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ARE OUR GRADUATES PREPARED?
Are Our Graduates Prepared? Comparing West Greene School District Graduates’ Soft
Skills to Greene County Employers’ Needs
A Doctoral Capstone Project
Submitted to the School of Graduate Studies and Research
Department of Education
In Partial Fulfillment of the
Requirements for the Degree of
Doctor of Education
Michael S. Hildreth
PennWest University of Pennsylvania
July 2025
ARE OUR GRADUATES PREPARED?
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Dedication
This was all made possible by my wife, the love of my life. Without her, this project ends
here. I dedicate this to you because of your dedication to me and our family.
ARE OUR GRADUATES PREPARED?
Acknowledgements
I would like to personally thank Dr. Stephanie Williams, my faculty chair, for being
patient with me as she pushed me through this project. Also, thank you to Dr. Bart Donley, my
external committee chair and friend, for helping me see this through. Lastly, thank you to Dr.
Brandon Robinson for being a confidant and sounding board as we went through this together
and for giving me my start in educational leadership.
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Table of Contents
Dedication
Acknowledgements
Table of Contents
List of Tables
Abstract
CHAPTER I. Introduction
Background
Capstone Focus
Research Questions
Expected Outcomes
Fiscal Implications
Summary
CHAPTER II. Literature Review
Required Skills
Hard Skills
Soft Skills
Acquisition of Soft Skills
Soft Skill Development
Teaching Soft Skills
Pre-Identified Soft Skills
Individual Skills
Working Under Pressure
Innovative Problem Solving
Integrity and Empathy
Emotional Intelligence
Collaborative Skills
Communication
Teamwork
Global and Cultural Diversity
Leadership
Business Etiquette
Procedural Skills
Quantitative Skills
Flexibility for Organizational Change
Critical Thinking
Responsibility to Get the Job Done
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Soft Skills in the Workplace and their Economic Impact
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Soft Skills and Working From Home
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Current and Projected Job Outlook of Greene County
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The Economic Outlook of Greene County, Pennsylvania
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Demographics of Greene County, Pennsylvania
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Economic Demographics of Greene County, Pennsylvania
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Comparing the Job Market of Greene County, Pennsylvania to the United States
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Demographics of Greene County, Pennsylvania Schools
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Graduate Preparedness of the West Greene School District
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Summary
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Chapter III. Methodology
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Purpose
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Setting and Participants
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Research Plan
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Research Methods & Data Collection
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Validity
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Summary
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Chapter IV. Data Analysis & Results
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Data Analysis
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Results
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Quantitative Industry Demographics
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Qualitative Industry Demographics
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Quantitative Ranking of Individual Soft Skills
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Qualitative Aggregation of Individual Soft Skills
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Quantitative Ranking of Collaborative Soft Skills
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Qualitative Aggregation of Collaborative Soft Skills
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Quantitative Ranking of Procedural Soft Skills
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Qualitative Aggregation of Procedural Soft Skills
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Quantitative Ranking of Soft Skills Categories: Individual, Collaborative, and Procedural
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Qualitative Aggregation Soft Skills Categories: Individual, Collaborative, and
Procedural
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Quantitative Alignment of Individual Soft Skills
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Qualitative Alignment of Individual Soft Skills
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Quantitative Alignment of Collaborative Soft Skills
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Qualitative Alignment of Collaborative Soft Skills
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Quantitative Alignment of Procedural Soft Skills
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Qualitative Alignment of Procedural Soft Skills
Quantitative Alignment of Soft Skill Categories: Individual, Collaborative, and
Procedural
Conclusion
Chapter V. Conclusions and Recommendations
Conclusions
Research Question 1
Individual Soft Skills
Collaborative Soft Skills
Procedural Soft Skills
Research Question 2
Research Question 3
Individual Soft Skills
Collaborative Soft Skills
Procedural Soft Skills
Limitations
Recommendations for Future Research
Summary
References
Appendix A
Appendix B
Appendix C
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List of Tables
Table 1
Table 2
Table 3
Table 4
Table 5
Table 6
Table 7
Table 8
Table 9
Table 10
Table 11
Table 12
Table 13
Table 14
Table 15
Table 16
Table 17
Table 18
Table 19
Table 20
Table 21
Table 22
Table 23
Table 24
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Abstract
This doctoral capstone project investigates the alignment between the soft skills taught by the
West Greene School District and the soft skills most valued by Greene County’s top employers.
In response to local economic challenges and a shrinking working-age population, this research
aims to determine whether the graduates of the West Greene School District are equipped with
the soft skills necessary for local employment and long-term community sustainability. The
purpose of the study was to assess the perceived value of the individual, collaborative, and
procedural soft skills amongst local business leaders and to evaluate whether the district’s current
programming sufficiently prepares students to meet workforce expectations. The research
employed a mixed-methods design, collecting both quantitative and qualitative data through
employer surveys. The findings revealed that “Communication,” “Responsibility to Get the Job
Done,” and “Integrity and Empathy,” stood out amongst the local employers. The study
concludes with strategic recommendations for aligning soft skill instruction with employer
expectations, emphasizing curriculum reform, community partnerships, and experiential learning
opportunities. This alignment is essential not only to improve graduate employability but also to
bolster the economic vitality of Greene County by cultivating a locally grounded,
workforce-ready population.
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CHAPTER I
Introduction
Greene County, Pennsylvania, is an area rich in history and culture, yet it faces economic
challenges as its workforce diminishes and its industries evolve. Once a community that was
thriving with opportunities centered on natural resources, the county now struggles with a
decline in working-age residents which prompts concerns about the sustainability of its local
economy (U.S. Census Bureau, 2023). The West Greene School District recognizes the critical
role it plays in addressing these challenges by preparing its graduates to meet the needs of the
local employers to give them the soft skills required to remain in the community after graduation.
This capstone research project seeks to bridge the gap between education and the
workforce demands by evaluating the alignment of the district’s soft skills curriculum with the
expectations of the local employers. Specifically, the study will identify the soft skills deemed
necessary by the top employers in Greene County, Pennsylvania, compare local job opportunities
with national trends, and assess whether graduates of the West Greene School District possess
the skills necessary to sustain the workforce and to contribute to the county’s economic vitality.
Soft skills encompass interpersonal and non-technical abilities that enhance communication,
problem- solving, and collaboration. These skills are crucial for navigating workplace
challenges, fostering positive relationships, and building a supportive workplace environment.
Unlike technical skills, soft skills are versatile and transferable across various roles and
industries, increasing an individual's professional value (Iorio et al., 2022).
The findings of this research have far reaching implications. They aim to inform strategic
curriculum adjustments, to foster stronger partnerships with local industries, and to ensure that
West Greene graduates are equipped to thrive in the county’s workforce. By addressing these
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issues, the district not only positions itself to enhance student outcomes and achievement but also
to contribute to the long-term economic stability of Greene County, Pennsylvania.This is vital to
the local economy because according to Börner et al. (2018), as data-driven tools and artificial
intelligence begin to more routinely handle specialized hard skills, the demand for humans with
industry specific soft skills will rise (p. 12635). Since managing interpersonal relationships and
applying data insights to real life and dynamic situations that cannot be automated at this time,
employees who can effectively collaborate and innovate in response to changing demands,
underscoring the enduring value of soft skills in the economy, will thrive at a rate much higher
than those who do not possess them (Börner et al., 2018. p. 12637). This research underscores
the importance of proactive educational planning to meet the demands of an evolving economy
in order to ensure that the district remains an integral part of Greene County, Pennsylvania's
future.
Background
Greene County, Pennsylvania, is a vibrant county in Pennsylvania that is rich with
history, culture, and pride. However, what was once a county booming with economic
opportunity surrounding natural resources is now facing economic hardships due to many
potential factors. Therefore, the West Greene School District is interested in updating its
curriculum and its philosophical outlook on what a graduate of the district should look like in
order to meet the economic needs of the county. It is important for the longevity of our district
that our graduates come back to live in the district upon high school or college graduation. The
current trends indicate that our graduates are leaving the district in order to pursue economic
opportunities elsewhere. If our district does not put mechanisms in place for our graduates to
enter the local workforce or a promise of employment upon graduation for our students going to
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college, we will have a tax windfall that may prove to be unsustainable, not to mention the
broader economic implications of our graduates leaving our communities. In order to create a
graduate who is suited for our local industries, we must work with these businesses to identify
their needs in potential applicants and determine job availability for our graduates. As the current
principal of West Greene Jr./Sr. High School, we must understand the needs of our local
economy, in order to find out what skills and competencies it needs in order to create a graduate
to fill that need. The purpose of this capstone research project is to identify the skills and
competencies that are needed of the local businesses in Greene County, Pennsylvania. In
addition, local businesses will provide feedback as to whether the school districts of Greene
County, Pennsylvania are providing the workforce with potential employees who are capable of
gaining positions for these businesses to sustain the local economy.
Capstone Focus
The goal of this capstone project is to determine where the soft skills curriculum in the
West Greene Junior/Senior High School is in relation to the desired soft skills of our local
employers in an effort to create the best soft skills curriculum in order to mold graduates who are
prepared and needed for the local workforce. According to Börner et al. (2018), while the
demand for technical skills is still very high, the rise of data-driven and collaborative work
environments has led to a much needed influx of workers with specific sets of soft skills (p.
12360). Therefore, this is important research to the vitality of Greene County’s economy because
of these changes. In addition, this curriculum could provide our graduates with an edge in
employment because as technical roles grow more specialized, professionals who have a strong
set of foundational soft skills to collaborate across the boundaries of technical disciplines who
can manage projects and effectively convey technical information to non-specialists are in great
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demand (Börner et al., 2018, p. 12637). According to the United States Census Bureau, in 2023,
58.1% of people in Greene County, Pennsylvania were between the ages of 20 and 64; whereas,
in 2010, 63.8% of people in Greene County, Pennsylvania were between the ages of 20 and 64.
This equates to a 5.7% drop in working- age individuals living in the county. This is
unacceptable. Potential reasons for this dramatic drop is that the students of the county may not
be prepared for the jobs in the local job market, students may be unaware of the opportunities
posed by the local job market, or we are not providing our students with a soft skills education to
prepare them for the local job market, but a job market elsewhere, causing graduates to relocate.
Whereas the West Greene School District cannot account for or dramatically improve the
economic opportunities that our students have upon graduation, we can prepare them to live and
work in our community with a curriculum of soft skills that could improve their productivity in
the workplace more than 13% (Adhvaryu et al., 2023, p. 2165). If our graduates continue to
relocate, and this trend continues, the West Greene School District will not be in a position to
economically sustain itself. Therefore, the District must take it upon itself to determine to what
degree the current job market matches up with national trends, to what extent local employers
value our current soft skills curriculum, and how do our graduates’ soft skills compare to the
needs of our local employers.
Research Questions
In order to achieve the goal of this academic research, the researcher has asked the
following questions:
1. To what extent do the top Greene County business employers in the public and private
sectors value the soft skills that are being taught by the West Greene School District for
entry level positions?
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2. To what extent do current job openings and projected job openings in Greene County
compare to statistics from the US Bureau of Labor and Statistics?
3. How do graduates with the desired soft skills, as determined by the West Greene School
District administration, compare to the soft skills identified by local business leaders to
sustain the workforce of Greene County, Pennsylvania?
Expected Outcomes
Through the research of this study, the West Greene School District will be able to
ascertain if the district is of the same mind as local employers as it pertains to important soft
skills, if the local job market is a snapshot of the national job market in terms of jobs available to
our graduates, and if the soft skills curriculum of the West Greene School District is creating
workers that are in demand in the local economy. The importance of an updated soft skills
curriculum cannot be understated. According to a study conducted by Laari and Dube (2017) on
nursing students’ perceptions on their soft skills training, soft skills training is seen as highly
valuable by 68.8% of respondents (p. 1). Based on the outcomes of the data collected, the
researcher aims to aid the West Greene School District by providing recommendations on how to
adapt the District’s soft skills curriculum in grades 7-12. These recommendations will certainly
have fiscal implications that must be addressed in order to sustain the District’s curriculum.
Fiscal Implications
The researcher believes that there are wide ranging fiscal implications associated with the
outcomes of these research questions. These implications will have a significant impact on
budgeting priorities of the district, resource allocation, and potential partnerships. The outcome
of these research questions could potentially lead to a curriculum redesign in terms of revising
curriculum materials, purchasing new resources, or providing professional development for
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teachers to emphasize the soft skills that local employers prioritize, in an effort to address
misalignment. Potential outcomes could lead to program expansions and program contractions
that could require additional funding. On the other hand, there could be opportunities for cost
saving measures as a result of the potential research outcomes. Once alignment exists between
our curriculum and local employers, the district could leverage partnerships that involve
co-funded programs, student internships, mentorship opportunities; opportunities that could
reduce the school’s financial burden. The fiscal implications of these research questions highlight
the need for careful evaluation of programs and strategic investment. With this being said, the
researcher believes that the outcomes of this research could be integrated into school districts of
similar size and demographic. Greene County, Pennsylvania, is very unique in its economic
makeup; therefore, large suburban or urban schools might not benefit from the data collected
because their economic opportunities are going to vary dramatically compared to the economic
opportunities in Greene County, Pennsylvania. However, the researcher does believe that having
a soft skills curriculum with the foundational soft skills described in the research can be
implemented by any school district, large or small. In addition, any school that would follow the
processes of this research could create a soft skills curriculum based on whatever outcomes the
district sees fit. The desired outcome of this research is to graduate locally employable adults;
whereas, other districts’ desired outcomes could vary. By addressing workforce skill alignment
proactively the district could not only enhance student outcomes but also secure financial
stability through partnerships, grants, and community support.
Summary
Greene County, Pennsylvania, once a thriving hub of natural resource-based industries,
now faces economic challenges and a declining working-age population. The West Greene
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School District aims to address these challenges by aligning its soft skills curriculum with the
needs of local employers to better prepare graduates for the workforce and give them the soft
skills to remain and thrive in the community. Homegrown graduates are particularly valuable in
areas like Greene County, Pennsylvania, where retaining skilled workers is essential to address
challenges such as a stagnant job market and a shrinking population (Regional Economic
Analysis Project, 2024). This research explores the value placed on the soft skills by Greene
County, Pennsylvania’s, top employers, the alignment between local and national job trends, and
the readiness of District Graduates to meet the demands of the local workforce. By identifying
gaps and opportunities, this study seeks to inform curriculum improvements, foster relationships
and partnerships with local industries, and to secure financial stability for the District and its
communities through strategic investment in these curriculums and alignment to local workforce
needs because highly qualified graduates not only possess technical knowledge, or hard skills,
but also demonstrate essential soft skills, such as communication, adaptability, and teamwork
that are increasingly recognized as vital for workplace success (Iorio et al., 2022).
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CHAPTER II
Literature Review
Highly qualified high school graduates are the cornerstone of a thriving workforce
because they bring valuable skills that contribute to economic and community development.
Highly qualified graduates not only possess technical knowledge, or hard skills, but also
demonstrate essential soft skills, such as communication, adaptability, and teamwork that are
increasingly recognized as vital for workplace success (Iorio et al., 2022). The integration of
these skills allows graduates to navigate diverse challenges and foster innovation, positioning
them as indispensable assets in modern industries. Moreover, graduates who are equipped with
these soft skills enhance workplace efficiency and productivity, which are critical in fostering
sustainable economic growth (Adhvaryu et al., 2023, p. 2168).
In addition to the individual benefits these skills provide, the contributions of
“homegrown” employees to their local economies are substantial. When graduates remain in
their communities, they enhance the local workforce by creating a sense of continuity, stability,
and investment in regional development. This alignment strengthens community ties and ensures
that the economic benefits of an educated workforce directly support local growth. Homegrown
graduates are particularly valuable in areas like Greene County, Pennsylvania, where retaining
skilled workers is essential to address challenges such as a stagnant job market and a shrinking
population (Regional Economic Analysis Project, 2024).
Greene County faces unique workforce needs that underline the importance of preparing
students for local employment. The county’s economy, rooted in industries like healthcare,
education, and natural resource extraction, requires a pipeline of qualified graduates who can
meet its workforce demands while possessing the soft skills necessary for adaptability in a
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changing economic landscape (Data USA, 2024). This literature review aims to explore the role
of soft skills, such as communication, adaptability, and teamwork in enhancing graduate
readiness and to assess how aligning educational outcomes with local workforce needs can
contribute to the economic revitalization of Greene County. By addressing these dynamics, this
study seeks to identify strategies to better prepare West Greene School District graduates for
meaningful employment and long-term success in their home community.
Required Skills
When discussing the types of skills that are pertinent to any job or industry, it is
important to distinguish skills between “hard skills” and “soft skills.” Both types of skills are
equally important in the workplace, but bring different dynamics. Whereas, hard skills establish
the foundation of skills required to have a job, soft skills enhance the workplace by increasing
workplace culture and job satisfaction amongst employees. In short, soft skills are the skills
required by employees to create a thriving and vibrant workplace.
Hard Skills
According to Hendarman and Cantner (2017), hard skills are defined as skills related to
technical aspects to do some tasks in the job and take into account the acquisition of knowledge
to be competent in the skill (p. 141). Historically, the focus of schools have been on the
acquisition of hard skills or technical skills. In fact, technical/hard skills are perceived by
graduates as being relatively more critical for getting a job (Rainsbury et al., 2002, p. 10). Since
hard/technical skills are the foundation of curriculums and rated by employers during interviews
to determine if a person is suited for employment, hard skills have been the area of focus for
training programs. A person must have the technical/hard skills to perform job duties. While hard
skills form the basis of a person’s ability to complete a job, soft skills are needed to enrich the
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workplace and to drive innovation. Therefore, the focus of this study is to determine which soft
skills should make up the foundation of curricular changes in the West Greene Jr./Sr. High
School. Since the focus of schools for years has been the acquisition of technical skills, schools
must adapt to enrich our focus to include soft skills in a student’s education.
Soft Skills
While it may be difficult to pinpoint which soft skills are more or less applicable to
various employers, defining the term “soft skill,” is not. Soft skills encompass interpersonal and
non-technical abilities that enhance communication, problem- solving, and collaboration. These
skills are crucial for navigating workplace challenges, fostering positive relationships, and
building a supportive workplace environment. Unlike technical skills, soft skills are versatile and
transferable across various roles and industries, increasing an individual's professional value
(Iorio et al., 2022). Soft skills encompass characteristics that make individuals valuable assets to
employers. Typically, soft skill training emphasizes relationship building and the importance of
interpersonal interactions, which are essential for fostering collaboration and positive
connections. Soft skills also enhance confidence in adapting to various situations (Iorio et al.,
2022). Ultimately, individuals equipped with strong soft skills become invaluable contributors
within any workforce. Therefore, our first focus must be on the acquisition of soft skills.
Acquisition of Soft Skills
Acquiring soft skills involves a blend of formal education, personal development, and
practical experiences. Karras (2022) emphasizes that schools play an essential role in helping
students develop workplace-relevant soft skills, and this acquisition should occur through
structured education and real-life practice (p. 42). While formal education is critical, Karras also
highlights the importance of real-life experiences. According to Khasanzanova (2017), engaging
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in volunteer work, employment, and social interactions serves as an effective way to develop soft
skills. Volunteering, in particular, offers a lower-stakes environment to practice these skills,
enhancing both personal and professional development (Khasanzanova, 2017, p. 367). Both
formal and informal methods are essential in acquiring soft skills, and once developed,
individuals must continue refining these abilities.
Soft Skill Development
The development of soft skills must occur in order for these skills to be ingrained into a
person's arsenal of readily available skills, but how are soft skills developed? Soft skills are
developed through experiential learning, social interactions, education, and training. They are
also developed through self-reflection and feedback, volunteering and community engagement,
and workplace exposure. Through continuous practice, exposure, learning, and reflection, soft
skill development and refinement will occur.
Khasanzyanova (2017) argues that soft skills are primarily developed through
experiential learning in non-formal settings, such as volunteering and other lower pressure work
situations. Through experiential learning by volunteering, Khasanzyanova (2017) emphasizes
that these activities provide a context in which individuals can practice and develop essential soft
skills in a “learning by doing” method (p. 373). Khasanzyanova (2017), shows that student
volunteers consciously reflect on the skills that are acquired through this volunteer work. This
conscious reflection and hands-on involvement allow young people to apply theoretical
knowledge in practical settings, which will allow them to transfer these skills more organically to
complex social issues and professional scenarios (p. 371). Khasanzyanova (2017), imparts that
this type of learning is more impactful than just school learning because it involves adaptation,
problem-solving, and self-management in unpredictable real-world contexts (p. 375). In essence,
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action and practice in combination with experiential learning are crucial in soft skill
development.
Not only do hard skills and soft skills vary based on definition but also how they are
taught. According to Barth et al. (2023), there is a distinct difference in how hard and soft skills
are taught. Hard skills are generally taught in a structured, technical environment with clear
objectives and very specialized training. This task-oriented training focuses on procedures and
includes skills such as operating machinery, managing software, or anything that is based on
specific tasks or algorithms with the specific outcome being the transfer of this knowledge from
the teacher to the student (pp. 236-237). The method or pedagogy of transferring hard skills is
best done through a constructivist and transmissive approach, meaning that that participants must
set a transfer goal while the teacher must ensure these transfer goals are met and to anticipate
possible implementation difficulties associated with the process (Barth et al., 2023, p. 238). In
contrast, soft skills require a more nuanced approach to teaching because these skills are less
directly transferable and much more context-dependent. Whereas hard skills require specialized
training with clear objectives, soft skill transfer requires methods such as observational learning,
feedback, and reflection. By utilizing these strategies, soft skill concepts can be internalized and
students will be much more able to apply the soft skills flexibly in unpredictable situations. The
design of this intentional transfer must incorporate opportunities for participants to reflect on
their experiences, receive feedback, and set personal goals for the application of soft skills in
different contexts (Barth et al., 2023, p. 248). The teaching and transfer of soft skills is much
more complex and dynamic than the teaching and transfer of hard skills. This leads to how one
must assess soft skills in the teaching and transfer of the skill.
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Soft skills, unlike hard skills, can only be observed by a critical observer. Therefore, soft
skills are assessed through behavioral assessments that measure the students’ abilities to apply
these skills in practical settings. In research completed by Tran et al. (2024), “Multiple Mini
Exams” or MME allowed for the assessment of soft skills (p. 2). MME are conducted where
students participate in role-play simulations like hypothetical patient interactions that were
recorded and scored based on the following criteria: Communication, bedside manner, and
teamwork. This approach to the assessment of these specific soft skills allowed the evaluators to
observe and score the soft skill transfer in a controlled and realistic environment. This provided
for a very practical assessment of the desired soft skills that are generally difficult to quantify
(Tran et al., 2024, p. 12). Assessing soft skills is typically done with subjective measures;
however, this study was able to quantify the subjective measures in order to ensure an objective
approach to soft skill acquisition. In the study by Tran et al. (2024), the review of the videotaped
simulations involved a detailed, rubric-scored process. This process involved two reviewers
watching the video recordings of the students role-playing in patient care scenarios and assessing
the students’ performance using a rubric with specific criteria for each of the following soft
skills: Obtaining background, bedside manners, and use of scientific and medical language (p.
12). The specific criteria for assessing these soft skills were determined collaboratively with
input from the course instructor to ensure alignment with learning objectives. In developing the
rubric, the researchers identified essential skills from the Association of Medical Colleges for
prospective medical students. The rubric was structured to provide clear, measurable indicators
for each skill which facilitated consistent and objective scoring during video review (Tran et al.,
2024, p. 2). Based on this specific research study, the importance of objectively assessing soft
skills cannot be understated in the acquisition and development of soft skills. While acquiring
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and developing soft skills are important to the workforce, it is incumbent upon the education
system to teach soft skills in order to promote a workforce that is equipped to handle the
challenges of tomorrow.
Teaching Soft Skills
The research offers various methods for teaching soft skills effectively and methods to
create best practices in soft skill education. One of these methods includes the Soft Skills
Training Program. Sutil-Martin and Otamendi (2021), created the structured Soft Skills Training
Program that uses “serious games” to help young students develop essential soft skills (pp. 3-4).
This specific program targets intrapersonal, interpersonal, personal social responsibility, and
organizational sustainability skills through gamified learning experiences. This educational
approach emphasizes experiential learning, where students engage actively in scenarios that
promote the development of soft skills critical for the workplace. The Soft Skills Training
Program also includes a pre and post training assessment to ensure objective improvement in the
desired areas that ensure the program’s effectiveness (Sutil-Martin & Otamendi, 2021, pp. 4-5).
This program is structured on and targets four broad categories of soft skills:
Interpersonal, intrapersonal, personal social responsibility, and organizational sustainability.
These skills are known in the program as the Four MacroSoftSkills. Each of the Four
MacroSoftSkills are divided into eight categories of soft skills known as MesoSoftSkills:
Self-knowledge, self-management, empathy, influence, strategic mindset, consciousness,
compassion, and morality. The MesoSoftSkills are then further subdivided into 21
MicroSoftSkills: Academic self-concept, emotional self-concept, social self-concept, family
self-concept, physical self-concept, volatility (emotional stability), withdrawal (self-control in
discomfort), adopting perspectives, understanding emotions, assertiveness, openness,
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industriousness, orderliness, kindness, common humanity, engagement, indifference, separation,
disengagement, idealism, and relativism (Sutil-Martin & Otamendi, 2021, pp. 6-7).
These skills are observed while students in the program play “Serious Games as Training
Tools.” These tools incorporate a variety of serious games, including gamestorming and
boardgames to engage participants in active learning. These games are tailored to develop each
skill level and are designed to be interactive and to promote behavioral change through
experiential learning. These games include Paradoxical Thinking, Emotions, Growing in
Mindfulness, Trust, Ikigai, Planning by Scenarios, and Compassion and Morality. This approach
is reinforced by a structured appraisal system that measures soft skill improvements over the
course of the program (Sutil-Martin & Otamendi, 2021, pp. 8-10). These tenets together create a
comprehensive framework that combines theory, measurement, and practice that makes the Soft
Skills Training Program a robust tool for fostering and assessing essential soft skills for the
modern workforce.
When evaluating the effectiveness of soft skills instructional programs, you should
address students’ perception of soft skills training programs. According to a study conducted by
Laari and Dube (2017) on nursing students’ perceptions on their soft skills training, soft skills
training is seen as highly valuable by 68.8% of respondents (p. 1). These respondents perceive
that soft skill training is highly valuable for their professional development and essential for
consistently delivering high quality patient care. The majority of students in the study recognize
that formal training in the soft skills that are specific to their profession would improve their
interactions with patients and colleagues. These students agreed that soft skills training should be
integrated into their nursing curriculum in order to enhance their clinical performance, make
them more compassionate caregivers, and help to address the gap in interpersonal skills that
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currently affects patient satisfaction and trust in healthcare (Laari & Dube, 2017, pp. 4-5). This
study shows that students see the benefit in soft skill training and acquisition. Teaching soft skills
will ensure that our students are prepared to handle the challenges of tomorrow, but which soft
skills are most important to be taught? In order to determine which soft skills our business
leaders find valuable, they must be provided with a list and description of pre-identified soft
skills.
Pre-Identified Soft Skills
Soft skills play a critical role in preparing students to sustain and enhance the local
workforce, equipping them to adapt alongside technological advancements. Given the broad
spectrum of soft skills, it is essential to identify those most relevant to the local workforce. A
study by Richie et al. (2022) identified key soft skills, categorized into three main areas:
Individual, collaborative, and procedural skills. Individual soft skills are working under pressure,
innovative problem-solving, integrity, empathy, and emotional intelligence. Collaborative skills
are communication, teamwork, global and cultural diversity, leadership skills, and professional
etiquette. Procedural skills are quantitative skills, flexibility, critical thinking, decisiveness, and
responsibility to complete tasks effectively (Richie et al., 2022, pp. 163-165). These skills
provide a foundation for programs that align with the needs of local employers.
Individual Skills
Individual soft skills refers to personal attributes and competencies that enhance an
individual’s ability to perform effectively and responsibly in a professional setting and are
essential to individually navigate workplace challenges and expectations. Developing these skills
enables a person to manage stress, make sound decisions, and maintain professionalism which
are foundational for personal success in any job role.
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Working Under Pressure
The first individual soft skill is working under pressure. Time management is the ability
to plan and organize priorities for work activities. Working smarter is an enabler to accomplish
more in less time without having to work harder. When time pressures are high, lack of time
management causes stress and reduces effectiveness (Vasanthakumari, 2019, p. 69).
Innovative Problem Solving
The next individual soft skill is innovative problem solving. This soft skill deals with
activities related to the job position and new ideas for improvements related to products and
services offerings provided by the organization (Succi & Canovi, 2019, p. 1835).
Integrity and Empathy
After innovative problem solving, there is integrity and empathy. According to Van
Deuren (2018), empathy and integrity are closely linked in fostering a strong values-driven
approach in the workplace. Empathy allows individuals to understand and respect the emotions,
perspectives, and needs for others. This is essential for effective teamwork, leadership, and
conflict resolution. On the other hand, integrity emphasizes honesty, ethical behavior, and
accountability (Van Deuren, 2018).
Emotional Intelligence
The last individual soft skill is emotional intelligence. Emotional intelligence is the
ability to recognize, understand, and manage one’s own emotions as well as the emotions of
others through self-awareness, self- regulation, social awareness, and relationship management
(Sadovyy et al., 2021, p. 2). According to Allam (2011), emotional intelligence is why people
excel in performance over others with the same level of training and experience (p. 71). The
attributes of emotional intelligence helps individuals navigate complex social environments,
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make better decisions, and build positive relationships which contribute to career success and
higher levels of personal and professional satisfaction (Allam, 2011, p. 77). By fostering
individual skills, employees become more adaptable and capable of navigating workplace
challenges independently.
Collaborative Skills
The next grouping of soft skills is collaborative skills. Collaborative skills are essential
abilities that enable individuals to work effectively with others towards shared goals. In today’s
increasingly collaborative workplaces, the ability to communicate clearly, to show empathy, and
contribute effectively to a team’s success is highly valued.
Communication
The first collaborative soft skill is communication. Communication is engaging in clear
and effective exchanges, both verbally and non-verbally, that are crucial for team success. All
employers place a priority on how an employee interacts with others, takes initiative, and
demonstrates the ability to achieve results. Skills related to business communication also include
traits that professionals use to convey information in the workplace. These skills are broad and
include active listening to use in negotiations or networking. Team collaboration includes giving
and receiving clear and succinct feedback to encourage creative thinking. Constructive feedback
supports reflective thinking and improvement (Valera, 2020, p. 190).
Teamwork
The next collaborative soft skill is teamwork, which is working collaboratively to support
group efforts, fostering trust and unity among team members. Phillips et al. (2020) identify
teamwork as a critical soft skill for employees at any level, to recognize the need for a mindset to
support the larger mission of the organization (p. 59). Attributes include coordinating,
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cooperating, and collaborating with others to build trust (Harlow, 2022, p. 47). Assisting team
members orchestrates the interdependent actions of motivation to evaluate the team’s mission.
Global and Cultural Diversity
Next, global and cultural diversity embraces diversity by recognizing and valuing
different cultural perspectives, which will ultimately enhance creativity and innovation within
teams. According to Florentine (2019), when diversity is present in the workplace, it sets the tone
for better performance. The risk of being publicly called out for lack of diversity in recruiting is
one way to lose competitive advantage. Companies are increasing their focus on diversity in the
workplace to avoid having a tarnished reputation.
Leadership
The next collaborative soft skill is leadership which is guiding and motivating others
towards common goals, often involving responsibility and influence. Leadership skills include
general personality traits such as self-confidence, enthusiasm, assertiveness, extraversion,
authenticity, trustworthiness, humility, and a sense of humor.
Business Etiquette
The last collaborative skill is business etiquette which is adhering to professional norms
and respectful interactions which maintain a respectful and productive work environment.
Collaborative skills enhance an employee’s ability to build positive working relationships,
resolve conflicts, and work productively with others, which are critical for achieving collective
goals and fostering a healthy work culture.
Procedural Skills
The last grouping of soft skills is procedural soft skills. Procedural soft skills are defined
as those skills needed to perform tasks or complete processes within an organization. Procedural
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skills help employees carry out tasks, adhere to organizational procedures, and apply analytical
thinking to make informed decisions. These skills are crucial for operational success and help
individuals navigate and fulfill the requirements of dynamic work environments (Richie et al.,
2022, p. 169).
Quantitative Skills
The first procedural soft skill is quantitative skills. This category of professional skills
involves reasoning and understanding numerical data to solve problems and make decisions.
Quantitative skills in fields such as health care, financial services, or manufacturing may indicate
the ability to conduct research and examine efficiency results, in addition to other numerical data
for decision making (Wilton, 2014, pp. 5-6).
Flexibility for Organizational Change
The next soft skill in this grouping is flexibility for organizational changes. This soft skill
focuses on the ability to adapt to shifts within an organization and demonstrating the ability to
adjust to tasks and priorities as needed. Depending on the position, the ability to accomplish
tasks that are dynamic and changing indicates the potential for high performance.
Critical Thinking
The next procedural soft skill is critical thinking which is the capacity to analyze
information, think logically, and approach problems systematically. After critical thinking, the
next skill is the ability to make decisive decisions which is being able to evaluate options and
make informed decisions in a timely manner. Considering alternative solutions will support the
cognitive process of a belief, or course of action based on several alternative options
(Vasanthakumari, 2019, p. 70). The pros and cons for each solution should match the course of
action related to the nearest desirable outcome. At a personal level, it is important to be focused
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only on the factors within the scope of control and recognize the factors outside the control for
decisions (Phillips et al., 2020, p. 59).
Responsibility to Get the Job Done
The last procedural soft skill is the responsibility to get the job done which is a
commitment to completing tasks reliably and effectively which includes being able to manage
time and ensure follow-through. Applying work habits such as maintaining wellness, time
management, follow through, and initiative creates the ability to contemplate information and
skill development (Phillips et al., 2020, p. 59). One example is the ability to determine the range
of tasks to organize and manage teamwork to achieve the desirable outcomes (Gruzdev et al.,
2018, p. 692). By focusing on procedural skills, employees can improve their efficiency and
reliability in job roles that require adherence to processes and problem-solving under varying
circumstances, making them valuable assets to organizations.
By structuring a soft skills program around the categories of individual, collaborative,
and procedural skills, the program can address a holistic set of competencies that support both
individual development and organizational success. This approach will ensure that employees
who enter the workforce from the West Greene School District are well-rounded, adaptable, and
prepared for diverse working demands that are aligned with educational outcomes from the
competencies that local employers deem essential. While the acquisition, development, and
teaching of soft skills are vital to understanding the process of learning soft skills, it is also
vitally important to understand why the workplace and workforce economically benefits from
employees with developed soft skills.
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Soft Skills in the Workplace and their Economic Impact
In the modern workplace, the demand for soft skills has steadily grown over time driven
by the evolution of the workforce and changes in job roles across various industries. Soft skills
are increasingly viewed as essential complements to technical skills that drive long-term career
success, productivity, and economic growth across sectors. According to Börner et al. (2018),
while the demand for technical skills is still very high, the rise of data-driven and collaborative
work environments has led to a much needed influx of workers with specific sets of soft skills (p.
12360). As automation and artificial intelligence begin handling more routine, technical tasks,
employers will need to seek employees who excel in interpersonal and cognitive skills that
cannot be replicated by machines or algorithms. Börner et al. (2018), also argues that as technical
roles grow more specialized, professionals who have a strong set of foundational soft skills to
collaborate across the boundaries of technical disciplines who can manage projects and
effectively convey technical information to non-specialists are in great demand (p. 12637). The
economic trends dictate the increased relevance of providing a soft skills curriculum in our
schools.
When examining the need for soft skills in the workplace, it is important to look at the
economic value that soft skills bring not only to an individual, but also to specific economic
sectors. In terms of individual career advancement, Tsalikova and Pakhotina (2019) argue that
professionals equipped with industry specific soft skills are better prepared to navigate complex
work environments and handle the diverse challenges of specific industries (p. 196). These skills
are essential for maintaining productivity and fostering positive workplace environments which
are both essential skills that are critical for individual career advancement. Possessing soft skills,
both a broad range and specific to an industry, make a person more resilient and capable of
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achieving sustainable career growth, even in rapidly changing industries (Tsalikova & Pakhotina,
2019, p. 191).
Soft skills that have been internalized by an individual can lead to individual economic
growth in career advancement, but on the other hand, a workforce that has employees trained in
industry-specific soft skills, provide economic value to those specific industrial sectors. For
example, the healthcare sector emphasizes soft skills such as empathy, communication, and
teamwork because these specific soft skills are essential for patient interaction, collaboration
with medical staff, and effective patient care. In the engineering and technology fields, soft skills
like problem solving, adaptability, and communication in multinational and interdisciplinary
settings where professionals need to explain complex ideas to a diverse audience are of the
utmost importance. The economic sectors of hospitality and tourism value interpersonal skills,
customer service, and emotional intelligence in order to manage customer interaction and to
ensure client satisfaction in high customer contact environments. Finally, sectors such as
information systems and security prioritize critical thinking, collaboration, and communication
because people working in these sectors address complex security issues working with
cross-functional teams (Tsalikova & Pakhotina, 2019, pp. 193-195).
The economic need for soft skills is growing exponentially by the minute with
automation and artificial intelligence. According to Rodriguez-Bustelo et al. (2020), automation
is expected to transform the workplace by significantly altering the types of skills in demand and
the nature of the jobs that will be coming available to the next generation of worker (pp. 1-2). As
automation and artificial intelligence technologies continue to advance, many routine and
predictable tasks are at a high risk of becoming automated. Unfortunately, this shift will
disproportionately impact blue collar jobs. On the other hand, there will be a rise in demand for
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roles consisting of soft skill rich abilities. Workers will need to adapt to this growing trend in
order to thrive in roles that cannot be replicated by machines or automation. This will require a
shift in the educational programs that produce the workers of tomorrow in order for the next
generation of workers to not be supplanted by automation or artificial intelligence
(Rodriguez-Bustelo et al., 2020, pp. 2-4). Therefore, technology will increase the importance of
workers with unique human skill sets possessing soft skills. Börner et al. (2018) explain that as
data-driven tools and artificial intelligence handle routine and specialized hard skills, the demand
for humans with industry specific soft skills will rise (p. 12635). Since managing interpersonal
relationships and applying data insights to real life and dynamic situations that cannot be
automated at this time, employees who can effectively collaborate and innovate in response to
changing demands, underscoring the enduring value of soft skills in the economy, will thrive at a
rate much higher than those who do not possess them (Börner et al., 2018, p. 12637).
In addition to a general need for soft skills in the workplace, there are tangible economic
returns from incorporating a soft skills training program to an employer’s workforce. According
to Adhvaryu et al. (2023), the economic returns of soft skills can be substantial, particularly in
productivity and cost-effectiveness for employers (pp. 2168-2169). In a study on garment
workers in India, Adhvaryu et al. (2023), found that workplace soft skills training improved
productivity by 13.5%, largely due to enhanced teamwork and collaboration (p. 2165). This
increase in productivity resulted from a large investment in soft skill training leading to a large
return on their investment of 256% in just eight months post-training. This study underscores
that the contribution of soft skills training on garment workers in India increased their
contributions and therefore promotion potential making them economically valuable (Adhvaryu
et al., 2023, pp. 2167-2169). Individuals with well-developed soft skills are more employable to
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work with and tend to have higher earnings. Employers value soft skills, especially for roles
requiring adaptability, teamwork, and customer service. This employability advantage helps
workers access better jobs and income, which will positively impact household economic
stability (Adhvaryu et al., 2023, p. 2166).
Workplace culture is very important to maintain a good work-home life balance. In fact,
according to Mennino et al. (2005), workplace culture affects employees’ ability to balance work
and family life. The study suggests that supportive and modern workplace cultures are essential
for reducing work-family conflict, highlighting the need for new ideas to improve workplace
culture (p. 21). Among many other factors that impact workplace culture, communication,
collaboration, and teamwork are key factors that create a workplace culture that creates a good
work-home life balance (Mennino et al., 2005, pp. 21-22). If workplaces have training programs
or if employees enter the workforce with these soft skills, workplace dynamics will be improved.
Since it is important for workplace dynamics to be positive for the sake of its workers, it
is important to look at key dynamics and the soft skills that are associated with them in order to
determine which soft skills have the most impact on a positive work culture. In a study
conducted by Sandlin, et al. (2018), the authors studied student perceptions of their performances
in team-based projects (p. 21). The study used the DISC Behavioral Style Assessment to
determine and understand students’ behavioral tendencies and how they influence team
interactions. The study concluded that teams with less compatible styles experienced more
challenges in cohesion. In addition, as students reflected on their ability to adjust their behavioral
styles to accommodate the team’s needs, students ascertained that adapting their behavioral style
will improve collaboration and communication (Sandlin et al., 2018, pp. 25-27). Therefore,
students who not only are aware of their strengths and weaknesses, but can also adapt their soft
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skills to the situation, will have a better work-life balance and live a happier existence. Since the
COVID-19 pandemic, the workforce composition has changed in terms of where people are
reporting to work. Therefore, it is integral to understand how soft skills impact the workforce if
the workforce is working from home.
Soft Skills and Working From Home
If the COVID-19 pandemic has taught us anything, it has taught us that we must be
prepared for a changing workforce at a moment’s notice. As the workforce continues to evolve as
a result of the pandemic, our hard and soft skills must evolve as well. The pandemic has created
a need for employees who are trained in different soft skills than before. With the shift to remote
work, employers are now looking for candidates who are adaptable, able to communicate, and
problem-solve. These skills have always been sought after by employers, but the shift to working
at home has intensified this need.
Ferreira et al. (2023) define the skill gap as the disparity between the skills that
organizations need for effective operation and those currently possessed by employees (p. 39).
The authors of this study surveyed employers and their satisfaction in their employee’s skills and
the importance of the skills. The outcome was that employers identified a gap between the
availability of problem-solving skills, adaptability, and communication in their employees.
(Ferreira et al. 2023, p. 42). In an effort to bridge this gap, Ferreira et al. (2023), found that
employers, especially in digital marketing and advertising provided training for these skills (p.
39). While remote working poses challenges to these training programs, the requisite soft skills
must be trained in order for a productive workplace to be maintained. Employers have begun
training on interpersonal skills, communication, emotional intelligence, and teamwork which are
all skills that need to be developed for the “new normal.” Training in those workplaces occurred
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in the form of online workshops and structured interactions designed to build communication
and collaboration skills across their virtual departments (Ferreira et al., 2023, p. 43).
The COVID pandemic has impacted the importance of social skills in the workplace. In
addition to changing what the workforce looks like, the pandemic has also changed the relevance
of specific soft skills in the workplace and the shift in working conditions could lead to a social
soft skill deficits that negatively impact productivity in certain sectors across demographic
groups (Gnecco et al., 2024, p. 647). These deficits could potentially lead to decreased
productivity and inefficiency in the workplace. Therefore, it is incumbent upon the schools to
adapt to these needs.
Gnecco et al. (2024), argue that the pandemic and shift to a virtual workplace in certain
sectors has led to skill deficits in the following soft skills: Empathy, coordination, teamwork, and
communication because of limited opportunities for direct social interactions, which are crucial
for team cohesion and effective collaboration (p. 653). Furthermore, certain age groups and
sectors were more affected than others. Workers under the age of 35, and sectors such as tourism,
commercial activities, and education show the greatest skill gaps. These skill gaps could
potentially lead to ongoing challenges in productivity and team dynamics which could impact
overall workplace morale and long-term organizational success if intentional skill-building
initiatives do not take place (Gnecco et al., 2024, pp. 650-677).
The pandemic and the move to remote working has increased the importance for social
soft skills like empathy, adaptability, and effective communication. These skills were once seen
as supplemental to traditional learning, but the changes in the workforce have taught us
differently. In addition, this shift has shown us that there are going to be persistent skill deficits
in certain sectors like tourism, education, and commercial services and that younger workers
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have been particularly impacted in the workforce by their lack of soft skills. In order to address
these skills deficits, it is clear that we must take a targeted approach to soft skills acquisition at
the primary and secondary levels of education, but also employers must develop their own soft
skills training program in order to increase productivity and to reduce the impact of the
pandemic-induced changes.
A common theme in addressing soft skills is addressing how soft skills have an impact on
workplace culture, and by extension, the mental health of the employee. With remote work
becoming more and more prevalent in our economy, the mental health of employees working at
home must also be addressed along with the soft skills at work to address mental health.
Working remotely is a new fold to our economy that does not come without its own
stressors. Remote workers experience more work-family conflicts because of the overlap of
personal and professional environments that lead to more frequent interruptions and more
challenges in balancing work and home responsibilities. This conflict is often heightened from
the employee working long hours with blurred work-home boundaries. Remote workers also
experience more isolation and burnout due to limited face- to- face interactions with colleagues.
This can contribute to feelings of loneliness and reduced social support. This isolation, coupled
with larger workloads has been associated with increased risk of burnout amongst some remote
workers (Andrade et al., 2024, p. 8). In addition, according to Andrade et al. (2024), there was a
significant prevalence of insomnia among remote workers at their 12 month follow- up (p. 1).
The disrupted work-life balance and increased stress from working in a home environment
without clear separation of personal and work time contributes to sleep disturbances and anxiety.
The findings of the study suggest that while remote work can offer protective benefits by
reducing certain physical stressors, it also introduces unique challenges for the remote worker.
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Fortunately there are ways to reduce these stressors in the in-home workplace, soft skills
training. According to Winarsunu et al. (2023), “life skills” training is described as a training
program that they have designed to improve individuals’ abilities in several skill areas (p. 1). The
skills that the authors allude to as “life skills” are soft skills. The soft skills they argue are critical
to reducing anxiety are decision making and problem solving, critical thinking, communication,
self-awareness, empathy, and coping skills (Winarsunu et al., 2023, p. 2). The purpose of their
study is to identify which soft skills help reduce anxiety in the remote workplace.
Winarsunu et al. (2023) argue that decision making and problem solving skills help
individuals make informed decisions and to solve everyday challenges effectively (p. 4). The
authors also argue that critical thinking can enhance an individual’s ability to think innovatively
and evaluate situations critically. Communication skills aid in improving verbal and non-verbal
communication that fosters positive interaction and builds stronger interpersonal relationships.
Self-awareness and empathy encourage individuals to develop a deeper understanding of
themselves and empathy towards others, while coping strategies help a person manage stress and
to regulate emotions in a healthy way (Winarsunu et al., 2023, pp. 5-6).
In conclusion, the COVID-19 pandemic has highlighted the need for stronger
management and training of soft skills in the workplaces, especially the remote workplace. Skills
like adaptability, empathy, communication, and stress management have become essential for
worker productivity and mental well-being. To bridge the gap, employers and academic
institutions must prioritize soft skills training to prevent burnout and isolation to foster a
healthier and more resilient workplace. In transitioning from soft skills, it is important to have a
basic understanding as to why our district is focusing on soft skills acquisition and its benefits for
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the workplace. In helping the reader understand this, it is valuable to understand the economic
outlook for our graduates in Greene County, Pennsylvania.
Current and Projected Job Outlook of Greene County
Greene County, Pennsylvania currently employs just more than 14,200 people. The
largest industries in Greene County, Pennsylvania, are health care and social services employing
around 2,640 people, retail trade which employs around 1,538 people and educational services
which employs around 1,322 people. Whereas these are the industry sectors that employ the most
people, the highest paying industries in the County are real estate & rental leasing paying around
$93, 214 on average and agriculture, forestry, fishing & hunting, and mining which pays around
$86, 118 on average (Data USA, 2024). These sectors alone account for 39% of the overall
employment in the county. While there are some sectors in the county that are thriving, the
Greene County Industrial Development Authority (GCIDA) is attempting to grow the economy.
The mission of the GCIDA's focus is on the creation, attraction, and retention of
businesses in Greene County, Pennsylvania. This department offers financial assistance through a
variety of loan programs and technical assistance to expand business opportunities throughout
the county through assistance for manufacturing and distribution investors interested in site
locations for new and expanding operations. This Authority offers money loan services through
their Revolving Loan Fund and Emergency Loan Program. The Emergency Loan Program offers
up to $50,000 dollars for 15 years at 1% to help local industries grow. The GCIDA works with
Waynesburg University and the University of Pittsburgh’s Institute of Entrepreneurial Excellence
to improve its outcomes. The GCIDA also provides resources to potential industrial developers
to aid in their search for economic development agencies, Greene County Realtors, the
Pittsburgh Regional Alliance, and GIS planning (Greene County, 2024).
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The GCIDA has several ways that it can help local students in the workforce. This
Authority could partner with local businesses, Waynesburg University, and the University of
Pittsburgh’s Institute of Entrepreneurial Excellence to create internship opportunities for local
students. In addition, it can organize tours of local industrial sites to expose students to local
career paths. The GCIDA could also work with its university partners to offer workshops for our
students interested in starting their own business. This partnership could also set the student up
with youth business grants to finance the ideas of our young entrepreneurs. However the GCIDA
could work with our students as a benefit to the local economy and our school as a liaison
between the school and industry. This will be needed to further the opportunities for our
graduates because the competition for jobs will only increase as the economic outlook of Greene
County, Pennsylvania changes.
The Economic Outlook of Greene County, Pennsylvania
In order to project an area’s real GDP, economists suggest using the following formula:
real GDP at starting date x (1+Growth rate of real GDP)Years (Mankiw, 2020, p. 489). It is
important to use real GDP because real GDP is adjusted for inflation. In addition, a ten year
projection is being used because if a five year projection is used, the recession from the COVID19 Pandemic will skew the results. The most recent real GDP calculation is from 2022, which is
$3,092,532. To project 10 years in the future, the real GDP from 2012 will be used which is
$3,052,491 (Regional Economic Analysis Project, 2024). Therefore, the projected GDP of
Greene County, Pennsylvania, in 2032 is: $3,092,532 x (1+ ($3,092,532-$3,052,491)
/$3,092,532)10= $3,517,095.69 real GDP. This incremental growth over the last decade implies a
stable economic base with no significant declines, but it also points to limited diversification or
expansion into high growth sectors. Based on this data, the local economy could benefit from
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targeted interventions to accelerate growth and capitalize on emerging opportunities. Our school
could be a hub to drive this innovation through soft skills training programs because compared to
the United States, Greene County, Pennsylvania needs to keep pace.
Demographics of Greene County, Pennsylvania
Greene County, Pennsylvania, is located in the southwestern most corner of
Pennsylvania. Greene County, Pennsylvania, boasts a population of 35,800 people, ranking it
58th out of Pennsylvania’s 67 counties (Data USA, 2024). Greene County is home to five public
school districts: Carmichaels Area School District, Central Greene School District,
Jefferson-Morgan School District, Southeastern Greene School District, and West Greene School
District. For the purposes of this capstone research project, the researcher will discuss important
demographics that pertain to the five school districts of Greene County, Pennsylvania, with a
specific focus on the West Greene School District. Not only will the researcher discuss
population demographics, but also economic demographics, as they are critical in understanding
the population of Greene County, Pennsylvania, and more specifically, the West Greene School
District
Economic Demographics of Greene County, Pennsylvania
Greene County, Pennsylvania’s economy is centered around mining and natural
resources, government, education, healthcare and social assistance, and retail. The economy,
having little diversity, still has a need for workers as the economy of Greene County,
Pennsylvania grew about 0.5% by roughly adding 100 jobs between 2021 and 2022 (Data USA,
2024). With an unemployment rate of 5.2%, there is little room for graduates of Greene County
schools to fit into the local economy (U.S. Census Bureau, 2024c). According to Data USA
(2024), roughly 18% of the Greene County, Pennsylvania’s economy is focused on healthcare
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and social assistance which grew around 8% in 2022. The fastest growing industries in the
county are finance, which grew 25%, and insurance and educational services, which grew 21%
(Data USA, 2024). While the economic growth of Greene County’s industries is relatively
stagnant, Greene County schools are still graduating students who need to find their way into
these industries. The subjects of this study, the industries being surveyed, are the top ten
employers in Greene County, Pennsylvania, in terms of the number of employees the business
employs, who are willing and able to complete the survey. These industries, listed in Appendix
A, are the backbone of the economy of Greene County, Pennsylvania.
Families of Greene County, Pennsylvania, have a median household income of $66,283
with property values hovering around $140,900, which is nearly half of the national average. In
addition in 2023, nearly 9% of Greene County’s population was living with severe housing
problems and almost 13% of the population currently lives below the poverty line (Data USA,
2024). As shown in Table 1, the rate of poverty in the county is exemplified by the percentages
of students who receive free and reduced lunch. The economic strain on Greene County residents
significantly impacts the local economy because small businesses have difficulty thriving,
leading to a diminished market of entrepreneurs and startups because of the ever increasing
poverty level and disposable income of the region. Whereas the bleak economic outlook of the
county presents great challenges, it also offers a great deal of promise for something better for
students entering into the job market who, with job ready skills, can help grow the economy.
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Table 1
Greene County Schools Free/Reduced Lunch Figures
School District
Percentage
Carmichaels Area School District
53.7%
Central Greene School District
51.1%
Jefferson-Morgan School District
54.6%
Southeastern Greene School District
West Greene School District
49%
55.6%
Note. Explanatory Note (Pennsylvania Department of Education, 2024a-e, Future Ready PA
Index)
Comparing the Job Market of Greene County, Pennsylvania to the United States
When comparing job markets, it is important to first compare unemployment rates. The
unemployment rate in the United States is 4.1% while the rate for Greene County, Pennsylvania
is 5.2% as noted previously (U.S. Bureau of Labor Statistics, 2024). The largest industries by
GDP in the United States are hospitals; health and medical insurance; commercial banking, drug,
cosmetic, and toiletry wholesaling; pharmaceuticals wholesaling; new car dealers; life insurance
and annuities; public schooling; property, casualty, and direct insurance; and retirement and
pension planning (IBISWorld, 2024). When comparing the United States’ economy with that of
Greene County, Pennsylvania, the lack of diversity and dependence on traditional economic
sectors in the Greene County economy highlight the need for strategic partnerships between the
local schools and the local employers. These strategic partnerships would focus on aligning
education and training with emerging and stalwart industries to ensure the economic vitality of
the region.
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Demographics of Greene County, Pennsylvania Schools
Student enrollment is a demographic marker that is indicative of potential future
employees to the businesses of Greene County. Graduates remaining in the region are essential
for the economic stability of Greene County, Pennsylvania. Therefore, it is important to know
how many potential future employees exist in the county. Table 2 lists the enrollment numbers
for each district since the 2020-2021 school year. As the schools in Greene County continue to
graduate students into the local job market, students in Greene County face additional
competition from 5.2% of the population, the unemployed population, of Greene County (U.S.
Census Bureau, 2024c). Approximately 6.8% of Greene County is nearing retirement age, the
students of Greene County must be highly marketable to employers in Greene County (U.S.
Census Bureau, 2024a).
Table 2
Greene County Schools Enrollment Figures
School District
School Year
2020-2021
2021-2022
2022-2023
2023-2024
Enrollment
Carmichaels
Area
997
989
961
968
Central Greene
1505
1487
1510
1443
JeffersonMorgan
773
776
792
779
Southeastern
Greene
549
587
580
580
West Greene
643
646
674
649
Note. Explanatory Note (Pennsylvania Department of Education, 2024f, Public school
enrollment reports)
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36
In order for the economy of Greene County, Pennsylvania, to thrive it needs highly
skilled and competent workers to fill jobs. Therefore it is important to understand the number of
graduates potentially entering into the workforce from the Greene County schools. To project
future enrollment numbers for each school district, it is important to examine from Table 3 the
total population numbers of each school district over the last four years in addition to each
school’s enrollment figures from Table 2 in order to predict the future enrollment of each school.
These numbers are based on the 2020 Census Data and will enable the researcher to create a
student population to overall population ratio. These ratios identified in Table 4 are completed
for 2020, 2021, 2022, and 2023. Extrapolation is a projection technique that uses aggregated data
from the past to project into the future. When making population projections, past and current
census information is used to project future population size. Extrapolation is done under the
basic assumption that the characteristics of the more recent period of development for a locale
are expected to continue in the future (Measure Evaluation, n.d.). In order to extrapolate data for
the next two years, the researcher will use the most recent four years of historical data, as it can
be expected that the population will change at that rate (Measure Evaluation, n.d.).
Only using the rate of change from the last four years of student enrollment may not
create a reliable enough extrapolation. More reliable enrollment projections can be ascertained
by using the average historic ratio of student population compared to the overall population.
Table 3 lists each school’s total population from the last four years and their average change per
year. The average change per year is a critical aspect in calculating the ratio because it will allow
the researcher to extrapolate the total population of each district over the next two years as
shown in Table 5, by multiplying the average change per year percentage by the 2023 population
number and then adding the result to the 2023 population number to get the 2024 projection.
ARE OUR GRADUATES PREPARED?
37
This process will be imitated to determine the 2025 projection, using the 2024 projection as a
baseline. Table 4 identifies the desired ratio by dividing the past enrollment figures of each
school by its past total population of that year, thus establishing a ratio that can be used to make
proper extrapolations of enrollments for the next two years by using the average percentage of
the four years. Now that the ratio by percentage has been established in Table 4, the average ratio
by percent of Greene County School Districts’ enrollment to total population will be multiplied
by the population projection figures and added to that year’s population from Table 5 in Table 6.
Table 6 shows the enrollment projections for each school district based on the above
calculations.
Table 3
Greene County School Districts’ Total Population
School District
Census Year
2020
2021
2022
2023
Total Population
Carmichaels
Area
6706
6877
6830
6815
Central Greene
14892
14820
14741
14984
JeffersonMorgan
5327
5214
5266
5567
Southeastern
Greene
4685
4673
4583
4322
West Greene
4874
4664
4361
4266
Average Population Change
Carmichaels
Area
2020 to 2021
2021 to 2022
2022 to 2023
Average Change
2.55%
-0.68%
-0.22%
0.62%
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38
Central Greene
-0.48%
-0.53%
1.65%
0.21%
JeffersonMorgan
-2.12%
1.0%
5.72%
1.53%
Southeastern
Greene
-0.26%
-1.93%
-5.7%
-2.63%
West Greene
-4.31%
-6.5%
-2.18%
-4.33%
Note. Explanatory Note (United States Census Bureau, 2020a-e)
Table 4
Ratio by Percent: Greene County School Districts’ Enrollment to Total Population
School
District
Census Year
2020
2021
2022
2023
Average
Ratio by Percent
Carmichaels
Area
14.87%
14.38%
14.07%
14.20%
14.38%
Central
Greene
10.11%
10.03%
10.24%
9.63%
10%
JeffersonMorgan
14.51%
14.88%
15.04%
13.99%
14.61%
Southeastern
Greene
11.72%
12.56%
12.66%
13.42%
12.59%
West Greene
13.19%
13.85%
15.46%
15.21%
14.43%
Note. The ratio by percent is calculated by dividing Greene County School Districts’ Total
Population (Table 3) by Greene County Schools Enrollment Figures (Table 2) and multiplying by
100 for each year.
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39
Table 5
Population Projections
School District
Year
2024
2025
Carmichaels
Area
6858
6901
Central Greene
15016
15048
JeffersonMorgan
5653
5740
Southeastern
Greene
4209
4099
West Greene
4082
3906
Note. Population Projections are calculated by multiplying the average change per year
percentage (Table 3) by the total population and then adding the result to the total population to
get the current year’s projection.
Table 6
Enrollment Projections
School District
Year
2024
2025
Carmichaels
Area
987
993
Central Greene
1502
1505
JeffersonMorgan
826
839
Southeastern
530
517
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40
Greene
West Greene
590
564
Note. Enrollment Projections are calculated by multiplying the average ratio by percent of
Greene County School Districts’ enrollment to total population by the population projection
figures and added to that year’s population.
The data from the projections in Table 6 show that two of the five districts will lose
enrollment and the other three districts will maintain little growth, but growth none-the-less. This
data shows us that there will not be a large influx in the population of Greene County,
Pennsylvania schools. What is more troubling is that the West Greene School District will lose
the largest percentage of students in the county. This means that the West Greene School District
must make every effort to attract families by making the district stand out. One way the district
can generate an influx of population is by creating curricular change around soft skills that are
tailored to the economy of Greene County, Pennsylvania that make the West Greene School
District graduate a more desired commodity. Thus making the District a more marketable
resource for families looking for a change in their child’s education.
Graduate Preparedness of the West Greene School District
The West Greene School District consists of the entire western portion of Greene County,
Pennsylvania. The District spans a geographic area of 253 square miles and has on average 17.2
people per square mile (Census Reporter, 2024). The district has a total population of 4266, as
indicated in Table 3 and is projected to drop in 2025 to 3906 as indicated in Table 5. According
to Table 2, the District currently has 649 students enrolled and enrollment is projected to drop to
564 students in 2025, as indicated in Table 6. Based on the figures in Table 1, the district as a
whole has a free/reduced lunch percentage of 55.6%. This number is so high because the median
ARE OUR GRADUATES PREPARED?
41
household income is $66,258, which is about $4,000 less than the median household income of
Greene County as a whole and a whopping $11,000 less than the median household income of
Pennsylvania’s households (Census Reporter, 2024). Table 7 indicates that it takes the average
person living in the West Greene School District 28.2 minutes to drive to work. These
demographics signify the challenge that potential employees living in the West Greene School
District will face in an effort to participate in the local economy.
Table 7
Travel Time to Work
Travel Time
Percent of Population
Less than 10 Minutes
14.6%
10 to 14 Minutes
11.6%
15 to 19 Minutes
11.7%
20 to 24 Minutes
9.4%
25 to 29 Minutes
6.8%
30 to 34 Minutes
13.6%
35 to 44 Minutes
11.6%
45 to 59 Minutes
10.3%
60 Minutes of More
10.3%
Note. Explanatory Note (U.S. Census Bureau. 2024b. Greene County, PA commute data.)
The projected population and enrollment decline suggests a decreasing tax base which
may lead to reduced local revenue for the school district, thus impacting the West Greene School
District’s ability to maintain or improve educational services and infrastructure. A substantial
portion of the District’s population relies upon county, state, and federal programs to provide
assistance as evidenced by 55.6% of students qualifying for free and reduced lunch as denoted in
ARE OUR GRADUATES PREPARED?
42
Table 1. The high level of free and reduced lunch implies a sustained demand for governmental
assistance and reliance upon social programs. The District’s median household income of $62,
258, being much lower than the state median of $73,170 and county median of $66,283, suggests
limited discretionary income amongst residents (Data USA, 2004). This could lead to decreased
local spending which can negatively impact local businesses and economic vitality. In addition to
a lower median income, the population of West Greene School District often experiences
additional challenges such as increased commuting costs from driving longer distances to work,
as denoted in Table 7, which will further reduce the amount of discretionary income a family will
have for school related expenses which will further negatively impact school resources, and
increased family relocation as shown by decreasing enrollments in Table 6. All of these factors
not only impact the families of the West Greene School District, but also the resources that the
district will be able to provide to its students.
The West Greene School District cannot afford for its population to relocate upon
graduation. Graduates of the West Greene School District must take advantage of economic
opportunities in Greene County to increase the likelihood that they will stay and be productive
members of society and taxpayers in the West Greene School District. The students of the West
Greene School District face more than preparedness challenges when entering into the
workforce. One such challenge is the unemployment rate of Greene County, Pennsylvania, is
5.2%, so the graduates of the West Greene School District are not only facing competition from
people outside of the county, but also the unemployed in Greene County looking for economic
opportunity (U.S. Census Bureau, 2024c). Working with the workforce of Greene County, the
West Greene School District is committed to assisting its students to address not only the obvious
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43
economic challenges that students will face, but also address the skills deficit that might exist,
especially in the area of soft skills.
Summary
The demographics, economic landscape, and the workforce needs of Greene County,
Pennsylvania, particularly in the West Greene School District demonstrates the need for
something more to be provided for our students in order for them to be successful and
competitive in the Greene County economy. Facing declining population, limited job market
growth, and higher levels of poverty, the West Greene School District faces economic challenges
that impact both local businesses and employment opportunities. Therefore, students must be
equipped with the skills, particularly soft skills that focus on personal, collaborative, and
procedural competencies that are essential for adapting to dynamic workplace environments and
automation-driven challenges. Soft Skills are identified as crucial for career success and to
revitalize the local economy. To address these needs, experiential learning methods, such as
volunteering and interactive programs are effective ways to help students acquire these skills.
Through a well-structured curriculum, the West Greene School District will incorporate these
skills in fostering a more prepared and adaptable graduate which will enhance a student’s
employability and support economic growth within Greene County.
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44
Chapter III
Methodology
In many rural communities across the United States, schools are deeply intertwined with
the economic health and vitality of the region. This is especially true in Greene County,
Pennsylvania, where economic challenges such as a dwindling working-age population,
increasing poverty rates, and a stagnant job market have placed pressure on local institutions to
adapt and respond (U.S. Census Bureau, 2023). Unlike urban and suburban districts that benefit
from a more diversified tax base and broader economic opportunities, rural districts like the West
Greene School District must rely heavily on the economic contributions of local families and
homeowners to sustain operations. As such, ensuring that educational programming aligns with
the needs of the local economy is not simply a matter of curriculum design; it is a matter of
district survival. The purpose of these methods is to investigate how West Greene School District
can develop a strategic approach to preparing its students for local employment through the
identification and integration of essential soft skills as required by the county's top employers.
The purpose of this research is to determine which soft skills are most valued by the
leading employers in Greene County, Pennsylvania, and how the West Greene School District
can align its educational practices to meet these needs. While the implementation of a soft skills
curriculum is beyond the immediate scope of this study, the findings will serve as a foundational
step for district leadership in designing such a program. Specifically, this research aims to inform
the development of a soft skills curriculum aligned with the West Greene School District’s
Positive Behavior Interventions and Supports (PBIS) framework, and then ultimately embedding
these competencies into a profile of a West Greene graduate. This alignment is crucial in
ARE OUR GRADUATES PREPARED?
45
reversing trends of graduate outmigration and in fostering sustainable economic development
within the region.
To best achieve these goals, the research was conducted through a mixed methods
approach using a concurrent embedded design. The study surveyed the top ten employers in
Greene County, who were willing to participate, as identified by the Pennsylvania Department of
Labor and Industry Center for Workforce Information and Analysis. The goal of collecting data
from these employers was to gain a comprehensive understanding of the soft skills they prioritize
and to assess the extent to which these skills are currently being taught in the West Greene
School District. As automation and technological advancements continue to reshape the
employment landscape, employers are placing increased value on competencies such as
communication, adaptability, collaboration, and emotional intelligence (Iorio et al., 2022).
However, measuring these skills in a survey presents a significant challenge, and traditional
quantitative methods alone often fall short. To address this, the mixed methods design allowed
for the simultaneous collection of both quantitative and qualitative data, ensuring a nuanced and
holistic analysis. Quantitative data included responses regarding industry sectors, workforce size,
job projections, and rankings of soft skills, while qualitative data provided contextual insights
into the experiences and perspectives of local employers.
Ultimately, the goal of this research is to empower the West Greene School District with
the data and insights necessary to cultivate a workforce-ready graduate. As rural communities
continue to navigate complex economic realities, schools must play an active role in regional
development by ensuring that students are equipped not only with academic knowledge but also
with the practical, interpersonal, and problem-solving skills demanded by today’s employers.
Through strategic alignment with local economic needs, the district has an opportunity to not
ARE OUR GRADUATES PREPARED?
46
only enhance student outcomes but also to contribute meaningfully to the revitalization of
Greene County.
Purpose
The working age population of Greene County, Pennsylvania, and rates of poverty have
increased in a stagnant job market (U.S. Census Bureau, 2023). The West Greene School district
has relied upon the economic vitality of the family and homeowner for tax revenue
disproportionately more than its urban and suburban counterparts, to survive, it has been forced
to look inward to ensure its programming has met the needs of our local economy to ensure that
graduates of the West Greene School District have the skills and competencies necessary to find
gainful, local employment. The purpose of this research was to determine the soft skills that the
top employers in Greene County required in potential candidates. While the next step of the
process was outside of the scope of this study, this data will be used by the West Greene School
District to create a soft skills curriculum that focuses on targeted soft skills in three primary
categories: Individual, collaborative, and procedural soft skills (Richie et al., 2022). These soft
skills will be aligned with positive behavior interventions and supports, to be integrated into the
persona of the West Greene graduate.
Setting and Participants
The scope of the research encompassed ten of the top employers in Greene County who
completed the survey. “Top” employers are defined in this study as businesses that employ the
most people in Greene County, Pennsylvania. Therefore, number one on the list of top
employers, employs more people than the second employer on the list, and so on. The survey
was sent out to the top 20 employers. While the initial goal was to get 100% participation from
the top ten employers, it became increasingly obvious to the researcher that was not probable.
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47
Therefore the scope of survey participants evolved over time as the researcher found that each of
the top ten employers were not willing to complete the survey. While the majority of the
respondents were in the top ten, the scope had to be broadened because it became clear that not
all ten would respond. This would point to a 50% participation rate amongst the top 20
employers in Greene County, Pennsylvania. While it is a small sample size, the employers who
chose to complete the survey will remain anonymous. The table in Appendix A, from the
Pennsylvania Department of Labor and Industry Center for Workforce Information and Analysis,
lists and names the top 50 employers in Greene County, Pennsylvania in the fourth quarter of
2023 (Pennsylvania Department of Labor & Industry Center for Workforce Information &
Analysis, 2023). These employers employ the most people in Greene County, Pennsylvania, and
need students from the West Greene School District to sustain their workforces. The only
identifying factor listed was the employers’ North American Industry Classification System
(NAICS) industry code. The NAICS is the standard used by federal statistical industries to
classify business establishments for the purpose of collecting, analyzing, and publishing
statistical data related to the United States business economy (U.S. Census Bureau, 2024d).
Table 8 illustrates the NAICS codes that employers in this study could choose from.
Table 8
NAICS Descriptors
Category
Subcategory
Goods-Producing Excluding Agriculture
Mining
Goods-Producing Excluding Agriculture
Construction
Goods-Producing Excluding Agriculture
Manufacturing
Service-Producing Excluding Special Industries
Utilities
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48
Service-Producing Excluding Special Industries
Wholesale Trade
Service-Producing Excluding Special Industries
Retail Trade
Service-Producing Excluding Special Industries
Transportation and Warehousing
Service-Producing Excluding Special Industries
Information
Service-Producing Excluding Special Industries
Financial Activities
Service-Producing Excluding Special Industries Professional and Business Services
Service-Producing Excluding Special Industries
Educational Services
Service-Producing Excluding Special Industries
Health Care and Social Assistance
Service-Producing Excluding Special Industries
Leisure and Hospitality
Service-Producing Excluding Special Industries
Other Services
Government
Federal Government
Government
State and Local Government
These descriptors are generally described by descriptor numbers based on NAICS coding. The
goal of collecting data from this list of participants was to create curricular programs to integrate
the soft skills that these employers desired the most in order for our school to educate graduates
best suited for the local workforce.
Each potential participant in the study was provided with a Participant Informed Consent
(Appendix B) before completing the survey. In order for participants to complete the survey,
participants were required to accept the informed consent. The purpose of informed consent was
to ensure that the person taking the survey agreed that they are freely and knowingly taking part
in the study before the study is completed. Informed consent serves as a critical safeguard that
ensures that participants understand that they are autonomous agents making an informed choice
about their participation (U.S. Department of Health and Human Services, 2025). Each
ARE OUR GRADUATES PREPARED?
participant knowingly entered into completing the survey once informed consent was received
eager to provide data about potential employees.
Research Plan
After a systematic review of the literature, it is clear that soft skills were essential
in modern workplaces, especially as automation has taken over many technical tasks.
Employers increasingly valued soft skills like communication, adaptability, teamwork, and
emotional intelligence (Iorio et al., 2022). Therefore, it was critical to our local economy
that the West Greene School District prepared students with these skills. This study
surveyed the top employers in Greene County to identify soft skills that were most
desirable to their businesses in order for the West Greene School District to make a plan to
implement a soft skills program at the junior/senior high school level. To reiterate, the
“Top” employers are defined in this study as businesses that employ the most people in
Greene County, Pennsylvania. Therefore, number one on the list of top employers,
employs more people than the second employer on the list, and so on. Therefore, the
largest employers in terms of number of people employed in Greene County,
Pennsylvania, were surveyed in this study to find the soft skills that they find most
desirable.
In reviewing the literature on types and categories of soft skills, it became
increasingly obvious that important soft skills were difficult to measure in a purely
quantitative way because of the sheer number of potential soft skills that could be required
by employers. Each piece of literature would point to different soft skills with different
definitions than the last piece of literature. There was not simply an aggregate list of soft
skills that employers could choose from to determine which ones were most valuable to a
49
ARE OUR GRADUATES PREPARED?
50
business. Therefore, a mixed methods approach needed to be employed in the research
design in order for the researcher to obtain results that were free from researcher bias to
aggregate the soft skills that were important to our local economy that may have been
overlooked by the researcher. The mixed methods approach with concurrent embedded
design allowed the researcher to explore statistical feedback from the employers, but also
qualitative employer feedback to gain a fuller picture of what soft skills were needed by
the local economy.
The study used a mixed methods approach with a concurrent embedded design,
primarily collecting quantitative data through survey responses about employer sectors,
workforce size, projected job openings, and valued soft skills. Participants could also
suggest additional soft skills that they felt were important to their operations. Qualitative
data was embedded into the survey to gather insights on current and future job
opportunities for students, compared with state and national trends. This method enabled
the researcher to gain a comprehensive understanding of the job market and how the
school can better prepare students for employment.
The basic premise of this research was to determine a way in which the West Greene
School District could develop programming in order to develop a graduate with the soft skills
necessary to thrive in the local economy. There was a clear disconnect between the soft skills
that have been historically ingrained in a West Greene graduate and what was needed by the
local workforce exhibited by the gradual outmigration of graduates and economic decline. This
research targeted local employers to determine the soft skills they valued, it compared those
skills with what is currently taught in the District, and it included questions to gain insights on
what would be available to our students in the local job market to determine the long-term needs
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51
of the workforce. The research plan met the needs of the research problem and used a robust,
mixed methods approach to gather valuable insights that were focused on localized, actionable
solutions to guide reform in the West Greene School District in an attempt to revitalize the local
economy.
Research Methods & Data Collection
The researcher gained approval from the Jefferson-Morgan School District
Superintendent on June 24, 2024, and the research timeline began with the Institutional Review
Board (IRB) approval on August 16, 2024 (Appendix C). However, after the researcher had been
given approval by the IRB, the researcher gained employment in the West Greene School District
as the Jr./Sr. High School Principal. Therefore, the researcher proposed a change of school
district as the basis of the research to the IRB on September 24, 2024, upon receipt of approval
from the West Greene School District Superintendent on September 22, 2024. The change was
approved and the research timeline began with the Institutional Review Board (IRB) approval on
September 30, 2024. The Google Form survey questionnaire was sent to qualifying employers in
early January. The scope of surveyed employers was increased from the top 10 to the top 20 in
March to ensure at least 10 responses from the top employers in Greene County, Pennsylvania.
The survey was open through April 2025. Table 9 illustrates the researcher’s timeline, research
questions, and correlated survey questions.
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52
Table 9
Data Collection Timeline and Survey Questions
Timeline for
survey
questions:
Surveys will be sent electronically and be available from December 23, 2024,
to April 30, 2025. After three weeks of the first ten employers having the
survey and being notified, five more employers will be sent the survey. I will
follow this pattern until the top twenty employers in Greene County,
Pennsylvania, have been provided the survey. Reminders will be sent every
three weeks to employers until ten surveys have been completed.
Research Question: How do graduates with the desired soft skills, as determined by the West
Greene School District administration, compare to the soft skills identified by local business
leaders to sustain the workforce of Greene County, Pennsylvania?
Data Type:
Quantitative
Survey Questions
On a scale from "Not Aligned" to "Perfectly Aligned", how closely do you
think the following Individual soft skills match the soft skills you consider
important to your workforce?
Short Descriptions:
Work Under Pressure- Time management involves effectively planning and
organizing priorities to optimize productivity and minimize stress. It enhances
performance under pressure and supports lifelong learning through continuous
self-assessment and improvement.
Innovative Problem-Solving- Innovative ideas and job-related activities are
vital for enhancing products and services, driving organizational growth.
Conducting cost-benefit analyses helps identify effective, long-term solutions
to business challenges.
Integrity and Empathy- Building trust and rapport fosters a compassionate
workplace while maintaining integrity and personal values. Empathy involves
understanding and appreciating others' perspectives, promoting positive
interactions and collaboration.
Emotional Intelligence- Emotional intelligence involves understanding,
managing, and utilizing emotions effectively. It encompasses skills like
self-awareness, empathy, influence, and collaboration. During crises or
conflicts, emotional intelligence fosters psychological safety, prevents
groupthink, and enhances organizational performance.
On a scale from "Not Aligned" to "Perfectly Aligned", how closely do you
think the following Collaborative soft skills match the soft skills you consider
important to your workforce? Short Descriptions: Communication- Business
communication skills include clear information sharing, active listening for
negotiations, and effective networking. Successful team collaboration requires
concise feedback to encourage creativity, while constructive feedback supports
ARE OUR GRADUATES PREPARED?
53
reflection and continuous improvement. Team Work- This involves
coordinating, cooperating, and collaborating to build trust and support among
team members while aligning actions with the team's mission. Effective
conflict management is key to resolving disputes and maintaining team
cohesion. Global and Cultural Diversity- This focuses on fostering an
inclusive environment that encourages creativity and a strong sense of
belonging. Leadership Skills- This highlights key leadership traits such as
self-confidence, enthusiasm, assertiveness, authenticity, trustworthiness,
humility, and humor. Effective leaders align their actions with their intentions,
demonstrating authenticity and fostering trust. Business Etiquette- Business
etiquette involves respecting workplace norms and differences. Actions like
remembering names, offering handshakes, and maintaining positive gestures,
such as nodding or smiling, demonstrate respect and active listening.
Awareness of cultural norms and effective communication practices helps
prevent miscommunication and fosters strong professional relationships. On a
scale from "Not Aligned" to "Perfectly Aligned", how closely do you think the
following Procedural soft skills match the soft skills you consider important to
your workforce? Short Descriptions: Quantitative Skills- These skills involve
reasoning and understanding numerical data to solve problems and make
decisions. Flexibility for Organizational Changes- These skills involve the
ability to adapt to dynamic tasks and changing circumstances, reflecting high
performance potential. Consistently completing defined activities ensures
reliability and fosters trust in outcomes. Critical Thinking- This is the ability
to research and create a critical analysis of information and relate a systemic
approach to problem solving. Ability to Make Decisive Decisions- This relates
to considering alternative solutions that will support the cognitive process of a
belief, or course of action based on several alternative options. Responsibility
for Getting the Job Done- This relates to applying work habits such as
maintaining wellness, time management, follow through, and initiative creates
the ability to contemplate information and skill development.
On a scale from "Not Aligned" to "Perfectly Aligned", how closely do you
think the following Procedural soft skills match the soft skills you consider
important to your workforce? Short Descriptions: Quantitative Skills- These
skills involve reasoning and understanding numerical data to solve problems
and make decisions. Flexibility for Organizational Changes- These skills
involve the ability to adapt to dynamic tasks and changing circumstances,
reflecting high performance potential. Consistently completing defined
activities ensures reliability and fosters trust in outcomes. Critical ThinkingThis is the ability to research and create a critical analysis of information and
relate a systemic approach to problem solving. Ability to Make Decisive
Decisions- This relates to considering alternative solutions that will support
the cognitive process of a belief, or course of action based on several
alternative options. Responsibility for Getting the Job Done- This relates to
applying work habits such as maintaining wellness, time management, follow
through, and initiative creates the ability to contemplate information and skill
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54
development.
On a scale from "No Gap" to "Significant Gap", to what degree do you believe
there is a gap between the Individual, Collaborative, and Procedural Soft
skills, identified above, and those needed for your workforce?
Data Type:
Qualitative
From your perspective, how do the Individual soft skills listed above compare
to the soft skills needed to sustain your workforce? Please provide specific
examples or experiences that highlight any similarities or differences.
From your perspective, how do the Collaborative soft skills listed above
compare to the soft skills needed to sustain your workforce? Please provide
specific examples or experiences that highlight any similarities or differences.
From your perspective, how do the Procedural soft skills listed above compare
to the soft skills needed to sustain your workforce? Please provide specific
examples or experiences that highlight any similarities or differences.
Research Question: To what extent do current job openings and projected job openings in
Greene County compare to statistics from the US Bureau of Labor and Statistics?
Data Type:
Quantitative
Survey Questions:
Which option best describes your industry? Goods- Producing Excluding
Agriculture- Mining, Goods- Producing Excluding Agriculture- Construction,
Goods- Producing Excluding Agriculture- Manufacturing, Service- Producing
Excluding Special Industries- Utilities, Service- Producing Excluding Special
Industries- Wholesale Trade, Service- Producing Excluding Special IndustriesRetail Trade, Service- Producing Excluding Special Industries- Transportation
and Warehousing, Service- Producing Excluding Special IndustriesInformation, Service- Producing Excluding Special Industries- Financial
Activities, Service- Producing Excluding Special Industries- Professional and
Business Services, Service- Producing Excluding Special IndustriesEducational Services, Service- Producing Excluding Special Industries- Health
Care and Social Assistance, Service- Producing Excluding Special IndustriesLeisure and Hospitality, Service- Producing Excluding Special IndustriesOther Services, Federal Government, State and Local Government.
How many employees does your company employ?
How many job openings do you anticipate hiring for within the next calendar
year?
How many job openings do you project hiring for five years from now?
Data Type:
Qualitative
Survey Questions:
What factors do you think will influence your projected hiring needs?
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Research Question: To what extent do the top Greene County business employers in the public
and private sectors value the soft skills that are being taught by the West Greene School
District for entry level positions?
Data Type:
Quantitative
Survey Questions:
Please rank the following "Individual Soft Skills" in order of most important
(1) to least important (4), on the list, in hiring a potential candidate in your
industry. Short Descriptions: Work Under Pressure- Time management
involves effectively planning and organizing priorities to optimize productivity
and minimize stress. It enhances performance under pressure and supports
lifelong learning through continuous self-assessment and improvement.
Innovative Problem-Solving- Innovative ideas and job-related activities are
vital for enhancing products and services, driving organizational growth.
Conducting cost-benefit analyses helps identify effective, long-term solutions
to business challenges. Integrity and Empathy- Building trust and rapport
fosters a compassionate workplace while maintaining integrity and personal
values. Empathy involves understanding and appreciating others' perspectives,
promoting positive interactions and collaboration. Emotional IntelligenceEmotional intelligence involves understanding, managing, and utilizing
emotions effectively. It encompasses skills like self-awareness, empathy,
influence, and collaboration. During crises or conflicts, emotional intelligence
fosters psychological safety, prevents groupthink, and enhances organizational
performance.
Please rank the following "Collaborative Soft Skills" in order of most
important (1) to least important (5), on the list, in hiring a potential candidate
in your industry. Short Descriptions: Communication- Business
communication skills include clear information sharing, active listening for
negotiations, and effective networking. Successful team collaboration requires
concise feedback to encourage creativity, while constructive feedback supports
reflection and continuous improvement. Team Work- This involves
coordinating, cooperating, and collaborating to build trust and support among
team members while aligning actions with the team's mission. Effective
conflict management is key to resolving disputes and maintaining team
cohesion. Global and Cultural Diversity- This focuses on fostering an
inclusive environment that encourages creativity and a strong sense of
belonging. Leadership Skills- This highlights key leadership traits such as
self-confidence, enthusiasm, assertiveness, authenticity, trustworthiness,
humility, and humor. Effective leaders align their actions with their intentions,
demonstrating authenticity and fostering trust. Business Etiquette- Business
etiquette involves respecting workplace norms and differences. Actions like
remembering names, offering handshakes, and maintaining positive gestures,
such as nodding or smiling, demonstrate respect and active listening.
Awareness of cultural norms and effective communication practices helps
prevent miscommunication and fosters strong professional relationships.
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Please rank the following "Procedural Soft Skills" in order of most important
(1) to least important (5), on the list, in hiring a potential candidate in your
industry. Short Descriptions: Quantitative Skills- These skills involve
reasoning and understanding numerical data to solve problems and make
decisions. Flexibility for Organizational Changes- These skills involve the
ability to adapt to dynamic tasks and changing circumstances, reflecting high
performance potential. Consistently completing defined activities ensures
reliability and fosters trust in outcomes. Critical Thinking- This is the ability
to research and create a critical analysis of information and relate a systemic
approach to problem solving. Ability to Make Decisive Decisions- This relates
to considering alternative solutions that will support the cognitive process of a
belief, or course of action based on several alternative options. Responsibility
for Getting the Job Done- This relates to applying work habits such as
maintaining wellness, time management, follow through, and initiative creates
the ability to contemplate information and skill development.
Please rank the following groupings of soft skills in order of most important
(1) to least important (3), on the list, in hiring a potential candidate in your
industry: Individual, Collaborative, and Procedural
Data Type:
Qualitative
Survey Questions:
In your experience, how does your workplace value the Individual soft skills
listed above for entry level and professional positions. Please provide
examples or anecdotes to illustrate your perspective.
In your experience, how does your workplace value the Collaborative soft
skills listed above for entry level and professional positions. Please provide
examples or anecdotes to illustrate your perspective.
In your experience, how does your workplace value the Procedural soft skills
listed above for entry level and professional positions. Please provide
examples or anecdotes to illustrate your perspective.
In your experience, how does your workplace value the three categories of soft
skills, as a whole, listed above for entry level and professional positions.
Please provide examples or anecdotes to illustrate your perspective.
The research method that was used in this research study was a mixed methods approach
with concurrent embedded design. According to Almeida (2018), an advantage of this type of
design is that it is very suitable when there is a predominant type of data being collected and
analyzed (p. 146). However, it must be noted that a disadvantage to this type of data collection
was that there could have been difficulties reconciling conflicting and antagonistic results
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(Almeida, 2018, p. 146). The predominant data type that was collected for this study was
quantitative data where respondents selected from a predetermined list of NAICS codes to
inform the researcher on the economic sector of respondents, the number of employees the
responder employed, the number of anticipated job openings the respondent expects within the
next calendar year and five years from now, and ranking the three sets of soft skills. In addition,
respondents had the ability to add soft skills that were not included in the survey that they saw as
valuable to their employment criteria. Furthermore, there were embedded qualitative questions to
determine current and employer projected positions that could be available to our students with
these skills/competencies compared to national and state level statistics. This type of research
design is being employed because of the time constraints associated with action research. This
mixed methods approach allowed both types of data to be collected simultaneously to gain a
comprehensive view of the job market and the school’s role in graduating students for the job
market.
When looking at the fiscal implications of the research, there were minimal fiscal
implications in the research methods or in data collection. Outside of administrative costs
associated with completing the work like the researcher’s time or the cost of the applications
used to aggregate data and to word process any documentation, the costs were incredibly limited.
Any and all fiscal implications of this research was based on the outcomes of the research and
data collection. These implications would have a significant impact on the budgeting priorities of
the district, resource allocation, and potential partnerships. The outcome of these research
questions would lead to a curriculum redesign in terms of revised curriculum materials,
purchasing new resources, or providing professional development for teachers to emphasize the
soft skills that local employers prioritize, in an effort to address misalignment. Potential
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outcomes could lead to program expansions and program contractions that could require
additional funding. On the other hand, there could be opportunities for cost saving measures as a
result of the potential research outcomes. Once alignment exists between our curriculum and
local employers, the district could leverage partnerships that involve co-funded programs,
student internships, mentorship opportunities; opportunities that could reduce the school’s
financial burden. These outcomes could result from the data collection and research design and
did not fiscally impact the study before it was conducted.
Validity
One aspect of a valid study is credibility. According to Hendricks (2017), having credible
data means having a dataset that is complete and accurate (p. 64). In creating credibility in this
study, the researcher focused on the accuracy of the findings in order to come to correct
interpretations with the correct conclusions. One strategy that was employed to maintain
accuracy and come to proper conclusions during data collection was triangulating survey
questions by using a mixed methods embedded design to gather data. Also, the researcher
worked to survey at least ten of the top employers in Greene County to ensure triangulation.
Another aspect of a valid study as it pertains to data collection is transferability, or the
extent to which the results of a study are applicable to other contexts and other individuals
(Hendricks, 2017, p. 64). In order to achieve transferability, the researcher has shown the
usefulness of the results in different settings and contexts. Some strategies that were employed to
help ensure transferability were describing in detail the setting, participants, intervention, and
research methods employed in the study (Hendricks, 2017, p.65). This will allow other
researchers to find commonality between this action research and their own.
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After the researcher had achieved credibility and transferability, the researcher needed to
achieve dependability, or the degree to which research results would replicate with the same or
similar participants and/or contexts (Hendricks, 2015, p. 64). The goal for any research study is
replicability to other participants, and in order to achieve this the researcher has provided a great
deal of detail to set the scene of the research. Make no mistake, Greene County, Pennsylvania, is
a very rural area of Appalachia, therefore, any results will most likely be dependable to other
school districts or to people in other contexts with similar demographics. Therefore, these
demographics needed to be explained in greater detail.
Lastly, a good research study has confirmability, or the showing of results that are an
accurate representation of what occurred, rather than a result of researcher bias (Hendricks, 2015,
p. 64). In order to achieve this, the research has provided evidence that biases have been taken
into account. In order to do this, the researcher has cleared any biases. This means that the
researcher has reflected and self-reported in the study any biases, including inherent biases that
might have existed in order to be fully transparent with the reader (Hendricks, 2017, p. 66). Since
the researcher engaged in triangulation and made biases clear, as well as engaged in a credible,
dependable, and transferable study, the research was and is valid.
Summary
In conclusion, this study offered a meaningful and localized approach to addressing the
pressing economic and educational challenges facing Greene County, Pennsylvania, and
specifically the West Greene School District. Rooted in the realities of a rural community
experiencing economic stagnation, workforce decline, and increasing poverty, the research
affirmed the critical role schools must play in regional revitalization (U.S. Census Bureau, 2023).
The West Greene School District, uniquely positioned as both an educational institution and a
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community anchor, has a responsibility to ensure that its graduates are equipped with the soft
skills essential for success in the contemporary job market.
The study's use of a mixed methods, concurrent embedded design allowed for the
collection of mostly quantitative and important qualitative data from a targeted group of Greene
County’s leading employers (Almeida, 2018, p. 146). This design proved instrumental in
capturing the nuances of employer needs while also producing measurable results that can
inform future decision-making. Quantitative survey responses offered insight into workforce
trends and soft skill priorities, while qualitative feedback enriched the data with contextual
understanding. Through this comprehensive approach, the research succeeded in highlighting
both current gaps and future opportunities in aligning educational outcomes with workforce
expectations.
Beyond academic implications, this research holds significant practical and fiscal
relevance. In the researcher’s estimation, the integration of employer-valued soft skills into the
district curriculum has the potential to reduce graduate outmigration, bolster local employment,
and create sustainable partnerships with area businesses. While implementation will require
resource investment and professional development, the long-term benefits include improved
student preparedness, greater employer satisfaction, and the strengthening of Greene County's
local economy.
To conclude, this research affirmed the necessity of aligning school programming with
local economic demands and provided a clear path forward for doing so. The West Greene
School District, through the development of a soft skills curriculum based on employer input,
can better prepare its graduates for meaningful, gainful employment while contributing to the
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revitalization of its community. This study marked an important step toward that goal, laying the
groundwork for future action that is both informed and impactful.
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Chapter IV
Data Analysis & Results
The primary focus of this action research study is to determine the soft skills that the
largest employers in Greene County, Pennsylvania, see as the most important to their businesses,
to determine to what degree the West Greene School District is already meeting the demand for
needed skills, and to determine the number of jobs that may be available by these employers for
entry level prospective candidates with these specific soft skills. The data analysis and results
were guided by the following research questions:
1. To what extent do the top Greene County business employers in the public and
private sectors value the soft skills that are being taught by the West Greene
School District for entry level positions?
2. To what extent do current job openings and projected job openings in Greene
County compare to statistics from the US Bureau of Labor and Statistics?
3. How do graduates with the desired soft skills, as determined by the West Greene
School District administration, compare to the soft skills identified by local
business leaders to sustain the workforce of Greene County, Pennsylvania?
The goal of this capstone project is to determine where the soft skills curriculum in the
West Greene Junior/Senior High School is in relation to the desired soft skills of our local
employers in an effort to create the best soft skills curriculum in order to mold graduates who are
prepared and needed for the local workforce. The research was designed to incorporate multiple
data sources and types to ensure strong results through triangulation using a mixed methods
approach with a concurrent embedded design. Qualitative and quantitative data were collected
through multiple measures through the use of a survey. As listed in Table 9, each research
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question had multiple qualitative and quantitative questions associated with it to ensure
triangulation and valid results. Specifically, the first research question had five quantitative
questions and three qualitative questions, the second research question had four quantitative
questions and one qualitative question, and the third research question had four quantitative
questions and four qualitative questions. Each survey question was aligned with an associated
research question for the purpose of triangulated results for better overall analysis and
understanding.
Data Analysis
Data analysis in this action research study took many twists and turns based on the results
from each of the survey questions. The survey was conducted through Google Forms. The
quantitative data from the Google Form was transferred into a Google Sheet that would be coded
for SPSS. SPSS was used to analyze the raw data into comprehensible information. In addition to
SPSS, NVivo was used to analyze qualitative data. Once themes were established, either
inductively or deductively, responses were analyzed through NVivo by coding themes and then
separating responses into those themes. Quantitative data set the foundation of the survey and
study; whereas, qualitative data was used to fill in any gaps that could not be predicted by the
researcher.
The first questions on the survey that were analyzed were aligned with my second
research question: To what extent do current job openings and projected job openings in Greene
County compare to statistics from the US Bureau of Labor and Statistics? SPSS was not used to
aggregate this data as the data was simple, but NVivo 15 software was used to analyze the
qualitative responses through thematic analysis to identify trends amongst the themes
(Lumivero, 2024).
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The next questions in the survey were aligned with research question one: To what extent
do the top Greene County business employers in the public and private sectors value the soft
skills that are being taught by the West Greene School District for entry level positions? SPSS
was used to find the mean and standard deviation of how each employer ranked soft skills within
each of the three categories: Individual, Collaborative, and Procedural. SPSS was only used on
the questions finding quantitative results. When looking at the mean for each question, finding a
mean closer to one meant that the employer ranked the soft skill higher, and having a lower
standard deviation meant that there was more consensus of the ranking among respondents (IBM
Corp., 2021). Once these measures were found, the researcher ran a Friedman Test through SPSS
to ensure that the differences in ranks occurred as a matter of fact and not by accident (IBM
Corp., 2021). If the Friedman Test resulted in a p-value of .05 or lower, it was clear that there
were strong correlations between the data. In order to find these correlations, a Wilcoxon Signed
Rank Test was run through SPSS (IBM Corp., 2021). If a p-value of less than .05 was shown
between two variables, then there were significant correlations. These tests were run on the
quantitative survey questions intended to rank soft skills. On the other hand, the qualitative
questions were thematically analyzed and then coded to find trends through NVivo 15 software
(Lumivero, 2024).
The next set of survey questions were aligned with the third research question: How do
graduates with the desired soft skills, as determined by the West Greene School District
administration, compare to the soft skills identified by local business leaders to sustain the
workforce of Greene County, Pennsylvania? SPSS was used on the quantitative questions
aligned with this research question to first find mean, standard deviation, and skewness because
these are Likert scale questions (IBM Corp., 2021). Again, a lower standard deviation meant
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more consensus in the respondents’ responses on the Likert scale. A mean closer to five meant
that the soft skill was highly aligned with the needs of their industry. Skewness was determined
to find the degree in which answers were skewed one way or the other, and a skewness closer to
zero meant that responses were less skewed. In addition, valid percentages were found to
determine the rate in which respondents responded at each level of the Likert scale. On the other
hand, qualitative data went through a thematic analysis, either inductively or deductively, and
then the responses were coded into those themes to find trends using NVivo 15 software
(Lumivero, 2024).
Results
As noted above, the data from each survey question, aligned to each research question
went through extensive data analysis. This goal of this analysis is to answer the following
research questions: To what extent do the top Greene County business employers in the public
and private sectors value the soft skills that are being taught by the West Greene School District
for entry level positions?; To what extent do current job openings and projected job openings in
Greene County compare to statistics from the US Bureau of Labor and Statistics?; and How do
graduates with the desired soft skills, as determined by the West Greene School District
administration, compare to the soft skills identified by local business leaders to sustain the
workforce of Greene County, Pennsylvania?
Quantitative Industry Demographics
The survey must first be deconstructed to the types of questions asked of the survey
participants. The first five survey questions were meant to gain data on the respondents with the
goal of comparing that data to state or national level data in correlation with the second research
question: To what extent do current job openings and projected job openings in Greene County
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compare to statistics from the US Bureau of Labor and Statistics? The first four questions
relating to the second research question were quantitative questions. The goal of the first
question was to gain information on the type of industry the respondents are in to help the
researcher understand the industries being represented. The survey was distributed to the 50
largest employers in Greene County (Appendix A). Out of the 50 potential respondents, 10
surveys were collected for a 20% participation rate. The goal of the study was to survey the top
10 businesses, but to expect a 100% participation rate was not likely. So the study was expanded
to the top 50 largest employers with a goal of at least 10 respondents. The researcher achieved
that goal. Table 10 refers to the NAICS descriptors of the respondents.
Table 10
NAICS Descriptors of Respondents
NAICS Descriptor
Percent of Respondents
Service- Producing Excluding
Special IndustriesEducational Services
(Includes Public and Private
Schools)
70%
Goods- Producing Excluding
Agriculture- Construction
20%
Service- Producing Excluding
Special Industries- Health
Care and Social Assistance
10%
The next quantitative question was meant to find out how large the company is by
requesting the total number of employees employed with the company. Table 11 illustrates a
breakdown of the number of employees the respondents have.
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Table 11
Number of Employees
Range
Percent of Respondents
1-49 employees
10%
50-99 employees
30%
100-199 employees
40%
200-299 employees
10%
300 or more employees
10%
The next quantitative question was meant to find how many job openings would be
available and filled within each company in the next year, and the last quantitative question
aligned with this research question was meant to determine how many openings the employer
plans on filling five years from now. Table 12 refers to the number of job openings each
respondent plans to fill this year compared to the number of positions that respondents plan to fill
in five years.
Table 12
Comparison of Job Openings to be Filled Within a Year Compared to Within Five Years
Range
Openings to be filled within the
year
Projected openings to be filled in
five years
Respondent 1
3-5
0
Respondent 2
5
15
Respondent 3
2-5
5
Respondent 4
3-5
12-15
Respondent 5
1-5
10-15
Respondent 6
0
1-5
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Respondent 7
10-15
0
Respondent 8
5-10
20
Respondent 9
1-2
4-6
Respondent 10
5-10
25
Qualitative Industry Demographics
The next survey question was an embedded qualitative question: What factors do you
think will influence your projected hiring needs? Through a thematic analysis, some very
pronounced themes arose in the manual coding of the qualitative data. These themes are as
follows: Retirements and turnover, program/company expansion or reduction, and industry
specific external factors. These themes were inductively developed, meaning that the researcher
analyzed responses and created a list of broad topics/ themes that were pronounced in responses
(Braun & Clarke, 2006, p. 12).
Once the themes were established, the qualitative data were analyzed using Nvivo 15
software (Lumivero, 2024). Using the software, the researcher found that industry specific
external factors were overwhelmingly the major theme of the returned data for this research
question. Included in these industry specific external factors is people changing positions or
school districts; school enrollment trends; the company’s increased involvement in oil/gas,
landfills, civil work, and trucking needs; school program expansions/contractions; insurance
reimbursements, aging population, and the expansion of larger healthcare organizations growing
in the area. The last two themes, retirements and turnover and program/company expansion or
reduction were still redundant themes but not as pronounced as industry specific external factors.
The factors associated with the theme industry specific external factors were shown to be the
greatest factors influencing projected hiring needs by a one to five ratio of the other themes.
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Quantitative Ranking of Individual Soft Skills
The next survey questions are aligned with the first research question: To what extent do
the top Greene County business employers in the public and private sectors value the soft skills
that are being taught by the West Greene School District for entry level positions? These
questions are intended to determine which of the soft skills valued by the West Greene School
District are most valued by the largest employers in Greene County. Respondents were asked to
rank different soft skills under each category of soft skills: Individual, Collaborative, and
Procedural. For Individual Soft Skills, respondents were asked to rank: Work under pressure,
innovative problem-solving, integrity and empathy, and emotional intelligence. Table 13
illustrates the mean and standard deviation of the responses. This data was run through the data
analysis tool SPSS (IBM Corp., 2021). Responses that have a mean closer to one were deemed
more important by respondents and the lower the standard deviation, the more consensus there
was about the particular rating of a soft skill.
Table 13
Mean and Standard Deviation of Ranking Individual Soft Skills
Individual Soft Skills
Mean
Standard Deviation
Work Under Pressure
2.5
1.269
Innovative ProblemSolving
2
.943
Integrity and
Empathy
2.2
1.135
Emotional
Intelligence
3.3
.823
When looking at this data it is important to delineate if these differences in ranking are
real or if the differences occurred by a random occurrence. In order to make this delineation the
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researcher used SPSS to run a Friedman Test to determine if the data was reliable and not
random. Table 14 provides the outcome of the Friedman Test. The p-value of .188 indicates that
there is no clear correlation in the differences and they could be a result of random occurrence.
Table 14
Friedman Test of Individual Soft Skills
Friedman Test
Chi- Square
df
Statistics
5.880
3
p-value
.118
Qualitative Aggregation of Individual Soft Skills
The next survey question was an embedded qualitative question that aimed to fill any
gaps that the researcher could have missed in their aggregation of Individual Soft Skills. Through
a thematic analysis, some very pronounced themes arose in the manual coding of the qualitative
data. These themes include “variances in desired soft skills between professional roles and entry
level roles” and “variances in desired soft skills between education sector positions and business
sector positions”. These themes were deductively developed, meaning that the researcher
analyzed responses that were aligned with a pre-existing framework of soft skills (Braun &
Clarke, 2006, p. 12).
Once the themes were established, the qualitative data were analyzed using Nvivo 15
software (Lumivero, 2024). The most prominent theme was the differences in desired soft skills
between entry level positions and professional level positions. In professional roles there is
increased emphasis on leadership, problem-solving, initiative, and independent decision-making;
whereas, for entry level positions the soft skills focus is on communication, teamwork,
adaptability, and time management. The next, less prominent theme is that there are differences
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between the needs of the business sector and the education sector in terms of soft skills.
Respondents from the education sector valued emotional intelligence and empathy much more
than the other sectors; whereas, service industry and business sector respondents value stress
management, reliability, and initiative. These stark contrasts represent a major theme of the data.
Quantitative Ranking of Collaborative Soft Skills
The next category of soft skills that was ranked by respondents was Collaborative Soft
Skills. For Collaborative Soft Skills, respondents were asked to rank the following soft skills:
Communication, teamwork, global and cultural diversity, leadership skills, and business
etiquette. Table 15 illustrates the mean and standard deviation of the responses. This data was
run through the data analysis tool SPSS. Responses that have a mean closer to one were deemed
more important by respondents and the lower the standard deviation, the more consensus there
was about the particular ranking of a soft skill.
Table 15
Mean and Standard Deviation of Ranking Collaborative Soft Skills
Collaborative Soft
Skills
Mean
Standard Deviation
Communication
1.1
.316
Teamwork
2.3
.823
Global and Cultural
Diversity
4.6
.516
Leadership Skills
3.4
.966
Business Etiquette
3.6
1.075
Likewise with Individual Soft Skills, when looking at this data it is important to delineate
if these differences in ranking are real or if the differences occurred by a random occurrence. In
order to make this delineation the researcher used SPSS to run a Friedman Test to determine if
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the data was reliable and not random. Table 16 provides the outcome of the Friedman Test. The
p-value of <.001 indicates that there is a strong correlation in the differences and are not a result
of potential random occurrences.
Table 16
Friedman Test of Collaborative Soft Skills
Friedman Test
Statistics
Chi Square
28.720
df
4
p-value
<.001
It was important for the researcher to dig deeper into the strong correlation p-value from
the ranking of Collaborative Soft Skills. With such a high correlation it is important to find
where that correlation exists within the data. In order to find these correlations, a Wilcoxon
Signed Rank Test was used in SPSS. In order to run this test, the researcher had to compare the
values of each of the soft skills to one another. The results of the Wilcoxon Signed Rank Tests
are illustrated in Table 17. With p-values under .05, the researcher can ascertain that these
differences are not by chance.
Table 17
Wilcoxon Signed Rank Tests
Comparisons
Z
2 Tailed p-value
Teamwork vs.
Communication
-2.489
.013
Global and Cultural
Diversity vs.
Communication
-2.877
.004
Leadership Skills vs.
Communication
-2.871
.004
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Business Etiquette vs.
Communication
-2.831
.005
Global and Cultural
Diversity vs.
Teamwork
-2.859
.004
Leadership Skills vs.
Teamwork
-1.998
.046
Business Etiquette vs.
Teamwork
-2.021
.043
Leadership Skills vs.
Global and Cultural
Diversity
2.235
.025
Business Etiquette vs.
Global and Cultural
Diversity
1.999
.046
Business Etiquette vs.
Leadership Skills
-.263
.793
Qualitative Aggregation of Collaborative Soft Skills
The next embedded qualitative question was aimed to fill any gaps that the researcher
could have missed in their aggregation of Collaborative Soft Skills. Through a thematic analysis,
themes such as communication and teamwork with mentorship and trust-building as a key
subtheme and leadership are pronounced themes. These themes were deductively developed,
meaning that the researcher analyzed responses that were aligned with a pre-existing framework
of soft skills and these themes were most pronounced (Braun & Clarke, 2006, p. 12).
Once the themes were established, the qualitative data were analyzed using Nvivo 15
software (Lumivero, 2024). From the data analysis, it is clear that communication is valued most
by each industry because of its interplay with building effective teams that lead to enhanced
mentorship opportunities. Leadership was also an important theme amongst respondents because
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leadership is an expectation of the most and least tenured employees in an organization. These
themes were most prominent in the analysis of this qualitative dataset.
Quantitative Ranking of Procedural Soft Skills
The next category of soft skills that was ranked by respondents was Procedural Soft
Skills. For Procedural Soft Skills, respondents were asked to rank the following soft skills:
Quantitative skills, flexibility for organizational change, critical thinking, ability to make
decisive decisions, and responsibility to get the job done. Table 18 illustrates the mean and
standard deviation of the responses. This data was run through the data analysis tool SPSS.
Responses that have a mean closer to one were deemed more important by respondents and the
lower the standard deviation, the more consensus there was about the particular ranking of a soft
skill.
Table 18
Mean and Standard Deviation of Ranking Procedural Soft Skills
Procedural Soft Skills
Mean
Standard Deviation
Quantitative Skills
4.3
1.494
Flexibility for
Organizational
Change
3.2
.919
Critical Thinking
2.4
1.350
Ability to Make
Decisive Decisions
2.9
.876
Responsibility to Get
the Job Done
1.89
1.269
Just as with Individual and Collaborative Soft Skills, when looking at this data it is
important to delineate if these differences in ranking are real or if the differences occurred by a
random occurrence. In order to make this delineation the researcher used SPSS to run a Friedman
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Test to determine if the data was reliable and not random. Table 19 provides the outcome of the
Friedman Test. The p-value of <.002 indicates that there is a strong correlation in the differences
and are not a result of potential random occurrences.
Table 19
Friedman Test of Procedural Soft Skills
Friedman Test
Statistics
Chi Square
16.622
df
4
p-value
.002
The result of the Friedman Test produced a very low p-value, indicating a strong
correlation. Therefore, It was again important for the researcher to dig deeper into the strong
correlation p-value from the ranking of Procedural Soft Skills. The results of the Wilcoxon
Signed Rank Test, made through SPSS, are illustrated in Table 20. With p-values under .05, the
researcher can ascertain that these differences are not by chance; however, there are a few
comparisons that do not guarantee a correlation.
Table 20
Wilcoxon Signed Rank Tests
Comparisons
Z
2 Tailed P-Score
Quantitative Skills vs.
Flexibility for
Organizational
Change
-1.658
.097
Quantitative Skills vs.
Critical Thinking
-2.265
.024
Quantitative Skills vs.
Ability to Make
Decisive Decisions
-1.813
.070
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Quantitative Skills vs.
Responsibility to Get
the Job Done
-2.534
.011
Flexibility for
Organizational
Change vs. Critical
Thinking
-1.412
.158
Flexibility for
Organizational
Change vs. Ability to
Make Decisive
Decisions
-.690
.490
Flexibility for
Organizational
Change vs.
Responsibility to Get
the Job Done
-2.228
.026
Critical Thinking vs.
Ability to Make
Decisive Decisions
.777
.437
Critical Thinking vs.
Responsibility to Get
the Job Done
-.889
.374
Ability to Make
Decisive Decisions
vs. Responsibility to
Get the Job Done
-2.145
.032
Qualitative Aggregation of Procedural Soft Skills
The next embedded qualitative survey question aimed to fill any gaps that the researcher
could have missed in their aggregation of Procedural Soft Skills. Through a thematic analysis,
the theme “Procedural Soft Skills are non-negotiable for successful work performance” and
subtheme “necessary Procedural Soft Skills vary across industries”. These themes were
deductively developed, meaning that the researcher analyzed responses that were aligned with a
pre-existing framework of soft skills (Braun & Clarke, 2006, p. 12).
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Once the themes were established, the qualitative data were analyzed using Nvivo 15
software (Lumivero, 2024). Once the data was analyzed it was clear that the major consensus
was that Procedural Soft Skills are non-negotiable to a successful workforce; however, the
specific sets of skills varied by industry. In education, time management and problem-solving
were emphasized; in healthcare informed decision-making, consistency, and professional
standards were emphasized; and in construction safety, flexibility, and independent
problem-solving was emphasized. This theme and subtheme was very pronounced in the
responses.
Quantitative Ranking of Soft Skills Categories: Individual, Collaborative, and Procedural
After respondents ranked each soft skill in each category, the researcher also wanted to
know how these employers would rank each of the categories in order to determine the main
categorical focus of the soft skills program. Table 21 illustrates how respondents ranked each of
the categories of soft skills. This data was run through the data analysis tool SPSS. Responses
that have a mean closer to one were deemed more important by respondents and the lower the
standard deviation, the more consensus there was about the particular ranking of a category.
Table 21
Mean and Standard Deviation of Ranking Soft Skills Categories
Category
Mean
Standard Deviation
Individual
1.6
.699
2
.943
2.40
.699
Collaborative
Procedural
The Friedman Test was performed to delineate if these differences in ranking are real or if
the differences occurred by a random occurrence. In order to make this delineation the researcher
used SPSS to run a Friedman Test to determine if the data was reliable and not random. Table 22
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provides the outcome of the Friedman Test. The p-value of .202 indicates that there is not a
strong correlation in the differences and could be a result of potential random occurrences.
Table 22
Friedman Test of Ranking Soft Skills Categories
Friedman Test
Chi Square
df
Statistics
3.2
2
p-value
.202
Qualitative Aggregation Soft Skills Categories: Individual, Collaborative, and Procedural
The last embedded qualitative survey question for the ranking questions is aimed to fill
any anecdotal gaps that could not have been ascertained through quantitative data about ranking
the three soft skills categories in terms of value to entry and professional level positions.
Through a thematic analysis, a very pronounced theme arose in the manual coding of the
qualitative analysis. This theme indicated that all of these soft skill categories are very valuable
to each industry; however, each comes with its specific drawbacks. These themes were
deductively developed, meaning that the researcher analyzed responses that were aligned with a
pre-existing framework of soft skills (Braun & Clarke, 2006, p. 12). This topic was the most
pronounced.
Once the themes were established, the qualitative data were analyzed using Nvivo 15
software and subthemes became apparent (Lumivero, 2024). Collaborative Skills are critical for
teamwork, but are the hardest to teach in the professional setting. Procedural skills ensure
organizational efficiency and can be developed with practice over time. Lastly, Individual Skills
are foundational skills that enhance the other categories. These subthemes enhance the larger
theme that each skillset is important, but have skill-specific drawbacks.
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Quantitative Alignment of Individual Soft Skills
Whereas the previous questions of the survey were ranking questions aligned with the
first research question, the next set of survey questions were aligned with the third research
question: How do graduates with the desired soft skills, as determined by the West Greene
School District administration, compared to the soft skills identified by local business leaders to
sustain the workforce of Greene County, Pennsylvania? For these questions, respondents were
asked to identify the alignment between the soft skills identified by the West Greene School
District and the soft skills needed in the respondents’ industry. Respondents answered on a Likert
scale with the following descriptors: Not aligned, somewhat not aligned, indifferent to the soft
skill in our industry, somewhat aligned, and perfectly aligned. The scale used in the survey
demonstrated high reliability, with Cronbach's Alpha (α) equaling .919. This score was
determined by a test using SPSS. The first Likert scale question asked respondents to scale the
Individual Soft Skills: “Work Under Pressure,” “Innovative Problem-Solving,” “Integrity and
Empathy,” and “Emotional Intelligence,” using the aforementioned scale. Table 23 illustrates the
mean, standard deviation, and skewness of the responses. This data was run through the data
analysis tool SPSS. Responses that have a mean closer to five were deemed more aligned to the
needs of the industry, the lower the standard deviation the more consensus there was about the
particular scale of a soft skill, and the closer the skewness number is to zero the less skewed the
results are one way or another.
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Table 23
Mean and Standard Deviation of Likert Scale Individual Soft Skills
Individual Soft
Skills
Mean
Standard Deviation
Skewness
Work Under
Pressure
2.56
1.509
-.697
3
1.225
-2.100
Integrity and
Empathy
3.67
.500
-.857
Emotional
Intelligence
3.33
7.07
-.606
Innovative
ProblemSolving
In addition to mean, standard deviation, and skewness, it is also valuable to determine the
frequencies by which respondents chose each rating. Table 24 illustrates the Valid Percent
frequencies of each descriptor in the Likert scale.
Table 24
Valid Percents of Scale Descriptors
Scale
Individual
Soft Skills
Not
Aligned
Somewhat Not
Aligned
Indifferent to
the Soft Skill
in Our
Industry
Somewhat
Aligned
Perfectly
Aligned
Valid Percents
Work
Under
Pressure
11.1%
22.2%
0%
33.3%
33.3%
Innovative
Problem-
11.1%
0%
0%
55.6%
33.3%
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Solving
Integrity
and
Empathy
0%
0%
0%
33.3%
66.7%
Emotional
Intelligence
0%
0%
11.1%
44.4%
44.4%
Qualitative Alignment of Individual Soft Skills
The first embedded qualitative survey question for the alignment questions aimed to
ascertain the level of alignment of Individual Soft Skills to sustain the industries of the
respondents. Through a thematic analysis, a very pronounced theme arose in the manual coding
of the qualitative analysis. This theme was: High alignment of Individual Soft Skills but varied
between sectors. These themes were deductively developed, meaning that the researcher
analyzed responses that were aligned with a pre-existing framework of soft skills (Braun &
Clarke, 2006, p. 12).
Once the themes were established, the qualitative data were analyzed using Nvivo 15
software (Lumivero, 2024). Through this analysis, respondents cited that their industry needs
align with the Individual Soft Skill category because soft skills like communication, adaptability,
and emotional intelligence are essential skills in a candidate to sustain their workforces. This
theme analysis indicated a high alignment.
Quantitative Alignment of Collaborative Soft Skills
The next Likert scale question asked respondents to scale the Collaborative Soft Skills:
Communication, teamwork, global and cultural diversity, leadership skills, and business
etiquette. Table 25 illustrates the mean, standard deviation, and skewness of the responses. This
data was run through the data analysis tool SPSS. Responses that have a mean closer to five were
deemed more aligned to the needs of the industry, the lower the standard deviation the more
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consensus there was about the particular scale of a soft skill, and the closer the skewness number
is to zero the less skewed the results are one way or another.
Table 25
Mean and Standard Deviation of Likert Scale Collaborative Soft Skills
Collaborative
Soft Skills
Mean
Standard Deviation
Skewness
Communication
3.78
.441
-1.620
Teamwork
3.44
.527
.271
Global and
Cultural
Diversity
2.22
1.202
-.537
Leadership
Skills
3.33
.500
.857
Business
Etiquette
2.78
.833
-1.166
In addition to mean, standard deviation, and skewness, it is also valuable to determine the
frequencies by which respondents chose each rating. Table 26 illustrates the Valid Percent
frequencies of each descriptor in the Likert scale.
Table 26
Valid Percents of Scale Descriptors
Scale
Collaborative
Soft Skills
Not
Aligned
Somewhat
Not Aligned
Indifferent to
the Soft Skill
in Our
Industry
Somewhat
Aligned
Perfectly
Aligned
Valid Percents
Communication
0%
0%
0%
22.2%
77.8%
Teamwork
0%
0%
0%
55.6%
44.4%
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Global and
Cultural
Diversity
11.1%
11.1%
33.3%
33.3%
11.1%
Leadership
Skills
0%
0%
0%
66.7%
33.3%
Business
Etiquette
0%
11.1%
11.1%
66.7%
11.1%
Qualitative Alignment of Collaborative Soft Skills
The next embedded qualitative survey question for the alignment questions aimed to
ascertain the level of alignment of Collaborative Soft Skills to sustain the industry. Through a
thematic analysis and manual coding, some thematic soft skills that arose were teamwork and
communication. These themes were deductively developed, meaning that the researcher analyzed
responses that were aligned with a pre-existing framework of soft skills (Braun & Clarke, 2006,
p. 12).
Respondents noted that communication is a foundational soft skill; however, there is a
generational gap reinforcing the importance of non-digital communication, and that
communication is embedded in organizational culture. Next, teamwork is not just nice to have, it
is a requirement to sustain a functional workforce. A sub- theme that emerged is that leadership,
adaptability, and professionalism support the aforementioned theme.
Quantitative Alignment of Procedural Soft Skills
The next Likert scale question asked respondents to scale the Procedural Soft Skills:
Quantitative skills, flexibility for organizational change, critical thinking, ability to make
decisive decisions, and responsibility to get the job done. Table 27 illustrates the mean, standard
deviation, and skewness of the responses. This data was run through the data analysis tool SPSS.
Responses that have a mean closer to five were deemed more aligned to the needs of the
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industry, the lower the standard deviation the more consensus there was about the particular scale
of a soft skill, and the closer the skewness number is to zero the less skewed the results are one
way or another.
Table 27
Mean and Standard Deviation of Likert Scale Procedural Soft Skills
Procedural
Soft Skills
Mean
Standard Deviation
Skewness
Quantitative
Skills
2.22
1.394
-.146
Flexibility for
Organizational
Change
3.22
1.093
-1.289
Critical
Thinking
3.33
1.0000
-1.821
Ability to
Make Decisive
Decisions
3.22
.972
-1.600
Responsibility
to Get the Job
Done
3.33
1.0000
-1.821
In addition to mean, standard deviation, and skewness, it is also valuable to determine the
frequencies by which respondents chose each rating. Table 28 illustrates the Valid Percent
frequencies of each descriptor in the Likert scale.
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Table 28
Valid Percents of Scale Descriptors
Scale
Procedural Soft
Skills
Not
Aligned
Somewhat
Not Aligned
Indifferent to
the Soft Skill
in Our
Industry
Somewhat
Aligned
Perfectly
Aligned
Valid Percents
Quantitative
Skills
11.1%
22.2%
22.2%
22.2%
22.2%
Flexibility for
Organizational
Change
0%
11.1%
11.1%
22.2%
55.6%
Critical
Thinking
0%
11.1%
0%
33.3%
55.6%
Ability to Make
Decisive
Decisions
0%
11.1%
0%
44.4%
44.4%
Responsibility
to Get the Job
Done
0%
11.1%
0%
33.3%
55.6%
Qualitative Alignment of Procedural Soft Skills
The last embedded qualitative survey question for the alignment questions aimed to
ascertain the level of alignment of Procedural Soft Skills to sustain the industries of the
respondents. Through a thematic analysis and manual coding this theme emerged: Different
sectors value different alignments. These themes were deductively developed, meaning that the
researcher analyzed responses that were aligned with a pre-existing framework of soft skills
(Braun & Clarke, 2006, p. 12).
Once the themes were established, the qualitative data were analyzed using Nvivo 15
software (Lumivero, 2024). It became clear that respondents from the education sector stress
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autonomy, critical thinking, organization, and quantitative skills for operational success. On the
other hand, the respondents in healthcare also value critical thinking, but also emphasize rapid
decision-making and professionalism. Respondents in the construction sector value flexibility,
safety, and independent decision-making. These subthemes all evolved out of the major theme.
Quantitative Alignment of Soft Skill Categories: Individual, Collaborative, and Procedural
The last Likert scale question asked the respondent to scale the three categories of soft
skills: Individual, collaborative, and procedural. This data was run through the data analysis tool
SPSS. Table 29 illustrates the mean, standard deviation, and skewness, whereas a mean closer to
five is deemed more aligned with the needs of the industry and a lower standard deviation means
more consensus amongst the respondents. In addition, a skewness number closer to zero
indicates less skew either way.
Table 29
Mean and Standard Deviation of Likert Scale Soft Skills Gap
Category
Mean
Standard Deviation
Skewness
Individual
1.33
1.0000
1.071
Collaborative
1.67
1.581
.705
Procedural
1.67
1.581
.217
In addition to mean, standard deviation, and skewness, it is also valuable to determine the
frequencies by which respondents chose each rating. Table 30 illustrates the Valid Percent
frequencies of each descriptor in the Likert scale.
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Table 30
Valid Percents of Scale Descriptors
Scale
Category
Not
Aligned
Somewhat
Not Aligned
Indifferent to
the Soft Skill
in Our
Industry
Somewhat
Aligned
Perfectly
Aligned
Valid Percents
Individual
11.1%
66.7%
0%
22.2%
0%
Collaborative
22.2%
44.4%
0%
11.1%
22.2%
Procedural
33.3%
22.2%
0%
33.3%
11.1%
Conclusion
This action research study examined the relationship between the soft skills taught by the
West Greene School District and the soft skills most valued by the largest employers in Greene
County, Pennsylvania. Through a mixed methods concurrent embedded design, this study
triangulated quantitative data, analyzed through SPSS, with qualitative data, thematically
analyzed using NVivo 15 software, to ensure a comprehensive understanding of workforce needs
and the district’s current alignment with those needs.
The results of the study indicate that while there is a degree of alignment between the
district’s soft skills curriculum and employer expectations, notable distinctions emerged.
Communication, teamwork, and responsibility were consistently rated as essential across
industries and for both entry-level and professional roles. However, variations by sector were
also apparent. The education sector emphasized emotional intelligence and critical thinking;
healthcare employers prioritized rapid decision-making and professionalism; and construction
industry leaders placed significant importance on flexibility, independent problem-solving, and
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safety. Additionally, differences in the expectations for entry-level versus professional positions
highlighted the need for a differentiated approach in preparing students for various career
trajectories.
Quantitative analyses provided statistical insight into the ranking and alignment of
individual, collaborative, and procedural soft skills, while qualitative analyses offered rich,
contextual perspectives that underscored the complexity of workforce expectations. Although not
all quantitative findings yielded statistically significant results, the qualitative data provided
valuable nuance, reinforcing the need for a curriculum that is responsive to the diverse demands
of the local economy.
Summary
In sum, the findings from this study provide a critical foundation for enhancing the West
Greene School District’s soft skills curriculum. By addressing both the universally valued
competencies and sector-specific needs identified by local employers, the district can better
prepare its graduates to enter and sustain successful careers within the Greene County workforce.
These results not only inform curriculum development but also contribute to broader efforts
aimed at bridging the gap between education and employment, ensuring that students are
equipped with the competencies necessary to thrive in an evolving labor market. The following
chapter will discuss these findings in greater depth, interpreting their implications for practice,
policy, and future research, and offering recommendations for the continued development of a
responsive and effective soft skills curriculum.
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Chapter V
Conclusions and Recommendations
This Doctoral Capstone Action Research Project was designed to survey the top
employers, by total number of employees, of Greene County, Pennsylvania, in order to create an
updated positive behavior model for the West Greene School district that focuses on the soft
skills that these employers find most valuable. While the District already has a positive behavior
model, it is in need of a facelift that is rooted in action research that will provide the best
economic outcomes for its students. This chapter will share conclusions, recommendations, and
future implications as the research is centered on the following research questions:
Research Question 1
To what extent do the top Greene County business employers in the public and private
sectors value the soft skills that are being taught by the West Greene School District for entry
level positions?
Research Question 2
To what extent do current job openings and projected job openings in Greene County
compare to statistics from the US Bureau of Labor and Statistics?
Research Question 3
How do graduates with the desired soft skills, as determined by the West Greene School
District administration, compare to the soft skills identified by local business leaders to sustain
the workforce of Greene County, Pennsylvania?
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Conclusions
Research Question 1
The researcher asked, “To what extent do the top Greene County business employers in
the public and private sectors value the soft skills that are being taught by the West Greene
School District for entry level positions?” Quantitative data taken from the survey was analyzed
using SPSS. Qualitative data taken from the survey was analyzed using Nvivo 15. Based on the
data returned from SPSS, respondents ranked Individual Soft Skills as most important of the
three soft skills categories with a mean response of 1.6/3. With a standard deviation of .699,
there was consensus amongst respondents that Individual Soft Skills ranked either first or second
amongst respondents. The second ranked soft skill category was Collaborative Soft Skills with a
mean response of 2/3. With a standard deviation of .943, there was less consensus amongst
respondents of this ranking, but not enough to invalidate the consensus of the group of
respondents that Collaborative Soft Skills was the second most valued category of soft skills.
Lastly, the third and lowest ranked category of soft skill was Procedural Soft Skills with a mean
ranking of 2.4/3. With a standard deviation of .699, there was consensus that this is the lowest
ranked category of soft skills. However, it must be determined if the differences in these ranks
occurred at random or if there was a true statistically significant difference in the data. Therefore
a Friedman Test was administered. The goal of the Friedman Test was to indicate if a statistically
significant difference existed in the data or if the outcome was a result of chance. When
analyzing a Friedman Test, or the Wilcoxon Signed Rank Test, any p-value over .05 is not seen
as statistically significant; therefore, our p-value of .202 indicated that there are no real
differences between group medians and that the differences in rank most likely occurred by
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statistical chance. Therefore, the researcher cannot make definitive conclusions based on the data
collected from these survey questions.
Likewise, the qualitative data suggested split valuing amongst respondents. Respondents
pointed out that while Individual Soft Skills enhance the other categories of soft skills, it has its
own skill-specific drawbacks. Additionally, Collaborative Soft Skills are very difficult to teach in
the workplace, and while Procedural Soft Skills ensure organizational efficiency, people can get
better at them over time. These themes reinforce the notion that respondents do not conclusively
value one category of soft skills over another. Since it cannot be definitively ascertained which
category of soft skills as a whole is valued most by employers, we must dive deeper to determine
which soft skills from each category are valued most in order to offer suggestions of which soft
skills will provide the best grounds for a positive behavior model.
Individual Soft Skills
Quantitative data from these survey questions was analyzed using SPSS. The resulting
analysis has shown that “Work Under Pressure” returned a mean value of 2.5/4 soft skills in this
category with a standard deviation of 1.269, “Innovative Problem-Solving” returned a mean
value of 2/4 soft skills in this category with a standard deviation of .943, “Integrity and
Empathy” returned a mean value of 2.2/4 soft skills in this category with a standard deviation of
1.135, and “Emotional Intelligence” returned a mean value of 3.3/4 soft skills in this category
with a standard deviation of .823. These averages and standard deviations reflect a noncommittal
rank valuation for each of the soft skills amongst respondents. Not one soft skill stuck out as
more or less valued than another and the standard deviations reflect moderate to strong
consensus of those values. The results of the Friedman Test, with a p-value of .118, reflect that
the outcome of this dataset is more than likely a result of chance. Any p-value over .05 indicates
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that there is no evidence of a statistically significant difference between the soft skill and any
differences in value are more than likely due to a random chance and does not show a true or
statistically significant consensus amongst respondents; therefore, no further tests were
completed because consensus amongst ranks could not be statistically concluded. Therefore, the
researcher cannot make definitive conclusions based on the collected data because it is
statistically inconclusive.
In surveying respondents, it was also important to identify any potential Individual Soft
Skills that are valued by employers that were not listed by the researcher on the survey in order
to have a holistic view of the Individual Soft Skills valued by each employer. Using Nvivo 15 to
analyze qualitative data themes from the survey, it became clear that respondents valued different
soft skills in professional positions compared to entry-level positions, and that different sectors
valued different Individual Soft Skills. Respondents noted that in professional level positions
Individual Soft Skills that are valued are “Leadership,” “Problem-Solving,” “Initiative,” and
“Independent Decision-Making;” whereas, for entry level positions, respondents indicated that
Individual Soft Skills like “Communication,” “Teamwork,” “Adaptability,” and “Time
Management” were valuable. On the other hand, respondents from the education sector valued
“Emotional Intelligence” and “Empathy” as valuable Individual Soft Skills, and respondents
from business sectors and service industries value “Stress Management,” “Reliability,” and
“Initiative” as important Individual Soft Skills. While the qualitative input added an additional
layer of data, it did not conclusively indicate the preference of any additional soft skills over the
soft skills indicated in the survey.
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Collaborative Soft Skills
The next set of data to be reviewed is the resulting data on Collaborative Soft Skills. In
analyzing the data, it has shown that “Communication” returned a mean value of 1.1/5 soft skills
in this category with a standard deviation of .316, “Teamwork” returned a mean value of 2.3/5
soft skills in this category with a standard deviation of .823, “Leadership Skills” returned a mean
value of 3.4/5 soft skills in this category with a standard deviation of .966, “Business Etiquette”
returned a mean value of 3.6/5 soft skills in this category and a standard deviation of 1.075, and
“Global and Cultural Diversity” returned a mean value of 4.6/5 soft skills in this category with a
standard deviation of .966. Based on the raw averages combined with the standard deviations,
“Communication” was valued most with high consensus. When the Friedman Test was
completed on these skills, a p-score of <.001 was found, meaning that these numbers did not
happen by mere coincidence and that there is some actionable data in this dataset. There is a
statistically significant chance that the respondents valued certain Collaborative Soft Skills over
others. Therefore, a Wilcoxon Signed Rank Test was completed on each Collaborative Soft Skill
against one another to find which soft skills actually ranked highest.
When analyzing a Wilcoxon Signed Rank Test, you must look at the “Z- Score” and
“p-score” of each of the comparisons. The Z- Score measures how many standard deviation
points away from the mean of zero that the data returned. Therefore, the larger the number, the
more statistically significant the comparison and higher likelihood that most of the respondents
felt one way and that numbers were less likely skewed by extreme values (Welkowitz, 2011, p.
92). When evaluating the returns from SPSS, the researcher must use the absolute value of the
Z-Score. The indication in the SPSS note will denote whether the Z- Score is “based on negative
ranks” or “based on positive ranks.” If the Z-Score is based on negative ranks, then the second of
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the two in the comparison group is the more likely choice, and if the Z-score is based on positive
ranks, then the first of the two in the comparison group is the more likely choice. When
evaluating the two-tailed p-value, anything less than .05 is considered a significant correlation
and extremely likely to occur (Welkowitz, 2011, p. 127). When evaluating these two scores
together, the Z-Score informs you which of the two compared soft skills was chosen more and a
p-score < .05 informs you the likelihood that the mean was not influenced by extreme outliers or
that it is the true choice of most respondents. First, the test determined that “Communication”
was ranked higher than “Teamwork” with a Z-Score of 2.489 and a two-tailed p-score of .013,
meaning that respondents do, in fact, rank “Communication” higher than “Teamwork”. Then,
the test determined that “Communication” overwhelmingly beat out “Global and Cultural
Diversity” with a Z- Score of 2.877 and a two-tailed p-score of .004 indicating that there is a
significant correlation to determine that respondents preferred “Communication” over “Global
and Cultural Diversity.” Next, “Communication” beat out “Leadership Skills” with a Z- Score of
2.871 with a two- tailed p-score of .004. This means that respondents overwhelmingly chose
“Communication” over “Leadership Skills”. “Communication” also outranked “Business
Etiquette" with a Z-Score of 2.831 and two-tailed p-score of .005. It must be noted that
“Communication” was seemingly the most obviously chosen soft skill of any soft skill in any of
the three categories. The next Collaborative Soft Skill to outrank another was “Teamwork.”
“Teamwork” outranked “Global and Cultural Diversity” with a Z-Score of 2.859 and two-tailed
p-score of .004, meaning that “Teamwork” was beyond a statistical significance chosen over
“Global and Cultural Diversity.” “Teamwork” was chosen over “Leadership Skills” with a
Z-Score of 1.998 and a two-tailed p-score of .046. Again, this p-score shows that “Teamwork”
was the clear choice between the two. Then, “Teamwork” outranked “Business Etiquette” with a
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Z-Score of 2.021 and a two-tailed p-score of .043. This p-score indicates that the rank was true
amongst respondents. Next, “Leadership Skills” outranked “Business Etiquette” with a Z-Score
of .263 and a two-tailed p-score of .793, indicating that “Leadership Skills” cannot be
definitively ranked higher than “Business Etiquette” because it returned a p-score over .05,
indicating that the rank could have been a result of extremes in the data. Then “Leadership
Skills” outranked “Global and Cultural Diversity” with a Z-Score of 2.235 and a two-tailed
p-score of .025 indicating that “Leadership Skills” was the clear choice amongst respondents.
The last Collaborative Skill to outrank another was “Business Etiquette,” outranking “Global and
Cultural Diversity” with a Z-Score of 1.999 and a two-tailed p-score of .046. This indicates that
respondents verifiably chose “Business Etiquette” over “Global and Cultural Diversity.” “Global
and Cultural Diversity” did not outrank any of the Collaborative Soft Skills. The Z-Scores and
p-scores of the Collaborative Soft Skills indicate that the respondents overwhelmingly, in a
statistically verifiable way, value “Communication” above the other soft skills of the category.
Therefore it is the suggestion of the researcher, based on this data return, that a positive behavior
model must be rooted in “Communication” first.
In surveying respondents, it was important to identify any potential Collaborative Soft
Skills that were valued by employers that were not listed by the researcher on the survey in order
to have a holistic view of the Collaborative Soft Skills valued by each employer. Using Nvivo 15
to analyze qualitative data themes from the survey, it became clear that “Communication” is
valued by each industry because of its interplay between teaming and mentorship opportunities.
While this soft skill is not new or different from the pre-identified list that was aggregated for
respondents, the qualitative data reinforced the quantitative data that “Communication” was the
highest valued Collaborative Soft Skill. The second theme that “Leadership” is an expected skill
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at all levels of tenure does not add to our aggregated list of Collaborative Soft Skills. While the
qualitative questions did not add to the list, it reinforced the value of “Communication” as an
integral soft skill to each industry, reinforcing the importance of its inclusion in the positive
behavior model.
Procedural Soft Skills
The next dataset to be examined was Procedural Soft Skills. The resulting analysis of the
data has shown that “Responsibility to Get the Job Done” returned a mean value of 1.89/5 of soft
skills in this category with a standard deviation of 1.269, “Critical Thinking” returned a mean
value of 2.4/5 of soft skills in this category with a standard deviation of 1.350, “Ability to Make
Decisive Decisions” returned a mean value of 2.9/5 of soft skills in this category with a standard
deviation of .876, “Flexibility for Organizational Change” returned a mean value of 3.2/5 of soft
skills in this category with a standard deviation of .919, and “Quantitative Skills” returned a
mean value of 4.3/5 of soft skills in this category with a standard deviation of 1.494. Based on
the raw averages combined with the standard deviations, “Responsibility to Get the Job Done”
was valued most with but not with a very high consensus. When the Friedman Test was
completed on these skills, a p-score of .002 was found, meaning that these numbers should result
in actionable data. There is a statistically significant chance that the respondents valued certain
Procedural Soft Skills over others, meaning that a Wilcoxon Signed Rank Test was also
administered.
When analyzing a Wilcoxon Signed Rank Test, you must look at the “Z- Score” and
“p-score” of each of the comparisons, as previously noted. The Z- Score measures how many
standard deviation points away from the mean of zero that the data returned. Therefore, the larger
the number, the more statistically significant the comparison and higher likelihood that most of
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the respondents felt one way and that numbers are less likely skewed by extreme values
(Welkowitz, 2011, p. 92). When evaluating the returns from SPSS, the researcher must use the
absolute value of the Z-Score. The indication in the SPSS note will denote whether the Z- Score
is “based on negative ranks” or “based on positive ranks.” If the Z-Score is based on negative
ranks, then the second of the two in the set is the more likely choice, and if the Z-score is based
on positive ranks, then the first of the two in the set is the more likely choice. When evaluating
the two-tailed p-value, anything less than .05 is considered a significant correlation and
extremely likely to occur (Welkowitz, 2011, p. 127). When evaluating these two scores together,
the Z-Score informs you which of the two compared soft skills was chosen more and the p-score
informs you the likelihood that the mean was influenced by extreme outliers or if it is the true
choice of most respondents. Therefore, a Wilcoxon Signed Rank Test was completed on each
Procedural Soft Skill as a comparison against one another to find true rank that was not
determined by chance. First the test determined that “Responsibility to Get the Job Done” was
ranked higher than “Quantitative Skills” with a Z-Score of 2.534 and a p-score of .011, meaning
that respondents do, in fact, rank “Responsibility to Get the Job Done” higher than Quantitative
Skills. Then, the test determined that “Responsibility to Get the Job Done” largely beat out
“Flexibility for Organizational Change” with a Z- Score of 2.228 and a two-tailed p-score of .026
indicated that there is likely a significant enough correlation to determine that respondents
preferred “Responsibility to Get the Job Done” over “Flexibility for Organizational Change”.
Next, “Responsibility to Get the Job Done” beat out “Ability to Make Decisive Decisions” with a
Z- Score of 2.145 with a two- tailed p-score of .032. This means that there is an excellent chance
that “Responsibility to Get the Job Done” is actually more valued than “Ability to Make
Decisive Decisions” amongst respondents. Respondents seemed to rank “Responsibility to Get
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the Job Done” higher than “Critical Thinking” with a Z-Score of .889; however, with a twotailed p-score of .374, it cannot be statistically verified as higher ranked in each case. The next
Procedural Soft Skill, “Ability to Make Decisive Decisions”, outranked “Quantitative Skills” and
“Flexibility for Organizational Change” with respective Z-Scores of 1.813 and .690; however,
with respective two- tailed p-scores of .070 and .490, the researcher cannot guarantee anything
more than coincidence between respondents. “Critical Thinking,” the next Procedural Soft Skill,
outranked “Quantitative Skills” with a Z-Score of 2.265 and a p-score of .024, meaning that it is
clear that “Critical Thinking” outranked “Quantitative Skills” amongst respondents. Although
“Critical Thinking” seemingly outranks “Flexibility for Organizational Change” and “Ability to
Make Decisive Decisions,” it cannot be proven with a two- tailed p-score of .158 and .437
respectively. The last Procedural Soft Skill to outrank at least one other Procedural Soft Skill,
“Flexibility for Organizational Change” outranked “Quantitative Skills” with a Z-Score of 1.658,
but it cannot be proven with consensus from respondents with a two- tailed p-score of .097.
Quantitative Skills did not outrank any of the Procedural Soft Skills. Therefore the consensus,
highest ranked Procedural Soft Skill was “Responsibility to Get the Job Done,” which aligns
with the means from the respondents. Therefore, the researcher can conclude that a positive
behavior model should include “Responsibility to Get the Job Done.”
In surveying respondents, it was important to identify any potential Procedural Soft Skills
that are valued by employers that were not listed by the researcher on the survey in order to have
a holistic view of the Procedural Soft Skills valued by each employer. Using Nvivo 15 to analyze
qualitative data themes from the survey, it became clear that Procedural Soft Skills are
non-negotiable soft skills to a successful workforce, but the consensus amongst respondents
varied in terms of which soft skills were non-negotiable to specific industries. Respondents in the
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education sector noted that “Time Management” was an important Procedural Soft Skill that
could have been included, while respondents from the healthcare field indicated that “Informed
Decision-Making,” “Consistency,” and “Professional Standards” are procedural-type soft skills
of high importance. Then, respondents from the construction sector indicated “Safety” and
“Flexibility” as important soft skills that are key to the industry. Whereas these added soft skills
seemed important to respondents, it is clear from quantitative data that “Communication” is of
the highest importance and value amongst respondents. While respondents added
“Communication” to this soft skill category through their qualitative responses, it does not take
away from the quantitative data suggesting the importance of “Responsibility to Get the Job
Done.” It only reinforces “Communication’s” place in the positive behavior plan.
Based on the results from the respondents, it must be noted that only the rank order from
Collaborative and Procedural Soft Skill categories could be verified to not be a result of skewed
numbers. Therefore, the researcher will only provide conclusions and recommendations from
those two datasets as it pertains to the first research question. The highest ranked Collaborative
Soft Skill was “Communication” and the highest ranked Procedural Soft Skill was
“Responsibility to Get the Job Done.” Based on this feedback from respondents, the West Greene
School District will certainly use these two soft skills as the cornerstone of its positive behavior
support plan moving forward.
Research Question 2
The researcher asked, “To what extent do current job openings and projected job
openings in Greene County compare to statistics from the US Bureau of Labor and Statistics?”
The results from this question will allow the researcher to determine to what degree the labor
market of the respondents is representative of the labor market of the area as a whole in terms of
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their projected needs. An overwhelming majority of respondents were from the education sector
meaning that only 20% of the respondents were from the construction sector, while 10% were
from health care and social assistance sectors. While this is very clearly not representative of
Greene County employers, it does say a great deal about the willingness of local school districts
and intermediate units to work and collaborate with one another. Also, 70% of the respondents
have between 50 and 200 employees. In a county with 677 total employer establishments and
9,637 employed people, the average employer establishment has roughly 14 employees that have
an expected year-over-year growth of 2.78% (Data USA, 2024). Therefore, a reasonable observer
can ascertain that the US Bureau of Labor and Statistics would expect these industries to grow
between 1.39 and 5.56 people over the next year. Based on the feedback of respondents,
respondents are expecting between four and five openings needed to be filled within the next
year and five year projections vary. With this data being taken into consideration, Greene
County, Pennsylvania, and the respondents of this survey seem to be fairly representative of each
other.
Research Question 3
The researcher asked, “How do graduates with the desired soft skills, as determined by
the West Greene School District administration, compare to the soft skills identified by local
business leaders to sustain the workforce of Greene County, Pennsylvania?” Respondents were
asked Likert scale style questions with zero equaling “Not Aligned,” one equaling “Somewhat
Not Aligned,” two equaling “Indifferent to the Soft Skill in Our Industry,” three equaling
“Somewhat Aligned,” and four equaling “Perfectly Aligned.” Therefore, means derived from
SPSS closer to four illustrate higher alignment. Standard deviations were also reported from
SPSS. For Likert scale questions, standard deviation shows how clustered responses are to the
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mean, and the higher the standard deviation, the more scores are spread out with less consensus.
Valid Percent frequencies were also reported in an effort to compare the means and the frequency
of each Likert response. Comparing these two data points will determine if there was consensus
amongst respondents. Along with SPSS to analyze quantitative data, Nvivo 15 software was used
to analyze qualitative data for each soft skill category to determine a deeper understanding of the
alignment between the soft skills listed and the needs of each sector. First, each soft skill
category was evaluated but the results came back low and relatively inconclusive. Individual Soft
Skill returned a mean value of 1.33, a standard deviation of 1 and a skewness of 1.071. Since the
skewness indicated that the mean is actually higher than the median value this leads the
researcher to conclude that there is a consensus of low value for this category. The next category
analyzed was Collaborative Soft Skills, which returned a mean of 1.67, a standard deviation of
1.581, and a skewness of .705. This leads one to conclude that there is moderate to low
consensus amongst respondents. The same applies to the third soft skill category: Procedural Soft
Skills. With a mean valuation of 1.67, a standard deviation of 1.581, and a skewness of .217, the
same logic applies as Collaborative Soft Skills. With this being said, there is inconclusive data to
suggest that one group is valued more so than the others. Therefore, each soft skill must be
evaluated to determine their overall value to employers.
Individual Soft Skills
The first group of soft skills that were analyzed for their relative importance to local
employers were the Individual Soft Skills. The mean for “Work Under Pressure” was 2.56, the
standard deviation was 1.509, and the skewness was -.697. While the results of this data indicate
that respondents viewed “Work Under Pressure” between somewhat indifferent and somewhat
aligned, the standard deviation in combination with the negative skew indicate that while some
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respondents rated it low, a notable number of respondents rated it higher leading the researcher to
conclude that there is a mixed perception amongst respondents as indicated in Table 24. The next
soft skill to be analyzed was “Innovative Problem-Solving.” The reported mean was 3, the
standard deviation was 1.225, and the skewness was -2.100. While the respondents indicated, on
average, that they somewhat valued this soft skill, the standard deviation and skewness indicated
there was no real consensus amongst the respondents as some respondents marked it as very
important while others, not important at all, as shown in Table 24. The third soft skill that was
analyzed was “Integrity and Empathy,” returning a mean of 3.67, a standard deviation of .500,
and a skewness of -.857. Compared to the other Individual Soft Skills, “Integrity and Empathy”
returned consensus that it is a valuable soft skill to local industries. The last soft skill of this
grouping to be analyzed was “Emotional Intelligence.” This soft skill returned a mean of 3.33, a
standard deviation of 7.07, and a skewness of -.606. The returns from this data did not indicate
any consensus towards the mean and therefore unusable. From the embedded qualitative
question, it was the consensus of respondents that Individual Soft Skills as written showed high
consensus; however, this could not be verified in all cases with quantitative data. Based on
quantitative and qualitative returns, there was consensus that “Integrity and Empathy” is a
valuable soft skill in its employees. Since this is the only definitive data to indicate the
importance of an Individual Soft Skill, the West Greene School District should use this soft skill
in its positive behavior plan.
Collaborative Soft Skills
The next group of soft skills that were analyzed for their relative importance to local
employers were Collaborative Soft Skills. The mean for “Communication” was 3.78, the
standard deviation was .441, and the skewness was -1.620. This means that “Communication” is
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between somewhat and perfectly valued with relatively high consensus. The negative skewness
indicates that the median is slightly higher than the mean; however, “Communication” is very
valuable to employers. “Teamwork” returned a mean of 3.44 with a standard deviation of .527
indicating that it is the consensus of respondents that “Teamwork” is valuable. The positive
skewness indicates that the mean is slightly less than the actual median; however, the value for
“Teamwork” is high enough with enough consensus to possibly include it in a positive behavior
plan for students. Next, “Global and Cultural Diversity” returned a mean of 2.22 with a standard
deviation of 1.202 and skewness of -.537, indicating that this soft skill not only lacks consensus,
but it also lacks value in the eyes of the top employers in the area. Next, Leadership Skills
returned a mean of 3.33 with a standard deviation of .500 and a skewness of .857. This indicates
that “Leadership Skills” are valued with consensus. The last Collaborative Soft Skill analyzed
was “Business Etiquette.” This soft skill returned a mean of 2.78, standard deviation of .833, and
a skewness of -1.166. The negative skewness indicates that the mean is slightly higher than the
mean with relatively high consensus; therefore, “Business Etiquette” could be of value in a
positive behavior plan. While the quantitative data indicates that there is some consensus
between a few Collaborative Soft Skills, the qualitative data reinforced the importance of those
soft skills and provided some sub-themes that reinforce the importance of Collaborative Soft
Skills.
Procedural Soft Skills
The next set of soft skills that were evaluated were Procedural Soft Skills. The first
Procedural Soft Skill was “Quantitative Skills.” This soft skill returned a mean value of 2.22, a
standard deviation of 1.394, and a skewness of -.146. This indicates very little consensus in value
for this soft skill. The next soft skill “Flexibility for Organizational Change” returned a mean
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value of 3.22 with a standard deviation of 1.093 and skewness of -1.289. These numbers indicate
that while the soft score averages highly, there is little consensus amongst respondents
determining its actual value. Next, “Critical Thinking” returned a mean value of 3.33 with a
standard deviation of 1 and skewness of -1.821. These numbers indicate a small amount of
consensus based on the skewness leaning towards high median valuations. “Ability to Make
Decisive Decisions” returned a mean value of 3.22. The standard deviation indicates that there is
moderate consensus amongst respondents and the skewness indicates that the median value is
higher than the mean. This indicates, as posited by Table 28, that there is certainly value in this
soft skill. The same holds true for the final Procedural Soft Skill: Responsibility to Get the Job
Done. This soft skill returned a mean value of 3.33, standard deviation of 1, and a skewness of
-1.821. The logic of this data would be the same as “Critical Thinking” and informs the
researcher of it higher than stated value. The qualitative questions indicated a high alignment of
value between the employer and the listed soft skills.
The analysis of Research Questions 1, 2, and 3 reveals several nuanced insights into the
alignment between soft skills valued by Greene County employers and those emphasized in the
West Greene School District. While quantitative data provided a measurable perspective on
employer preferences, qualitative responses added critical context to these findings, highlighting
sector-specific priorities.
In regards to the first research question, although the overall ranking of the three soft skill
categories, Individual, Collaborative, and Procedural, suggested a trend, the Friedman Test
revealed no statistically significant differences among them, indicating that employers may view
all three as relatively comparable in importance. Qualitative data supported this ambiguity,
noting that skill categories are interdependent. However, within each category, clearer
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preferences emerged. Specifically, “Communication” in the Collaborative Soft Skills category
and “Responsibility to Get the Job Done” in the Procedural Soft Skills category emerged as
statistically significant, verifiable preferences. These findings suggest that these two skills should
serve as foundational elements in any behavior or soft skills curriculum.
Next in regards to the second research question, while there was overrepresentation from
the education sector, the hiring projections from survey participants were consistent with the
U.S. Bureau of Labor Statistics trends, suggesting a moderate degree of representativeness. The
feedback also highlights a strong willingness among local educational employers to engage in
regional workforce development conversations.
Lastly in regards to the third research question, the alignment between graduates’ soft
skills and employer expectations yielded mixed results. While overall means indicated moderate
alignment, high standard deviations and skewness pointed to inconsistencies in perception
among respondents. Notably, “Integrity and Empathy,” “Communication,” and “Responsibility
to Get the Job Done” stood out as skills with both high mean values and relative consensus,
suggesting they are more widely valued across sectors. Qualitative themes reinforced these
quantitative findings, especially the primacy of “Communication” and “Responsibility” as core
workplace competencies.
Overall, the study concludes that while employers in Greene County recognize the value
of a range of soft skills, only a select few demonstrate statistically significant consensus across
respondents. These results offer practical direction for the West Greene School District to
prioritize specific soft skills like “Communication,” “Responsibility to Get the Job Done,” and
“Integrity and Empathy,” within its positive behavior and workforce preparation initiatives. This
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alignment may ultimately enhance graduate preparedness and better serve the region’s evolving
economic needs.
Limitations
While this study was designed to provide a comprehensive understanding of the
alignment between soft skills valued by local employers and those taught within the West Greene
School District, several limitations must be acknowledged that affect the interpretation and
generalizability of the findings. These limitations span methodological, geographic, and
analytical domains and are important to consider when applying the results beyond the scope of
this study. Specifically, challenges related to sample size and response rate, geographic and
economic specificity, reliance on self-reported data, potential for researcher bias, and limitations
in mixed methods integration all impacted the depth and breadth of the conclusions that could be
drawn. The following subsections outline each of these limitations in detail and provide insight
into how they may have influenced the study's results.
The first apparent limitation of this study is its limited sample size and low response rate.
Initially, only the top 10 on the list of 50 were sent surveys to be completed; however, the
researcher soon began to realize that the scope would need to be broadened in order to get ten
respondents. Therefore, more potential respondents were notified and previous respondents were
reminded. I repeated this cycle until I had notified the top 50 employers, which had exhausted
the list in Appendix A. At that point, potential respondents were reminded and kindly asked to
take the survey until the 10th survey response had been submitted. This did, however, create a
response rate of 20%. This lower response rate than previously anticipated, limits the
generalizability of the findings and may not represent the full spectrum of employer perspectives
across the county.
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The next limitation of the study is the geographic and economic specificity. While this
study aimed to help the West Greene School District create a positive behavior plan for its
district, it must be understood that there is limited transferability in the findings because Greene
County, Pennsylvania is a very rural region with a unique economic profile. Therefore, findings
might not easily transfer to urban or suburban school districts or areas more economically
diverse.
After the limitation of geographic specificity, the next limitation is in self-reported data.
The survey relies solely on data that is self-reported which may include bias. In addition to
self-reported data, data collected from each employer may have been collected from people of
varying backgrounds, educational levels, and positions within the company/school district. This
increases the likelihood of data that is inconsistent across respondents as scientific controls could
not be further implemented in the collection of data to maintain a higher degree of anonymity.
While the data that was submitted was submitted by people working in each of those industries
and were employed by the employer, specific and consistent employee positions were not
requested to fill out the survey.
In addition to self-reporting bias, there is also the potential for researcher bias and mixed
methods integration challenges. Despite the use of the Nvivo 15 software, qualitative analysis is
susceptible to researcher bias in theme development and coding. In addition, respondents were
unable to fully differentiate between the three categories of soft skills, leading to overlap in skill
reporting in qualitative questions. This limited the potential interpretation of data because solid
outcomes could not be aggregated from the responses. In addition to these types of biases,
respondents from the education sector responded at 70% of the overall participation meaning that
certain soft skills might be accounted for more than others based on the nature of the sector.
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In conclusion, while the study offers valuable insights into the alignment of soft skills
between local industry expectations and school-based instruction, the aforementioned limitations
underscore the need for caution when interpreting its findings. The small sample size, regional
specificity, and inherent biases within self-reported and researcher-analyzed data all contribute to
constraints in generalizability and replicability. These factors, combined with disproportionate
sectoral representation and overlapping soft skill interpretations, suggest that in further research
incorporating a broader sample, clearer role delineation amongst respondents, and more refined
qualitative coding practices would strengthen the applicability of the results. Despite these
limitations, this study serves as an important foundation for ongoing efforts to bridge educational
practices with workforce demands in rural communities like Greene County, Pennsylvania.
Recommendations for Future Research
While the findings of this study provide valuable insight into the alignment between local
employer expectations and the soft skills emphasized in the West Greene School District, several
opportunities exist to expand and strengthen future research in this area. As with many
exploratory studies, limitations in sample size, sector representation, and data collection methods
suggest important directions for continued investigation. Future studies should aim to engage a
broader and more diverse group of participants, adopt more targeted respondent roles, and
incorporate additional qualitative methods such as interviews or focus groups to enhance data
richness and triangulation. Furthermore, longitudinal and comparative research would deepen
understanding of how soft skills alignment evolves over time and across educational and
economic contexts. The following recommendations are offered to guide researchers seeking to
build upon the foundation of this study and extend its relevance across both rural and broader
workforce development settings.
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While it is not unique to this research study, future studies should aim for a larger and
more diverse sample. The goal of this study was to have ten respondents because the researcher
understood the potential limitations of the population. However, a larger sample size means that
more diverse voices will be heard in the data analysis. While ten was always the goal, having
70% of respondents from the education sector was not. In future studies, efforts need to be made
to have a better cross section, and more representative group of participants. This will avoid
overrepresentation of a single industry, which this study is. In addition, having a larger sample
size will increase the generalizability of results.
Next, future research might track and gather data from specific job roles or specify hiring
personnel as the main data contributors. This will provide a more consistent perspective on skill
importance in the hiring process, not just to the industry as a whole. This will reduce the
variability introduced by respondents’ differing organizational rolls or backgrounds.
If this study were to be replicated, additional qualitative data collection methods should
be employed to guarantee a higher level of triangulation of data. In doing this, it would limit the
misunderstanding that clearly took place in the data collection of this study. Respondents were
inadvertently going between soft skill categories in a way that made the results for the qualitative
questions mostly inconclusive. By adding in follow-up interviews or focus groups, the researcher
could gain a better understanding of employer needs and wants, beyond the survey responses.
This would in turn refine the integration of mixed methods as the appropriate tool used to gain
data from respondents. In addition, a team based coding of themes could be used to limit
researcher bias.
In addition to methodology recommendations, it is important to determine where this
research can go from here to potentially deepen the study as it is and to provide better breadth.
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Based on the conclusions gathered from data analysis, the West Greene School District can
implement a revised soft skills curriculum. Based on these revisions to the curricula, follow-up
studies could assess its effectiveness through pre- and post- measures, employer feedback, and
graduate success rates. These findings could be used to broaden the scope of the study using this
study as a blueprint. Urban and suburban populations could use this outline to add to the body of
research to compare and contrast their findings. Ultimately, based on the outcomes of this
research study and others that build upon it, researchers could generate and include longitudinal
studies to determine the overall effectiveness of this process over time. This research study is a
snapshot in time and is not reflective of historic economic or educational trends. Future research
could track the effectiveness of revised soft skills curricula over time, from this data, by
examining student outcomes and local employment rates. This would ultimately determine
whether alignment improvements actually influence workforce readiness and job placement.
In summary, this study lays the groundwork for understanding the relationship between
local workforce demands and soft skills instruction within a rural school district. However, to
build on this foundation and enhance both the depth and breadth of future research, intentional
methodological improvements and broader study scopes are necessary. Increasing sample
diversity, refining respondent roles, incorporating richer qualitative methods, and conducting
longitudinal assessments will strengthen the reliability, validity, and applicability of findings.
Furthermore, extending this research to include urban and suburban contexts can offer valuable
comparative insights and contribute to the development of scalable, data-informed soft skills
curricula. Ultimately, continued exploration of this topic will not only support regional
workforce readiness but also help educational institutions more effectively prepare students for
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the evolving demands of the 21st-century labor market, all based on the findings related to the
West Greene School District and the labor market of Greene County, Pennsylvania.
Summary
This Doctoral Capstone Project surveyed the local workforce, more specifically the top
employers in Greene County, Pennsylvania by number of employees in order to answer the
following research questions:
1. To what extent do the top Greene County business employers in the public and
private sectors value the soft skills that are being taught by the West Greene
School District for entry level positions?
2. To what extent do current job openings and projected job openings in Greene
County compare to statistics from the US Bureau of Labor and Statistics?
3. How do graduates with the desired soft skills, as determined by the West Greene
School District administration, compare to the soft skills identified by local
business leaders to sustain the workforce of Greene County, Pennsylvania?
The study reviewed survey responses from ten of the fifty top employers in Greene
County, Pennsylvania, in terms of total employed. A Google Form was sent out to these fifty
employers and ten responded for a total response rate of 20%, indicating what type of industry
they work in, the number of employees the business employs, the number of projected openings
the company will have, the soft skill that they most value, and a rank of soft skills from a
predefined list.
The survey results enabled the researcher to determine that there is not one group of soft
skills that are valued higher than other groups, but specific soft skills like “Communication,”
“Responsibility to Get the Job Done,” and “Integrity and Empathy” should be used a building
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blocks for positive behavior models and workforce readiness within the West Greene School
District.
Ultimately, the value of this study lies not just in the insights it provides into local
employer expectations, but in its call to action. By identifying key soft skills such as
“Communication,” “Integrity and Empathy,” and “Responsibility to Get the Job Done,” this
research offers a roadmap for aligning educational priorities with workforce demands. In an era
where rural schools face mounting pressures to prepare students for an uncertain economic
future, this study affirms that success begins not only with academic proficiency but with
personal and professional character. If embraced with intention, the findings of this study can
help school leaders forge stronger partnerships with industry, enhance curriculum relevance, and
ultimately, empower students with the tools to succeed in both work and life to bridge
classrooms and communities.
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APPENDICES
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Appendix A
Top 50 Employers in Greene County
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Appendix B
Informed Consent Statement
●
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●
●
●
●
●
●
Informed Consent
Title of Study: Are Our Graduates Prepared: Comparing West Greene School District
Graduates’ Skills to the Needs of Greene County Employers
KEY INFORMATION
You are being asked by Michael Hildreth, Dr. Stephanie Williams, and Dr. Bart Donley to
participate in a research study. Participation in the study is voluntary, and you may stop anytime.
The purpose of the study is to identify the soft skills that are needed of the local businesses in
Greene County, Pennsylvania. In addition, local businesses will provide feedback as to whether a
local school district is providing the workforce with potential employees with the pertinent soft
skills who are capable of gaining positions for these businesses to sustain the local economy.
In this study, you will be asked to answer survey questions about how your business values the
soft skills that a local school district values for its students for entry into your workforce, how
your current job openings and projections compare with the US Bureau of Labor and Statistics,
and the degree to which the needs of your workforce are being met by the soft skills valued by a
local district.
It will take approximately 20 minutes to complete the study.
The potential risks during the study are: Potentially revealing sensitive, competitive information
while being an unidentified responder; negative feedback could potentially impact how
businesses are generally perceived to outside stakeholders of the school district; and your
responses could help dictate policy or curriculum adjustments that you may not personally agree
with. In an effort to mitigate these potential risks the purpose of the research will be clearly
communicated, confidentiality and anonymity practices will be observed, you may skip
questions that you are uncomfortable answering, and honest and accurate responses will be
collected without repercussion from the research team. Remember, you may stop taking the
survey at any time. In addition, if you feel the need to talk with someone, you may contact the
PennWest Edinboro counseling center at 814-732-2252, or for emergencies, call 814-732-2911.
There are no direct benefits to participants from the research. It will help researchers better
understand the steps that the West Greene School District can take to graduate students who can
thrive in the current job market and to not leave Greene County upon high school or
postsecondary graduation to pursue non-local economic opportunities.
SECURITY OF DATA
The online study is completely anonymous; you will not be asked to give any information that
could identify you (e.g., name). The survey is NOT linked to IP addresses. Individual responses
will not be presented, just the aggregated data.
Remember, taking part in this study is voluntary. If, while taking the survey, you feel
uncomfortable or no longer want to participate, you may stop at any time. To stop taking the
survey, you may either:
(1) proceed to the last page of the survey and press “Submit,” or (2) if you wish
to exit the survey, close your browser completely.
There are no consequences if you decide to stop participating in this study.
There is no identifiable information collected from you during this study; all other information
from this study will be confidential within local, state, and federal laws. The PennWest
ARE OUR GRADUATES PREPARED?
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124
University Institutional Review Board (IRB) may review the research records. The study results
may be shared in aggregate form at a meeting or journal, but there is no identifiable information
to be revealed. The records from this study will be maintained for a minimum of three (3) years
after the study is complete.
Your information collected in this research will not be used or distributed for future research,
even if all your identifiers are removed.
If you have questions about the research or a research-related injury, you can contact Dr.
Stephanie Williams at williams_s@pennwest.edu. If you have a question about your rights as a
research participant that you need to discuss with someone, you can contact the PenWest
University Institutional Review Board at InstReviewBoard@pennwest.edu.
If you would like a copy of this informed consent, please print this screen or contact Dr.
Stephanie Williams at williams_s@pennwest.edu. .
By clicking on the “I agree” box and continuing with the survey, you have acknowledged that
you have read the informed consent and are at least 18 years old. Also, you acknowledge that
you agree to participate in the study and have the right not to answer any or all the questions in
the survey. Finally, you understand your participation is entirely voluntary, and you may quit the
study at any time without penalty.
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125
Appendix C
IRB Approval
Are Our Graduates Prepared? Comparing West Greene School District Graduates’ Soft
Skills to Greene County Employers’ Needs
A Doctoral Capstone Project
Submitted to the School of Graduate Studies and Research
Department of Education
In Partial Fulfillment of the
Requirements for the Degree of
Doctor of Education
Michael S. Hildreth
PennWest University of Pennsylvania
July 2025
ARE OUR GRADUATES PREPARED?
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Dedication
This was all made possible by my wife, the love of my life. Without her, this project ends
here. I dedicate this to you because of your dedication to me and our family.
ARE OUR GRADUATES PREPARED?
Acknowledgements
I would like to personally thank Dr. Stephanie Williams, my faculty chair, for being
patient with me as she pushed me through this project. Also, thank you to Dr. Bart Donley, my
external committee chair and friend, for helping me see this through. Lastly, thank you to Dr.
Brandon Robinson for being a confidant and sounding board as we went through this together
and for giving me my start in educational leadership.
iv
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Table of Contents
Dedication
Acknowledgements
Table of Contents
List of Tables
Abstract
CHAPTER I. Introduction
Background
Capstone Focus
Research Questions
Expected Outcomes
Fiscal Implications
Summary
CHAPTER II. Literature Review
Required Skills
Hard Skills
Soft Skills
Acquisition of Soft Skills
Soft Skill Development
Teaching Soft Skills
Pre-Identified Soft Skills
Individual Skills
Working Under Pressure
Innovative Problem Solving
Integrity and Empathy
Emotional Intelligence
Collaborative Skills
Communication
Teamwork
Global and Cultural Diversity
Leadership
Business Etiquette
Procedural Skills
Quantitative Skills
Flexibility for Organizational Change
Critical Thinking
Responsibility to Get the Job Done
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2
3
4
5
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6
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9
9
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21
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Soft Skills in the Workplace and their Economic Impact
22
Soft Skills and Working From Home
26
Current and Projected Job Outlook of Greene County
30
The Economic Outlook of Greene County, Pennsylvania
31
Demographics of Greene County, Pennsylvania
32
Economic Demographics of Greene County, Pennsylvania
32
Comparing the Job Market of Greene County, Pennsylvania to the United States
34
Demographics of Greene County, Pennsylvania Schools
35
Graduate Preparedness of the West Greene School District
40
Summary
43
Chapter III. Methodology
44
Purpose
46
Setting and Participants
46
Research Plan
49
Research Methods & Data Collection
51
Validity
58
Summary
59
Chapter IV. Data Analysis & Results
61
Data Analysis
62
Results
64
Quantitative Industry Demographics
64
Qualitative Industry Demographics
67
Quantitative Ranking of Individual Soft Skills
68
Qualitative Aggregation of Individual Soft Skills
69
Quantitative Ranking of Collaborative Soft Skills
70
Qualitative Aggregation of Collaborative Soft Skills
72
Quantitative Ranking of Procedural Soft Skills
73
Qualitative Aggregation of Procedural Soft Skills
76
Quantitative Ranking of Soft Skills Categories: Individual, Collaborative, and Procedural
76
Qualitative Aggregation Soft Skills Categories: Individual, Collaborative, and
Procedural
77
Quantitative Alignment of Individual Soft Skills
78
Qualitative Alignment of Individual Soft Skills
80
Quantitative Alignment of Collaborative Soft Skills
81
Qualitative Alignment of Collaborative Soft Skills
82
Quantitative Alignment of Procedural Soft Skills
83
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Qualitative Alignment of Procedural Soft Skills
Quantitative Alignment of Soft Skill Categories: Individual, Collaborative, and
Procedural
Conclusion
Chapter V. Conclusions and Recommendations
Conclusions
Research Question 1
Individual Soft Skills
Collaborative Soft Skills
Procedural Soft Skills
Research Question 2
Research Question 3
Individual Soft Skills
Collaborative Soft Skills
Procedural Soft Skills
Limitations
Recommendations for Future Research
Summary
References
Appendix A
Appendix B
Appendix C
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List of Tables
Table 1
Table 2
Table 3
Table 4
Table 5
Table 6
Table 7
Table 8
Table 9
Table 10
Table 11
Table 12
Table 13
Table 14
Table 15
Table 16
Table 17
Table 18
Table 19
Table 20
Table 21
Table 22
Table 23
Table 24
Table 25
Table 26
Table 27
Table 28
Table 29
Table 30
33
35
37
38
39
39
41
47
51
65
66
66
68
69
70
71
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Abstract
This doctoral capstone project investigates the alignment between the soft skills taught by the
West Greene School District and the soft skills most valued by Greene County’s top employers.
In response to local economic challenges and a shrinking working-age population, this research
aims to determine whether the graduates of the West Greene School District are equipped with
the soft skills necessary for local employment and long-term community sustainability. The
purpose of the study was to assess the perceived value of the individual, collaborative, and
procedural soft skills amongst local business leaders and to evaluate whether the district’s current
programming sufficiently prepares students to meet workforce expectations. The research
employed a mixed-methods design, collecting both quantitative and qualitative data through
employer surveys. The findings revealed that “Communication,” “Responsibility to Get the Job
Done,” and “Integrity and Empathy,” stood out amongst the local employers. The study
concludes with strategic recommendations for aligning soft skill instruction with employer
expectations, emphasizing curriculum reform, community partnerships, and experiential learning
opportunities. This alignment is essential not only to improve graduate employability but also to
bolster the economic vitality of Greene County by cultivating a locally grounded,
workforce-ready population.
ARE OUR GRADUATES PREPARED?
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CHAPTER I
Introduction
Greene County, Pennsylvania, is an area rich in history and culture, yet it faces economic
challenges as its workforce diminishes and its industries evolve. Once a community that was
thriving with opportunities centered on natural resources, the county now struggles with a
decline in working-age residents which prompts concerns about the sustainability of its local
economy (U.S. Census Bureau, 2023). The West Greene School District recognizes the critical
role it plays in addressing these challenges by preparing its graduates to meet the needs of the
local employers to give them the soft skills required to remain in the community after graduation.
This capstone research project seeks to bridge the gap between education and the
workforce demands by evaluating the alignment of the district’s soft skills curriculum with the
expectations of the local employers. Specifically, the study will identify the soft skills deemed
necessary by the top employers in Greene County, Pennsylvania, compare local job opportunities
with national trends, and assess whether graduates of the West Greene School District possess
the skills necessary to sustain the workforce and to contribute to the county’s economic vitality.
Soft skills encompass interpersonal and non-technical abilities that enhance communication,
problem- solving, and collaboration. These skills are crucial for navigating workplace
challenges, fostering positive relationships, and building a supportive workplace environment.
Unlike technical skills, soft skills are versatile and transferable across various roles and
industries, increasing an individual's professional value (Iorio et al., 2022).
The findings of this research have far reaching implications. They aim to inform strategic
curriculum adjustments, to foster stronger partnerships with local industries, and to ensure that
West Greene graduates are equipped to thrive in the county’s workforce. By addressing these
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issues, the district not only positions itself to enhance student outcomes and achievement but also
to contribute to the long-term economic stability of Greene County, Pennsylvania.This is vital to
the local economy because according to Börner et al. (2018), as data-driven tools and artificial
intelligence begin to more routinely handle specialized hard skills, the demand for humans with
industry specific soft skills will rise (p. 12635). Since managing interpersonal relationships and
applying data insights to real life and dynamic situations that cannot be automated at this time,
employees who can effectively collaborate and innovate in response to changing demands,
underscoring the enduring value of soft skills in the economy, will thrive at a rate much higher
than those who do not possess them (Börner et al., 2018. p. 12637). This research underscores
the importance of proactive educational planning to meet the demands of an evolving economy
in order to ensure that the district remains an integral part of Greene County, Pennsylvania's
future.
Background
Greene County, Pennsylvania, is a vibrant county in Pennsylvania that is rich with
history, culture, and pride. However, what was once a county booming with economic
opportunity surrounding natural resources is now facing economic hardships due to many
potential factors. Therefore, the West Greene School District is interested in updating its
curriculum and its philosophical outlook on what a graduate of the district should look like in
order to meet the economic needs of the county. It is important for the longevity of our district
that our graduates come back to live in the district upon high school or college graduation. The
current trends indicate that our graduates are leaving the district in order to pursue economic
opportunities elsewhere. If our district does not put mechanisms in place for our graduates to
enter the local workforce or a promise of employment upon graduation for our students going to
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college, we will have a tax windfall that may prove to be unsustainable, not to mention the
broader economic implications of our graduates leaving our communities. In order to create a
graduate who is suited for our local industries, we must work with these businesses to identify
their needs in potential applicants and determine job availability for our graduates. As the current
principal of West Greene Jr./Sr. High School, we must understand the needs of our local
economy, in order to find out what skills and competencies it needs in order to create a graduate
to fill that need. The purpose of this capstone research project is to identify the skills and
competencies that are needed of the local businesses in Greene County, Pennsylvania. In
addition, local businesses will provide feedback as to whether the school districts of Greene
County, Pennsylvania are providing the workforce with potential employees who are capable of
gaining positions for these businesses to sustain the local economy.
Capstone Focus
The goal of this capstone project is to determine where the soft skills curriculum in the
West Greene Junior/Senior High School is in relation to the desired soft skills of our local
employers in an effort to create the best soft skills curriculum in order to mold graduates who are
prepared and needed for the local workforce. According to Börner et al. (2018), while the
demand for technical skills is still very high, the rise of data-driven and collaborative work
environments has led to a much needed influx of workers with specific sets of soft skills (p.
12360). Therefore, this is important research to the vitality of Greene County’s economy because
of these changes. In addition, this curriculum could provide our graduates with an edge in
employment because as technical roles grow more specialized, professionals who have a strong
set of foundational soft skills to collaborate across the boundaries of technical disciplines who
can manage projects and effectively convey technical information to non-specialists are in great
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demand (Börner et al., 2018, p. 12637). According to the United States Census Bureau, in 2023,
58.1% of people in Greene County, Pennsylvania were between the ages of 20 and 64; whereas,
in 2010, 63.8% of people in Greene County, Pennsylvania were between the ages of 20 and 64.
This equates to a 5.7% drop in working- age individuals living in the county. This is
unacceptable. Potential reasons for this dramatic drop is that the students of the county may not
be prepared for the jobs in the local job market, students may be unaware of the opportunities
posed by the local job market, or we are not providing our students with a soft skills education to
prepare them for the local job market, but a job market elsewhere, causing graduates to relocate.
Whereas the West Greene School District cannot account for or dramatically improve the
economic opportunities that our students have upon graduation, we can prepare them to live and
work in our community with a curriculum of soft skills that could improve their productivity in
the workplace more than 13% (Adhvaryu et al., 2023, p. 2165). If our graduates continue to
relocate, and this trend continues, the West Greene School District will not be in a position to
economically sustain itself. Therefore, the District must take it upon itself to determine to what
degree the current job market matches up with national trends, to what extent local employers
value our current soft skills curriculum, and how do our graduates’ soft skills compare to the
needs of our local employers.
Research Questions
In order to achieve the goal of this academic research, the researcher has asked the
following questions:
1. To what extent do the top Greene County business employers in the public and private
sectors value the soft skills that are being taught by the West Greene School District for
entry level positions?
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2. To what extent do current job openings and projected job openings in Greene County
compare to statistics from the US Bureau of Labor and Statistics?
3. How do graduates with the desired soft skills, as determined by the West Greene School
District administration, compare to the soft skills identified by local business leaders to
sustain the workforce of Greene County, Pennsylvania?
Expected Outcomes
Through the research of this study, the West Greene School District will be able to
ascertain if the district is of the same mind as local employers as it pertains to important soft
skills, if the local job market is a snapshot of the national job market in terms of jobs available to
our graduates, and if the soft skills curriculum of the West Greene School District is creating
workers that are in demand in the local economy. The importance of an updated soft skills
curriculum cannot be understated. According to a study conducted by Laari and Dube (2017) on
nursing students’ perceptions on their soft skills training, soft skills training is seen as highly
valuable by 68.8% of respondents (p. 1). Based on the outcomes of the data collected, the
researcher aims to aid the West Greene School District by providing recommendations on how to
adapt the District’s soft skills curriculum in grades 7-12. These recommendations will certainly
have fiscal implications that must be addressed in order to sustain the District’s curriculum.
Fiscal Implications
The researcher believes that there are wide ranging fiscal implications associated with the
outcomes of these research questions. These implications will have a significant impact on
budgeting priorities of the district, resource allocation, and potential partnerships. The outcome
of these research questions could potentially lead to a curriculum redesign in terms of revising
curriculum materials, purchasing new resources, or providing professional development for
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teachers to emphasize the soft skills that local employers prioritize, in an effort to address
misalignment. Potential outcomes could lead to program expansions and program contractions
that could require additional funding. On the other hand, there could be opportunities for cost
saving measures as a result of the potential research outcomes. Once alignment exists between
our curriculum and local employers, the district could leverage partnerships that involve
co-funded programs, student internships, mentorship opportunities; opportunities that could
reduce the school’s financial burden. The fiscal implications of these research questions highlight
the need for careful evaluation of programs and strategic investment. With this being said, the
researcher believes that the outcomes of this research could be integrated into school districts of
similar size and demographic. Greene County, Pennsylvania, is very unique in its economic
makeup; therefore, large suburban or urban schools might not benefit from the data collected
because their economic opportunities are going to vary dramatically compared to the economic
opportunities in Greene County, Pennsylvania. However, the researcher does believe that having
a soft skills curriculum with the foundational soft skills described in the research can be
implemented by any school district, large or small. In addition, any school that would follow the
processes of this research could create a soft skills curriculum based on whatever outcomes the
district sees fit. The desired outcome of this research is to graduate locally employable adults;
whereas, other districts’ desired outcomes could vary. By addressing workforce skill alignment
proactively the district could not only enhance student outcomes but also secure financial
stability through partnerships, grants, and community support.
Summary
Greene County, Pennsylvania, once a thriving hub of natural resource-based industries,
now faces economic challenges and a declining working-age population. The West Greene
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School District aims to address these challenges by aligning its soft skills curriculum with the
needs of local employers to better prepare graduates for the workforce and give them the soft
skills to remain and thrive in the community. Homegrown graduates are particularly valuable in
areas like Greene County, Pennsylvania, where retaining skilled workers is essential to address
challenges such as a stagnant job market and a shrinking population (Regional Economic
Analysis Project, 2024). This research explores the value placed on the soft skills by Greene
County, Pennsylvania’s, top employers, the alignment between local and national job trends, and
the readiness of District Graduates to meet the demands of the local workforce. By identifying
gaps and opportunities, this study seeks to inform curriculum improvements, foster relationships
and partnerships with local industries, and to secure financial stability for the District and its
communities through strategic investment in these curriculums and alignment to local workforce
needs because highly qualified graduates not only possess technical knowledge, or hard skills,
but also demonstrate essential soft skills, such as communication, adaptability, and teamwork
that are increasingly recognized as vital for workplace success (Iorio et al., 2022).
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CHAPTER II
Literature Review
Highly qualified high school graduates are the cornerstone of a thriving workforce
because they bring valuable skills that contribute to economic and community development.
Highly qualified graduates not only possess technical knowledge, or hard skills, but also
demonstrate essential soft skills, such as communication, adaptability, and teamwork that are
increasingly recognized as vital for workplace success (Iorio et al., 2022). The integration of
these skills allows graduates to navigate diverse challenges and foster innovation, positioning
them as indispensable assets in modern industries. Moreover, graduates who are equipped with
these soft skills enhance workplace efficiency and productivity, which are critical in fostering
sustainable economic growth (Adhvaryu et al., 2023, p. 2168).
In addition to the individual benefits these skills provide, the contributions of
“homegrown” employees to their local economies are substantial. When graduates remain in
their communities, they enhance the local workforce by creating a sense of continuity, stability,
and investment in regional development. This alignment strengthens community ties and ensures
that the economic benefits of an educated workforce directly support local growth. Homegrown
graduates are particularly valuable in areas like Greene County, Pennsylvania, where retaining
skilled workers is essential to address challenges such as a stagnant job market and a shrinking
population (Regional Economic Analysis Project, 2024).
Greene County faces unique workforce needs that underline the importance of preparing
students for local employment. The county’s economy, rooted in industries like healthcare,
education, and natural resource extraction, requires a pipeline of qualified graduates who can
meet its workforce demands while possessing the soft skills necessary for adaptability in a
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changing economic landscape (Data USA, 2024). This literature review aims to explore the role
of soft skills, such as communication, adaptability, and teamwork in enhancing graduate
readiness and to assess how aligning educational outcomes with local workforce needs can
contribute to the economic revitalization of Greene County. By addressing these dynamics, this
study seeks to identify strategies to better prepare West Greene School District graduates for
meaningful employment and long-term success in their home community.
Required Skills
When discussing the types of skills that are pertinent to any job or industry, it is
important to distinguish skills between “hard skills” and “soft skills.” Both types of skills are
equally important in the workplace, but bring different dynamics. Whereas, hard skills establish
the foundation of skills required to have a job, soft skills enhance the workplace by increasing
workplace culture and job satisfaction amongst employees. In short, soft skills are the skills
required by employees to create a thriving and vibrant workplace.
Hard Skills
According to Hendarman and Cantner (2017), hard skills are defined as skills related to
technical aspects to do some tasks in the job and take into account the acquisition of knowledge
to be competent in the skill (p. 141). Historically, the focus of schools have been on the
acquisition of hard skills or technical skills. In fact, technical/hard skills are perceived by
graduates as being relatively more critical for getting a job (Rainsbury et al., 2002, p. 10). Since
hard/technical skills are the foundation of curriculums and rated by employers during interviews
to determine if a person is suited for employment, hard skills have been the area of focus for
training programs. A person must have the technical/hard skills to perform job duties. While hard
skills form the basis of a person’s ability to complete a job, soft skills are needed to enrich the
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workplace and to drive innovation. Therefore, the focus of this study is to determine which soft
skills should make up the foundation of curricular changes in the West Greene Jr./Sr. High
School. Since the focus of schools for years has been the acquisition of technical skills, schools
must adapt to enrich our focus to include soft skills in a student’s education.
Soft Skills
While it may be difficult to pinpoint which soft skills are more or less applicable to
various employers, defining the term “soft skill,” is not. Soft skills encompass interpersonal and
non-technical abilities that enhance communication, problem- solving, and collaboration. These
skills are crucial for navigating workplace challenges, fostering positive relationships, and
building a supportive workplace environment. Unlike technical skills, soft skills are versatile and
transferable across various roles and industries, increasing an individual's professional value
(Iorio et al., 2022). Soft skills encompass characteristics that make individuals valuable assets to
employers. Typically, soft skill training emphasizes relationship building and the importance of
interpersonal interactions, which are essential for fostering collaboration and positive
connections. Soft skills also enhance confidence in adapting to various situations (Iorio et al.,
2022). Ultimately, individuals equipped with strong soft skills become invaluable contributors
within any workforce. Therefore, our first focus must be on the acquisition of soft skills.
Acquisition of Soft Skills
Acquiring soft skills involves a blend of formal education, personal development, and
practical experiences. Karras (2022) emphasizes that schools play an essential role in helping
students develop workplace-relevant soft skills, and this acquisition should occur through
structured education and real-life practice (p. 42). While formal education is critical, Karras also
highlights the importance of real-life experiences. According to Khasanzanova (2017), engaging
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in volunteer work, employment, and social interactions serves as an effective way to develop soft
skills. Volunteering, in particular, offers a lower-stakes environment to practice these skills,
enhancing both personal and professional development (Khasanzanova, 2017, p. 367). Both
formal and informal methods are essential in acquiring soft skills, and once developed,
individuals must continue refining these abilities.
Soft Skill Development
The development of soft skills must occur in order for these skills to be ingrained into a
person's arsenal of readily available skills, but how are soft skills developed? Soft skills are
developed through experiential learning, social interactions, education, and training. They are
also developed through self-reflection and feedback, volunteering and community engagement,
and workplace exposure. Through continuous practice, exposure, learning, and reflection, soft
skill development and refinement will occur.
Khasanzyanova (2017) argues that soft skills are primarily developed through
experiential learning in non-formal settings, such as volunteering and other lower pressure work
situations. Through experiential learning by volunteering, Khasanzyanova (2017) emphasizes
that these activities provide a context in which individuals can practice and develop essential soft
skills in a “learning by doing” method (p. 373). Khasanzyanova (2017), shows that student
volunteers consciously reflect on the skills that are acquired through this volunteer work. This
conscious reflection and hands-on involvement allow young people to apply theoretical
knowledge in practical settings, which will allow them to transfer these skills more organically to
complex social issues and professional scenarios (p. 371). Khasanzyanova (2017), imparts that
this type of learning is more impactful than just school learning because it involves adaptation,
problem-solving, and self-management in unpredictable real-world contexts (p. 375). In essence,
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action and practice in combination with experiential learning are crucial in soft skill
development.
Not only do hard skills and soft skills vary based on definition but also how they are
taught. According to Barth et al. (2023), there is a distinct difference in how hard and soft skills
are taught. Hard skills are generally taught in a structured, technical environment with clear
objectives and very specialized training. This task-oriented training focuses on procedures and
includes skills such as operating machinery, managing software, or anything that is based on
specific tasks or algorithms with the specific outcome being the transfer of this knowledge from
the teacher to the student (pp. 236-237). The method or pedagogy of transferring hard skills is
best done through a constructivist and transmissive approach, meaning that that participants must
set a transfer goal while the teacher must ensure these transfer goals are met and to anticipate
possible implementation difficulties associated with the process (Barth et al., 2023, p. 238). In
contrast, soft skills require a more nuanced approach to teaching because these skills are less
directly transferable and much more context-dependent. Whereas hard skills require specialized
training with clear objectives, soft skill transfer requires methods such as observational learning,
feedback, and reflection. By utilizing these strategies, soft skill concepts can be internalized and
students will be much more able to apply the soft skills flexibly in unpredictable situations. The
design of this intentional transfer must incorporate opportunities for participants to reflect on
their experiences, receive feedback, and set personal goals for the application of soft skills in
different contexts (Barth et al., 2023, p. 248). The teaching and transfer of soft skills is much
more complex and dynamic than the teaching and transfer of hard skills. This leads to how one
must assess soft skills in the teaching and transfer of the skill.
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Soft skills, unlike hard skills, can only be observed by a critical observer. Therefore, soft
skills are assessed through behavioral assessments that measure the students’ abilities to apply
these skills in practical settings. In research completed by Tran et al. (2024), “Multiple Mini
Exams” or MME allowed for the assessment of soft skills (p. 2). MME are conducted where
students participate in role-play simulations like hypothetical patient interactions that were
recorded and scored based on the following criteria: Communication, bedside manner, and
teamwork. This approach to the assessment of these specific soft skills allowed the evaluators to
observe and score the soft skill transfer in a controlled and realistic environment. This provided
for a very practical assessment of the desired soft skills that are generally difficult to quantify
(Tran et al., 2024, p. 12). Assessing soft skills is typically done with subjective measures;
however, this study was able to quantify the subjective measures in order to ensure an objective
approach to soft skill acquisition. In the study by Tran et al. (2024), the review of the videotaped
simulations involved a detailed, rubric-scored process. This process involved two reviewers
watching the video recordings of the students role-playing in patient care scenarios and assessing
the students’ performance using a rubric with specific criteria for each of the following soft
skills: Obtaining background, bedside manners, and use of scientific and medical language (p.
12). The specific criteria for assessing these soft skills were determined collaboratively with
input from the course instructor to ensure alignment with learning objectives. In developing the
rubric, the researchers identified essential skills from the Association of Medical Colleges for
prospective medical students. The rubric was structured to provide clear, measurable indicators
for each skill which facilitated consistent and objective scoring during video review (Tran et al.,
2024, p. 2). Based on this specific research study, the importance of objectively assessing soft
skills cannot be understated in the acquisition and development of soft skills. While acquiring
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and developing soft skills are important to the workforce, it is incumbent upon the education
system to teach soft skills in order to promote a workforce that is equipped to handle the
challenges of tomorrow.
Teaching Soft Skills
The research offers various methods for teaching soft skills effectively and methods to
create best practices in soft skill education. One of these methods includes the Soft Skills
Training Program. Sutil-Martin and Otamendi (2021), created the structured Soft Skills Training
Program that uses “serious games” to help young students develop essential soft skills (pp. 3-4).
This specific program targets intrapersonal, interpersonal, personal social responsibility, and
organizational sustainability skills through gamified learning experiences. This educational
approach emphasizes experiential learning, where students engage actively in scenarios that
promote the development of soft skills critical for the workplace. The Soft Skills Training
Program also includes a pre and post training assessment to ensure objective improvement in the
desired areas that ensure the program’s effectiveness (Sutil-Martin & Otamendi, 2021, pp. 4-5).
This program is structured on and targets four broad categories of soft skills:
Interpersonal, intrapersonal, personal social responsibility, and organizational sustainability.
These skills are known in the program as the Four MacroSoftSkills. Each of the Four
MacroSoftSkills are divided into eight categories of soft skills known as MesoSoftSkills:
Self-knowledge, self-management, empathy, influence, strategic mindset, consciousness,
compassion, and morality. The MesoSoftSkills are then further subdivided into 21
MicroSoftSkills: Academic self-concept, emotional self-concept, social self-concept, family
self-concept, physical self-concept, volatility (emotional stability), withdrawal (self-control in
discomfort), adopting perspectives, understanding emotions, assertiveness, openness,
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industriousness, orderliness, kindness, common humanity, engagement, indifference, separation,
disengagement, idealism, and relativism (Sutil-Martin & Otamendi, 2021, pp. 6-7).
These skills are observed while students in the program play “Serious Games as Training
Tools.” These tools incorporate a variety of serious games, including gamestorming and
boardgames to engage participants in active learning. These games are tailored to develop each
skill level and are designed to be interactive and to promote behavioral change through
experiential learning. These games include Paradoxical Thinking, Emotions, Growing in
Mindfulness, Trust, Ikigai, Planning by Scenarios, and Compassion and Morality. This approach
is reinforced by a structured appraisal system that measures soft skill improvements over the
course of the program (Sutil-Martin & Otamendi, 2021, pp. 8-10). These tenets together create a
comprehensive framework that combines theory, measurement, and practice that makes the Soft
Skills Training Program a robust tool for fostering and assessing essential soft skills for the
modern workforce.
When evaluating the effectiveness of soft skills instructional programs, you should
address students’ perception of soft skills training programs. According to a study conducted by
Laari and Dube (2017) on nursing students’ perceptions on their soft skills training, soft skills
training is seen as highly valuable by 68.8% of respondents (p. 1). These respondents perceive
that soft skill training is highly valuable for their professional development and essential for
consistently delivering high quality patient care. The majority of students in the study recognize
that formal training in the soft skills that are specific to their profession would improve their
interactions with patients and colleagues. These students agreed that soft skills training should be
integrated into their nursing curriculum in order to enhance their clinical performance, make
them more compassionate caregivers, and help to address the gap in interpersonal skills that
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currently affects patient satisfaction and trust in healthcare (Laari & Dube, 2017, pp. 4-5). This
study shows that students see the benefit in soft skill training and acquisition. Teaching soft skills
will ensure that our students are prepared to handle the challenges of tomorrow, but which soft
skills are most important to be taught? In order to determine which soft skills our business
leaders find valuable, they must be provided with a list and description of pre-identified soft
skills.
Pre-Identified Soft Skills
Soft skills play a critical role in preparing students to sustain and enhance the local
workforce, equipping them to adapt alongside technological advancements. Given the broad
spectrum of soft skills, it is essential to identify those most relevant to the local workforce. A
study by Richie et al. (2022) identified key soft skills, categorized into three main areas:
Individual, collaborative, and procedural skills. Individual soft skills are working under pressure,
innovative problem-solving, integrity, empathy, and emotional intelligence. Collaborative skills
are communication, teamwork, global and cultural diversity, leadership skills, and professional
etiquette. Procedural skills are quantitative skills, flexibility, critical thinking, decisiveness, and
responsibility to complete tasks effectively (Richie et al., 2022, pp. 163-165). These skills
provide a foundation for programs that align with the needs of local employers.
Individual Skills
Individual soft skills refers to personal attributes and competencies that enhance an
individual’s ability to perform effectively and responsibly in a professional setting and are
essential to individually navigate workplace challenges and expectations. Developing these skills
enables a person to manage stress, make sound decisions, and maintain professionalism which
are foundational for personal success in any job role.
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Working Under Pressure
The first individual soft skill is working under pressure. Time management is the ability
to plan and organize priorities for work activities. Working smarter is an enabler to accomplish
more in less time without having to work harder. When time pressures are high, lack of time
management causes stress and reduces effectiveness (Vasanthakumari, 2019, p. 69).
Innovative Problem Solving
The next individual soft skill is innovative problem solving. This soft skill deals with
activities related to the job position and new ideas for improvements related to products and
services offerings provided by the organization (Succi & Canovi, 2019, p. 1835).
Integrity and Empathy
After innovative problem solving, there is integrity and empathy. According to Van
Deuren (2018), empathy and integrity are closely linked in fostering a strong values-driven
approach in the workplace. Empathy allows individuals to understand and respect the emotions,
perspectives, and needs for others. This is essential for effective teamwork, leadership, and
conflict resolution. On the other hand, integrity emphasizes honesty, ethical behavior, and
accountability (Van Deuren, 2018).
Emotional Intelligence
The last individual soft skill is emotional intelligence. Emotional intelligence is the
ability to recognize, understand, and manage one’s own emotions as well as the emotions of
others through self-awareness, self- regulation, social awareness, and relationship management
(Sadovyy et al., 2021, p. 2). According to Allam (2011), emotional intelligence is why people
excel in performance over others with the same level of training and experience (p. 71). The
attributes of emotional intelligence helps individuals navigate complex social environments,
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make better decisions, and build positive relationships which contribute to career success and
higher levels of personal and professional satisfaction (Allam, 2011, p. 77). By fostering
individual skills, employees become more adaptable and capable of navigating workplace
challenges independently.
Collaborative Skills
The next grouping of soft skills is collaborative skills. Collaborative skills are essential
abilities that enable individuals to work effectively with others towards shared goals. In today’s
increasingly collaborative workplaces, the ability to communicate clearly, to show empathy, and
contribute effectively to a team’s success is highly valued.
Communication
The first collaborative soft skill is communication. Communication is engaging in clear
and effective exchanges, both verbally and non-verbally, that are crucial for team success. All
employers place a priority on how an employee interacts with others, takes initiative, and
demonstrates the ability to achieve results. Skills related to business communication also include
traits that professionals use to convey information in the workplace. These skills are broad and
include active listening to use in negotiations or networking. Team collaboration includes giving
and receiving clear and succinct feedback to encourage creative thinking. Constructive feedback
supports reflective thinking and improvement (Valera, 2020, p. 190).
Teamwork
The next collaborative soft skill is teamwork, which is working collaboratively to support
group efforts, fostering trust and unity among team members. Phillips et al. (2020) identify
teamwork as a critical soft skill for employees at any level, to recognize the need for a mindset to
support the larger mission of the organization (p. 59). Attributes include coordinating,
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cooperating, and collaborating with others to build trust (Harlow, 2022, p. 47). Assisting team
members orchestrates the interdependent actions of motivation to evaluate the team’s mission.
Global and Cultural Diversity
Next, global and cultural diversity embraces diversity by recognizing and valuing
different cultural perspectives, which will ultimately enhance creativity and innovation within
teams. According to Florentine (2019), when diversity is present in the workplace, it sets the tone
for better performance. The risk of being publicly called out for lack of diversity in recruiting is
one way to lose competitive advantage. Companies are increasing their focus on diversity in the
workplace to avoid having a tarnished reputation.
Leadership
The next collaborative soft skill is leadership which is guiding and motivating others
towards common goals, often involving responsibility and influence. Leadership skills include
general personality traits such as self-confidence, enthusiasm, assertiveness, extraversion,
authenticity, trustworthiness, humility, and a sense of humor.
Business Etiquette
The last collaborative skill is business etiquette which is adhering to professional norms
and respectful interactions which maintain a respectful and productive work environment.
Collaborative skills enhance an employee’s ability to build positive working relationships,
resolve conflicts, and work productively with others, which are critical for achieving collective
goals and fostering a healthy work culture.
Procedural Skills
The last grouping of soft skills is procedural soft skills. Procedural soft skills are defined
as those skills needed to perform tasks or complete processes within an organization. Procedural
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skills help employees carry out tasks, adhere to organizational procedures, and apply analytical
thinking to make informed decisions. These skills are crucial for operational success and help
individuals navigate and fulfill the requirements of dynamic work environments (Richie et al.,
2022, p. 169).
Quantitative Skills
The first procedural soft skill is quantitative skills. This category of professional skills
involves reasoning and understanding numerical data to solve problems and make decisions.
Quantitative skills in fields such as health care, financial services, or manufacturing may indicate
the ability to conduct research and examine efficiency results, in addition to other numerical data
for decision making (Wilton, 2014, pp. 5-6).
Flexibility for Organizational Change
The next soft skill in this grouping is flexibility for organizational changes. This soft skill
focuses on the ability to adapt to shifts within an organization and demonstrating the ability to
adjust to tasks and priorities as needed. Depending on the position, the ability to accomplish
tasks that are dynamic and changing indicates the potential for high performance.
Critical Thinking
The next procedural soft skill is critical thinking which is the capacity to analyze
information, think logically, and approach problems systematically. After critical thinking, the
next skill is the ability to make decisive decisions which is being able to evaluate options and
make informed decisions in a timely manner. Considering alternative solutions will support the
cognitive process of a belief, or course of action based on several alternative options
(Vasanthakumari, 2019, p. 70). The pros and cons for each solution should match the course of
action related to the nearest desirable outcome. At a personal level, it is important to be focused
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only on the factors within the scope of control and recognize the factors outside the control for
decisions (Phillips et al., 2020, p. 59).
Responsibility to Get the Job Done
The last procedural soft skill is the responsibility to get the job done which is a
commitment to completing tasks reliably and effectively which includes being able to manage
time and ensure follow-through. Applying work habits such as maintaining wellness, time
management, follow through, and initiative creates the ability to contemplate information and
skill development (Phillips et al., 2020, p. 59). One example is the ability to determine the range
of tasks to organize and manage teamwork to achieve the desirable outcomes (Gruzdev et al.,
2018, p. 692). By focusing on procedural skills, employees can improve their efficiency and
reliability in job roles that require adherence to processes and problem-solving under varying
circumstances, making them valuable assets to organizations.
By structuring a soft skills program around the categories of individual, collaborative,
and procedural skills, the program can address a holistic set of competencies that support both
individual development and organizational success. This approach will ensure that employees
who enter the workforce from the West Greene School District are well-rounded, adaptable, and
prepared for diverse working demands that are aligned with educational outcomes from the
competencies that local employers deem essential. While the acquisition, development, and
teaching of soft skills are vital to understanding the process of learning soft skills, it is also
vitally important to understand why the workplace and workforce economically benefits from
employees with developed soft skills.
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Soft Skills in the Workplace and their Economic Impact
In the modern workplace, the demand for soft skills has steadily grown over time driven
by the evolution of the workforce and changes in job roles across various industries. Soft skills
are increasingly viewed as essential complements to technical skills that drive long-term career
success, productivity, and economic growth across sectors. According to Börner et al. (2018),
while the demand for technical skills is still very high, the rise of data-driven and collaborative
work environments has led to a much needed influx of workers with specific sets of soft skills (p.
12360). As automation and artificial intelligence begin handling more routine, technical tasks,
employers will need to seek employees who excel in interpersonal and cognitive skills that
cannot be replicated by machines or algorithms. Börner et al. (2018), also argues that as technical
roles grow more specialized, professionals who have a strong set of foundational soft skills to
collaborate across the boundaries of technical disciplines who can manage projects and
effectively convey technical information to non-specialists are in great demand (p. 12637). The
economic trends dictate the increased relevance of providing a soft skills curriculum in our
schools.
When examining the need for soft skills in the workplace, it is important to look at the
economic value that soft skills bring not only to an individual, but also to specific economic
sectors. In terms of individual career advancement, Tsalikova and Pakhotina (2019) argue that
professionals equipped with industry specific soft skills are better prepared to navigate complex
work environments and handle the diverse challenges of specific industries (p. 196). These skills
are essential for maintaining productivity and fostering positive workplace environments which
are both essential skills that are critical for individual career advancement. Possessing soft skills,
both a broad range and specific to an industry, make a person more resilient and capable of
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achieving sustainable career growth, even in rapidly changing industries (Tsalikova & Pakhotina,
2019, p. 191).
Soft skills that have been internalized by an individual can lead to individual economic
growth in career advancement, but on the other hand, a workforce that has employees trained in
industry-specific soft skills, provide economic value to those specific industrial sectors. For
example, the healthcare sector emphasizes soft skills such as empathy, communication, and
teamwork because these specific soft skills are essential for patient interaction, collaboration
with medical staff, and effective patient care. In the engineering and technology fields, soft skills
like problem solving, adaptability, and communication in multinational and interdisciplinary
settings where professionals need to explain complex ideas to a diverse audience are of the
utmost importance. The economic sectors of hospitality and tourism value interpersonal skills,
customer service, and emotional intelligence in order to manage customer interaction and to
ensure client satisfaction in high customer contact environments. Finally, sectors such as
information systems and security prioritize critical thinking, collaboration, and communication
because people working in these sectors address complex security issues working with
cross-functional teams (Tsalikova & Pakhotina, 2019, pp. 193-195).
The economic need for soft skills is growing exponentially by the minute with
automation and artificial intelligence. According to Rodriguez-Bustelo et al. (2020), automation
is expected to transform the workplace by significantly altering the types of skills in demand and
the nature of the jobs that will be coming available to the next generation of worker (pp. 1-2). As
automation and artificial intelligence technologies continue to advance, many routine and
predictable tasks are at a high risk of becoming automated. Unfortunately, this shift will
disproportionately impact blue collar jobs. On the other hand, there will be a rise in demand for
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roles consisting of soft skill rich abilities. Workers will need to adapt to this growing trend in
order to thrive in roles that cannot be replicated by machines or automation. This will require a
shift in the educational programs that produce the workers of tomorrow in order for the next
generation of workers to not be supplanted by automation or artificial intelligence
(Rodriguez-Bustelo et al., 2020, pp. 2-4). Therefore, technology will increase the importance of
workers with unique human skill sets possessing soft skills. Börner et al. (2018) explain that as
data-driven tools and artificial intelligence handle routine and specialized hard skills, the demand
for humans with industry specific soft skills will rise (p. 12635). Since managing interpersonal
relationships and applying data insights to real life and dynamic situations that cannot be
automated at this time, employees who can effectively collaborate and innovate in response to
changing demands, underscoring the enduring value of soft skills in the economy, will thrive at a
rate much higher than those who do not possess them (Börner et al., 2018, p. 12637).
In addition to a general need for soft skills in the workplace, there are tangible economic
returns from incorporating a soft skills training program to an employer’s workforce. According
to Adhvaryu et al. (2023), the economic returns of soft skills can be substantial, particularly in
productivity and cost-effectiveness for employers (pp. 2168-2169). In a study on garment
workers in India, Adhvaryu et al. (2023), found that workplace soft skills training improved
productivity by 13.5%, largely due to enhanced teamwork and collaboration (p. 2165). This
increase in productivity resulted from a large investment in soft skill training leading to a large
return on their investment of 256% in just eight months post-training. This study underscores
that the contribution of soft skills training on garment workers in India increased their
contributions and therefore promotion potential making them economically valuable (Adhvaryu
et al., 2023, pp. 2167-2169). Individuals with well-developed soft skills are more employable to
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work with and tend to have higher earnings. Employers value soft skills, especially for roles
requiring adaptability, teamwork, and customer service. This employability advantage helps
workers access better jobs and income, which will positively impact household economic
stability (Adhvaryu et al., 2023, p. 2166).
Workplace culture is very important to maintain a good work-home life balance. In fact,
according to Mennino et al. (2005), workplace culture affects employees’ ability to balance work
and family life. The study suggests that supportive and modern workplace cultures are essential
for reducing work-family conflict, highlighting the need for new ideas to improve workplace
culture (p. 21). Among many other factors that impact workplace culture, communication,
collaboration, and teamwork are key factors that create a workplace culture that creates a good
work-home life balance (Mennino et al., 2005, pp. 21-22). If workplaces have training programs
or if employees enter the workforce with these soft skills, workplace dynamics will be improved.
Since it is important for workplace dynamics to be positive for the sake of its workers, it
is important to look at key dynamics and the soft skills that are associated with them in order to
determine which soft skills have the most impact on a positive work culture. In a study
conducted by Sandlin, et al. (2018), the authors studied student perceptions of their performances
in team-based projects (p. 21). The study used the DISC Behavioral Style Assessment to
determine and understand students’ behavioral tendencies and how they influence team
interactions. The study concluded that teams with less compatible styles experienced more
challenges in cohesion. In addition, as students reflected on their ability to adjust their behavioral
styles to accommodate the team’s needs, students ascertained that adapting their behavioral style
will improve collaboration and communication (Sandlin et al., 2018, pp. 25-27). Therefore,
students who not only are aware of their strengths and weaknesses, but can also adapt their soft
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skills to the situation, will have a better work-life balance and live a happier existence. Since the
COVID-19 pandemic, the workforce composition has changed in terms of where people are
reporting to work. Therefore, it is integral to understand how soft skills impact the workforce if
the workforce is working from home.
Soft Skills and Working From Home
If the COVID-19 pandemic has taught us anything, it has taught us that we must be
prepared for a changing workforce at a moment’s notice. As the workforce continues to evolve as
a result of the pandemic, our hard and soft skills must evolve as well. The pandemic has created
a need for employees who are trained in different soft skills than before. With the shift to remote
work, employers are now looking for candidates who are adaptable, able to communicate, and
problem-solve. These skills have always been sought after by employers, but the shift to working
at home has intensified this need.
Ferreira et al. (2023) define the skill gap as the disparity between the skills that
organizations need for effective operation and those currently possessed by employees (p. 39).
The authors of this study surveyed employers and their satisfaction in their employee’s skills and
the importance of the skills. The outcome was that employers identified a gap between the
availability of problem-solving skills, adaptability, and communication in their employees.
(Ferreira et al. 2023, p. 42). In an effort to bridge this gap, Ferreira et al. (2023), found that
employers, especially in digital marketing and advertising provided training for these skills (p.
39). While remote working poses challenges to these training programs, the requisite soft skills
must be trained in order for a productive workplace to be maintained. Employers have begun
training on interpersonal skills, communication, emotional intelligence, and teamwork which are
all skills that need to be developed for the “new normal.” Training in those workplaces occurred
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in the form of online workshops and structured interactions designed to build communication
and collaboration skills across their virtual departments (Ferreira et al., 2023, p. 43).
The COVID pandemic has impacted the importance of social skills in the workplace. In
addition to changing what the workforce looks like, the pandemic has also changed the relevance
of specific soft skills in the workplace and the shift in working conditions could lead to a social
soft skill deficits that negatively impact productivity in certain sectors across demographic
groups (Gnecco et al., 2024, p. 647). These deficits could potentially lead to decreased
productivity and inefficiency in the workplace. Therefore, it is incumbent upon the schools to
adapt to these needs.
Gnecco et al. (2024), argue that the pandemic and shift to a virtual workplace in certain
sectors has led to skill deficits in the following soft skills: Empathy, coordination, teamwork, and
communication because of limited opportunities for direct social interactions, which are crucial
for team cohesion and effective collaboration (p. 653). Furthermore, certain age groups and
sectors were more affected than others. Workers under the age of 35, and sectors such as tourism,
commercial activities, and education show the greatest skill gaps. These skill gaps could
potentially lead to ongoing challenges in productivity and team dynamics which could impact
overall workplace morale and long-term organizational success if intentional skill-building
initiatives do not take place (Gnecco et al., 2024, pp. 650-677).
The pandemic and the move to remote working has increased the importance for social
soft skills like empathy, adaptability, and effective communication. These skills were once seen
as supplemental to traditional learning, but the changes in the workforce have taught us
differently. In addition, this shift has shown us that there are going to be persistent skill deficits
in certain sectors like tourism, education, and commercial services and that younger workers
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have been particularly impacted in the workforce by their lack of soft skills. In order to address
these skills deficits, it is clear that we must take a targeted approach to soft skills acquisition at
the primary and secondary levels of education, but also employers must develop their own soft
skills training program in order to increase productivity and to reduce the impact of the
pandemic-induced changes.
A common theme in addressing soft skills is addressing how soft skills have an impact on
workplace culture, and by extension, the mental health of the employee. With remote work
becoming more and more prevalent in our economy, the mental health of employees working at
home must also be addressed along with the soft skills at work to address mental health.
Working remotely is a new fold to our economy that does not come without its own
stressors. Remote workers experience more work-family conflicts because of the overlap of
personal and professional environments that lead to more frequent interruptions and more
challenges in balancing work and home responsibilities. This conflict is often heightened from
the employee working long hours with blurred work-home boundaries. Remote workers also
experience more isolation and burnout due to limited face- to- face interactions with colleagues.
This can contribute to feelings of loneliness and reduced social support. This isolation, coupled
with larger workloads has been associated with increased risk of burnout amongst some remote
workers (Andrade et al., 2024, p. 8). In addition, according to Andrade et al. (2024), there was a
significant prevalence of insomnia among remote workers at their 12 month follow- up (p. 1).
The disrupted work-life balance and increased stress from working in a home environment
without clear separation of personal and work time contributes to sleep disturbances and anxiety.
The findings of the study suggest that while remote work can offer protective benefits by
reducing certain physical stressors, it also introduces unique challenges for the remote worker.
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Fortunately there are ways to reduce these stressors in the in-home workplace, soft skills
training. According to Winarsunu et al. (2023), “life skills” training is described as a training
program that they have designed to improve individuals’ abilities in several skill areas (p. 1). The
skills that the authors allude to as “life skills” are soft skills. The soft skills they argue are critical
to reducing anxiety are decision making and problem solving, critical thinking, communication,
self-awareness, empathy, and coping skills (Winarsunu et al., 2023, p. 2). The purpose of their
study is to identify which soft skills help reduce anxiety in the remote workplace.
Winarsunu et al. (2023) argue that decision making and problem solving skills help
individuals make informed decisions and to solve everyday challenges effectively (p. 4). The
authors also argue that critical thinking can enhance an individual’s ability to think innovatively
and evaluate situations critically. Communication skills aid in improving verbal and non-verbal
communication that fosters positive interaction and builds stronger interpersonal relationships.
Self-awareness and empathy encourage individuals to develop a deeper understanding of
themselves and empathy towards others, while coping strategies help a person manage stress and
to regulate emotions in a healthy way (Winarsunu et al., 2023, pp. 5-6).
In conclusion, the COVID-19 pandemic has highlighted the need for stronger
management and training of soft skills in the workplaces, especially the remote workplace. Skills
like adaptability, empathy, communication, and stress management have become essential for
worker productivity and mental well-being. To bridge the gap, employers and academic
institutions must prioritize soft skills training to prevent burnout and isolation to foster a
healthier and more resilient workplace. In transitioning from soft skills, it is important to have a
basic understanding as to why our district is focusing on soft skills acquisition and its benefits for
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the workplace. In helping the reader understand this, it is valuable to understand the economic
outlook for our graduates in Greene County, Pennsylvania.
Current and Projected Job Outlook of Greene County
Greene County, Pennsylvania currently employs just more than 14,200 people. The
largest industries in Greene County, Pennsylvania, are health care and social services employing
around 2,640 people, retail trade which employs around 1,538 people and educational services
which employs around 1,322 people. Whereas these are the industry sectors that employ the most
people, the highest paying industries in the County are real estate & rental leasing paying around
$93, 214 on average and agriculture, forestry, fishing & hunting, and mining which pays around
$86, 118 on average (Data USA, 2024). These sectors alone account for 39% of the overall
employment in the county. While there are some sectors in the county that are thriving, the
Greene County Industrial Development Authority (GCIDA) is attempting to grow the economy.
The mission of the GCIDA's focus is on the creation, attraction, and retention of
businesses in Greene County, Pennsylvania. This department offers financial assistance through a
variety of loan programs and technical assistance to expand business opportunities throughout
the county through assistance for manufacturing and distribution investors interested in site
locations for new and expanding operations. This Authority offers money loan services through
their Revolving Loan Fund and Emergency Loan Program. The Emergency Loan Program offers
up to $50,000 dollars for 15 years at 1% to help local industries grow. The GCIDA works with
Waynesburg University and the University of Pittsburgh’s Institute of Entrepreneurial Excellence
to improve its outcomes. The GCIDA also provides resources to potential industrial developers
to aid in their search for economic development agencies, Greene County Realtors, the
Pittsburgh Regional Alliance, and GIS planning (Greene County, 2024).
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The GCIDA has several ways that it can help local students in the workforce. This
Authority could partner with local businesses, Waynesburg University, and the University of
Pittsburgh’s Institute of Entrepreneurial Excellence to create internship opportunities for local
students. In addition, it can organize tours of local industrial sites to expose students to local
career paths. The GCIDA could also work with its university partners to offer workshops for our
students interested in starting their own business. This partnership could also set the student up
with youth business grants to finance the ideas of our young entrepreneurs. However the GCIDA
could work with our students as a benefit to the local economy and our school as a liaison
between the school and industry. This will be needed to further the opportunities for our
graduates because the competition for jobs will only increase as the economic outlook of Greene
County, Pennsylvania changes.
The Economic Outlook of Greene County, Pennsylvania
In order to project an area’s real GDP, economists suggest using the following formula:
real GDP at starting date x (1+Growth rate of real GDP)Years (Mankiw, 2020, p. 489). It is
important to use real GDP because real GDP is adjusted for inflation. In addition, a ten year
projection is being used because if a five year projection is used, the recession from the COVID19 Pandemic will skew the results. The most recent real GDP calculation is from 2022, which is
$3,092,532. To project 10 years in the future, the real GDP from 2012 will be used which is
$3,052,491 (Regional Economic Analysis Project, 2024). Therefore, the projected GDP of
Greene County, Pennsylvania, in 2032 is: $3,092,532 x (1+ ($3,092,532-$3,052,491)
/$3,092,532)10= $3,517,095.69 real GDP. This incremental growth over the last decade implies a
stable economic base with no significant declines, but it also points to limited diversification or
expansion into high growth sectors. Based on this data, the local economy could benefit from
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targeted interventions to accelerate growth and capitalize on emerging opportunities. Our school
could be a hub to drive this innovation through soft skills training programs because compared to
the United States, Greene County, Pennsylvania needs to keep pace.
Demographics of Greene County, Pennsylvania
Greene County, Pennsylvania, is located in the southwestern most corner of
Pennsylvania. Greene County, Pennsylvania, boasts a population of 35,800 people, ranking it
58th out of Pennsylvania’s 67 counties (Data USA, 2024). Greene County is home to five public
school districts: Carmichaels Area School District, Central Greene School District,
Jefferson-Morgan School District, Southeastern Greene School District, and West Greene School
District. For the purposes of this capstone research project, the researcher will discuss important
demographics that pertain to the five school districts of Greene County, Pennsylvania, with a
specific focus on the West Greene School District. Not only will the researcher discuss
population demographics, but also economic demographics, as they are critical in understanding
the population of Greene County, Pennsylvania, and more specifically, the West Greene School
District
Economic Demographics of Greene County, Pennsylvania
Greene County, Pennsylvania’s economy is centered around mining and natural
resources, government, education, healthcare and social assistance, and retail. The economy,
having little diversity, still has a need for workers as the economy of Greene County,
Pennsylvania grew about 0.5% by roughly adding 100 jobs between 2021 and 2022 (Data USA,
2024). With an unemployment rate of 5.2%, there is little room for graduates of Greene County
schools to fit into the local economy (U.S. Census Bureau, 2024c). According to Data USA
(2024), roughly 18% of the Greene County, Pennsylvania’s economy is focused on healthcare
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and social assistance which grew around 8% in 2022. The fastest growing industries in the
county are finance, which grew 25%, and insurance and educational services, which grew 21%
(Data USA, 2024). While the economic growth of Greene County’s industries is relatively
stagnant, Greene County schools are still graduating students who need to find their way into
these industries. The subjects of this study, the industries being surveyed, are the top ten
employers in Greene County, Pennsylvania, in terms of the number of employees the business
employs, who are willing and able to complete the survey. These industries, listed in Appendix
A, are the backbone of the economy of Greene County, Pennsylvania.
Families of Greene County, Pennsylvania, have a median household income of $66,283
with property values hovering around $140,900, which is nearly half of the national average. In
addition in 2023, nearly 9% of Greene County’s population was living with severe housing
problems and almost 13% of the population currently lives below the poverty line (Data USA,
2024). As shown in Table 1, the rate of poverty in the county is exemplified by the percentages
of students who receive free and reduced lunch. The economic strain on Greene County residents
significantly impacts the local economy because small businesses have difficulty thriving,
leading to a diminished market of entrepreneurs and startups because of the ever increasing
poverty level and disposable income of the region. Whereas the bleak economic outlook of the
county presents great challenges, it also offers a great deal of promise for something better for
students entering into the job market who, with job ready skills, can help grow the economy.
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Table 1
Greene County Schools Free/Reduced Lunch Figures
School District
Percentage
Carmichaels Area School District
53.7%
Central Greene School District
51.1%
Jefferson-Morgan School District
54.6%
Southeastern Greene School District
West Greene School District
49%
55.6%
Note. Explanatory Note (Pennsylvania Department of Education, 2024a-e, Future Ready PA
Index)
Comparing the Job Market of Greene County, Pennsylvania to the United States
When comparing job markets, it is important to first compare unemployment rates. The
unemployment rate in the United States is 4.1% while the rate for Greene County, Pennsylvania
is 5.2% as noted previously (U.S. Bureau of Labor Statistics, 2024). The largest industries by
GDP in the United States are hospitals; health and medical insurance; commercial banking, drug,
cosmetic, and toiletry wholesaling; pharmaceuticals wholesaling; new car dealers; life insurance
and annuities; public schooling; property, casualty, and direct insurance; and retirement and
pension planning (IBISWorld, 2024). When comparing the United States’ economy with that of
Greene County, Pennsylvania, the lack of diversity and dependence on traditional economic
sectors in the Greene County economy highlight the need for strategic partnerships between the
local schools and the local employers. These strategic partnerships would focus on aligning
education and training with emerging and stalwart industries to ensure the economic vitality of
the region.
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Demographics of Greene County, Pennsylvania Schools
Student enrollment is a demographic marker that is indicative of potential future
employees to the businesses of Greene County. Graduates remaining in the region are essential
for the economic stability of Greene County, Pennsylvania. Therefore, it is important to know
how many potential future employees exist in the county. Table 2 lists the enrollment numbers
for each district since the 2020-2021 school year. As the schools in Greene County continue to
graduate students into the local job market, students in Greene County face additional
competition from 5.2% of the population, the unemployed population, of Greene County (U.S.
Census Bureau, 2024c). Approximately 6.8% of Greene County is nearing retirement age, the
students of Greene County must be highly marketable to employers in Greene County (U.S.
Census Bureau, 2024a).
Table 2
Greene County Schools Enrollment Figures
School District
School Year
2020-2021
2021-2022
2022-2023
2023-2024
Enrollment
Carmichaels
Area
997
989
961
968
Central Greene
1505
1487
1510
1443
JeffersonMorgan
773
776
792
779
Southeastern
Greene
549
587
580
580
West Greene
643
646
674
649
Note. Explanatory Note (Pennsylvania Department of Education, 2024f, Public school
enrollment reports)
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In order for the economy of Greene County, Pennsylvania, to thrive it needs highly
skilled and competent workers to fill jobs. Therefore it is important to understand the number of
graduates potentially entering into the workforce from the Greene County schools. To project
future enrollment numbers for each school district, it is important to examine from Table 3 the
total population numbers of each school district over the last four years in addition to each
school’s enrollment figures from Table 2 in order to predict the future enrollment of each school.
These numbers are based on the 2020 Census Data and will enable the researcher to create a
student population to overall population ratio. These ratios identified in Table 4 are completed
for 2020, 2021, 2022, and 2023. Extrapolation is a projection technique that uses aggregated data
from the past to project into the future. When making population projections, past and current
census information is used to project future population size. Extrapolation is done under the
basic assumption that the characteristics of the more recent period of development for a locale
are expected to continue in the future (Measure Evaluation, n.d.). In order to extrapolate data for
the next two years, the researcher will use the most recent four years of historical data, as it can
be expected that the population will change at that rate (Measure Evaluation, n.d.).
Only using the rate of change from the last four years of student enrollment may not
create a reliable enough extrapolation. More reliable enrollment projections can be ascertained
by using the average historic ratio of student population compared to the overall population.
Table 3 lists each school’s total population from the last four years and their average change per
year. The average change per year is a critical aspect in calculating the ratio because it will allow
the researcher to extrapolate the total population of each district over the next two years as
shown in Table 5, by multiplying the average change per year percentage by the 2023 population
number and then adding the result to the 2023 population number to get the 2024 projection.
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This process will be imitated to determine the 2025 projection, using the 2024 projection as a
baseline. Table 4 identifies the desired ratio by dividing the past enrollment figures of each
school by its past total population of that year, thus establishing a ratio that can be used to make
proper extrapolations of enrollments for the next two years by using the average percentage of
the four years. Now that the ratio by percentage has been established in Table 4, the average ratio
by percent of Greene County School Districts’ enrollment to total population will be multiplied
by the population projection figures and added to that year’s population from Table 5 in Table 6.
Table 6 shows the enrollment projections for each school district based on the above
calculations.
Table 3
Greene County School Districts’ Total Population
School District
Census Year
2020
2021
2022
2023
Total Population
Carmichaels
Area
6706
6877
6830
6815
Central Greene
14892
14820
14741
14984
JeffersonMorgan
5327
5214
5266
5567
Southeastern
Greene
4685
4673
4583
4322
West Greene
4874
4664
4361
4266
Average Population Change
Carmichaels
Area
2020 to 2021
2021 to 2022
2022 to 2023
Average Change
2.55%
-0.68%
-0.22%
0.62%
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Central Greene
-0.48%
-0.53%
1.65%
0.21%
JeffersonMorgan
-2.12%
1.0%
5.72%
1.53%
Southeastern
Greene
-0.26%
-1.93%
-5.7%
-2.63%
West Greene
-4.31%
-6.5%
-2.18%
-4.33%
Note. Explanatory Note (United States Census Bureau, 2020a-e)
Table 4
Ratio by Percent: Greene County School Districts’ Enrollment to Total Population
School
District
Census Year
2020
2021
2022
2023
Average
Ratio by Percent
Carmichaels
Area
14.87%
14.38%
14.07%
14.20%
14.38%
Central
Greene
10.11%
10.03%
10.24%
9.63%
10%
JeffersonMorgan
14.51%
14.88%
15.04%
13.99%
14.61%
Southeastern
Greene
11.72%
12.56%
12.66%
13.42%
12.59%
West Greene
13.19%
13.85%
15.46%
15.21%
14.43%
Note. The ratio by percent is calculated by dividing Greene County School Districts’ Total
Population (Table 3) by Greene County Schools Enrollment Figures (Table 2) and multiplying by
100 for each year.
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Table 5
Population Projections
School District
Year
2024
2025
Carmichaels
Area
6858
6901
Central Greene
15016
15048
JeffersonMorgan
5653
5740
Southeastern
Greene
4209
4099
West Greene
4082
3906
Note. Population Projections are calculated by multiplying the average change per year
percentage (Table 3) by the total population and then adding the result to the total population to
get the current year’s projection.
Table 6
Enrollment Projections
School District
Year
2024
2025
Carmichaels
Area
987
993
Central Greene
1502
1505
JeffersonMorgan
826
839
Southeastern
530
517
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Greene
West Greene
590
564
Note. Enrollment Projections are calculated by multiplying the average ratio by percent of
Greene County School Districts’ enrollment to total population by the population projection
figures and added to that year’s population.
The data from the projections in Table 6 show that two of the five districts will lose
enrollment and the other three districts will maintain little growth, but growth none-the-less. This
data shows us that there will not be a large influx in the population of Greene County,
Pennsylvania schools. What is more troubling is that the West Greene School District will lose
the largest percentage of students in the county. This means that the West Greene School District
must make every effort to attract families by making the district stand out. One way the district
can generate an influx of population is by creating curricular change around soft skills that are
tailored to the economy of Greene County, Pennsylvania that make the West Greene School
District graduate a more desired commodity. Thus making the District a more marketable
resource for families looking for a change in their child’s education.
Graduate Preparedness of the West Greene School District
The West Greene School District consists of the entire western portion of Greene County,
Pennsylvania. The District spans a geographic area of 253 square miles and has on average 17.2
people per square mile (Census Reporter, 2024). The district has a total population of 4266, as
indicated in Table 3 and is projected to drop in 2025 to 3906 as indicated in Table 5. According
to Table 2, the District currently has 649 students enrolled and enrollment is projected to drop to
564 students in 2025, as indicated in Table 6. Based on the figures in Table 1, the district as a
whole has a free/reduced lunch percentage of 55.6%. This number is so high because the median
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household income is $66,258, which is about $4,000 less than the median household income of
Greene County as a whole and a whopping $11,000 less than the median household income of
Pennsylvania’s households (Census Reporter, 2024). Table 7 indicates that it takes the average
person living in the West Greene School District 28.2 minutes to drive to work. These
demographics signify the challenge that potential employees living in the West Greene School
District will face in an effort to participate in the local economy.
Table 7
Travel Time to Work
Travel Time
Percent of Population
Less than 10 Minutes
14.6%
10 to 14 Minutes
11.6%
15 to 19 Minutes
11.7%
20 to 24 Minutes
9.4%
25 to 29 Minutes
6.8%
30 to 34 Minutes
13.6%
35 to 44 Minutes
11.6%
45 to 59 Minutes
10.3%
60 Minutes of More
10.3%
Note. Explanatory Note (U.S. Census Bureau. 2024b. Greene County, PA commute data.)
The projected population and enrollment decline suggests a decreasing tax base which
may lead to reduced local revenue for the school district, thus impacting the West Greene School
District’s ability to maintain or improve educational services and infrastructure. A substantial
portion of the District’s population relies upon county, state, and federal programs to provide
assistance as evidenced by 55.6% of students qualifying for free and reduced lunch as denoted in
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Table 1. The high level of free and reduced lunch implies a sustained demand for governmental
assistance and reliance upon social programs. The District’s median household income of $62,
258, being much lower than the state median of $73,170 and county median of $66,283, suggests
limited discretionary income amongst residents (Data USA, 2004). This could lead to decreased
local spending which can negatively impact local businesses and economic vitality. In addition to
a lower median income, the population of West Greene School District often experiences
additional challenges such as increased commuting costs from driving longer distances to work,
as denoted in Table 7, which will further reduce the amount of discretionary income a family will
have for school related expenses which will further negatively impact school resources, and
increased family relocation as shown by decreasing enrollments in Table 6. All of these factors
not only impact the families of the West Greene School District, but also the resources that the
district will be able to provide to its students.
The West Greene School District cannot afford for its population to relocate upon
graduation. Graduates of the West Greene School District must take advantage of economic
opportunities in Greene County to increase the likelihood that they will stay and be productive
members of society and taxpayers in the West Greene School District. The students of the West
Greene School District face more than preparedness challenges when entering into the
workforce. One such challenge is the unemployment rate of Greene County, Pennsylvania, is
5.2%, so the graduates of the West Greene School District are not only facing competition from
people outside of the county, but also the unemployed in Greene County looking for economic
opportunity (U.S. Census Bureau, 2024c). Working with the workforce of Greene County, the
West Greene School District is committed to assisting its students to address not only the obvious
ARE OUR GRADUATES PREPARED?
43
economic challenges that students will face, but also address the skills deficit that might exist,
especially in the area of soft skills.
Summary
The demographics, economic landscape, and the workforce needs of Greene County,
Pennsylvania, particularly in the West Greene School District demonstrates the need for
something more to be provided for our students in order for them to be successful and
competitive in the Greene County economy. Facing declining population, limited job market
growth, and higher levels of poverty, the West Greene School District faces economic challenges
that impact both local businesses and employment opportunities. Therefore, students must be
equipped with the skills, particularly soft skills that focus on personal, collaborative, and
procedural competencies that are essential for adapting to dynamic workplace environments and
automation-driven challenges. Soft Skills are identified as crucial for career success and to
revitalize the local economy. To address these needs, experiential learning methods, such as
volunteering and interactive programs are effective ways to help students acquire these skills.
Through a well-structured curriculum, the West Greene School District will incorporate these
skills in fostering a more prepared and adaptable graduate which will enhance a student’s
employability and support economic growth within Greene County.
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44
Chapter III
Methodology
In many rural communities across the United States, schools are deeply intertwined with
the economic health and vitality of the region. This is especially true in Greene County,
Pennsylvania, where economic challenges such as a dwindling working-age population,
increasing poverty rates, and a stagnant job market have placed pressure on local institutions to
adapt and respond (U.S. Census Bureau, 2023). Unlike urban and suburban districts that benefit
from a more diversified tax base and broader economic opportunities, rural districts like the West
Greene School District must rely heavily on the economic contributions of local families and
homeowners to sustain operations. As such, ensuring that educational programming aligns with
the needs of the local economy is not simply a matter of curriculum design; it is a matter of
district survival. The purpose of these methods is to investigate how West Greene School District
can develop a strategic approach to preparing its students for local employment through the
identification and integration of essential soft skills as required by the county's top employers.
The purpose of this research is to determine which soft skills are most valued by the
leading employers in Greene County, Pennsylvania, and how the West Greene School District
can align its educational practices to meet these needs. While the implementation of a soft skills
curriculum is beyond the immediate scope of this study, the findings will serve as a foundational
step for district leadership in designing such a program. Specifically, this research aims to inform
the development of a soft skills curriculum aligned with the West Greene School District’s
Positive Behavior Interventions and Supports (PBIS) framework, and then ultimately embedding
these competencies into a profile of a West Greene graduate. This alignment is crucial in
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45
reversing trends of graduate outmigration and in fostering sustainable economic development
within the region.
To best achieve these goals, the research was conducted through a mixed methods
approach using a concurrent embedded design. The study surveyed the top ten employers in
Greene County, who were willing to participate, as identified by the Pennsylvania Department of
Labor and Industry Center for Workforce Information and Analysis. The goal of collecting data
from these employers was to gain a comprehensive understanding of the soft skills they prioritize
and to assess the extent to which these skills are currently being taught in the West Greene
School District. As automation and technological advancements continue to reshape the
employment landscape, employers are placing increased value on competencies such as
communication, adaptability, collaboration, and emotional intelligence (Iorio et al., 2022).
However, measuring these skills in a survey presents a significant challenge, and traditional
quantitative methods alone often fall short. To address this, the mixed methods design allowed
for the simultaneous collection of both quantitative and qualitative data, ensuring a nuanced and
holistic analysis. Quantitative data included responses regarding industry sectors, workforce size,
job projections, and rankings of soft skills, while qualitative data provided contextual insights
into the experiences and perspectives of local employers.
Ultimately, the goal of this research is to empower the West Greene School District with
the data and insights necessary to cultivate a workforce-ready graduate. As rural communities
continue to navigate complex economic realities, schools must play an active role in regional
development by ensuring that students are equipped not only with academic knowledge but also
with the practical, interpersonal, and problem-solving skills demanded by today’s employers.
Through strategic alignment with local economic needs, the district has an opportunity to not
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46
only enhance student outcomes but also to contribute meaningfully to the revitalization of
Greene County.
Purpose
The working age population of Greene County, Pennsylvania, and rates of poverty have
increased in a stagnant job market (U.S. Census Bureau, 2023). The West Greene School district
has relied upon the economic vitality of the family and homeowner for tax revenue
disproportionately more than its urban and suburban counterparts, to survive, it has been forced
to look inward to ensure its programming has met the needs of our local economy to ensure that
graduates of the West Greene School District have the skills and competencies necessary to find
gainful, local employment. The purpose of this research was to determine the soft skills that the
top employers in Greene County required in potential candidates. While the next step of the
process was outside of the scope of this study, this data will be used by the West Greene School
District to create a soft skills curriculum that focuses on targeted soft skills in three primary
categories: Individual, collaborative, and procedural soft skills (Richie et al., 2022). These soft
skills will be aligned with positive behavior interventions and supports, to be integrated into the
persona of the West Greene graduate.
Setting and Participants
The scope of the research encompassed ten of the top employers in Greene County who
completed the survey. “Top” employers are defined in this study as businesses that employ the
most people in Greene County, Pennsylvania. Therefore, number one on the list of top
employers, employs more people than the second employer on the list, and so on. The survey
was sent out to the top 20 employers. While the initial goal was to get 100% participation from
the top ten employers, it became increasingly obvious to the researcher that was not probable.
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47
Therefore the scope of survey participants evolved over time as the researcher found that each of
the top ten employers were not willing to complete the survey. While the majority of the
respondents were in the top ten, the scope had to be broadened because it became clear that not
all ten would respond. This would point to a 50% participation rate amongst the top 20
employers in Greene County, Pennsylvania. While it is a small sample size, the employers who
chose to complete the survey will remain anonymous. The table in Appendix A, from the
Pennsylvania Department of Labor and Industry Center for Workforce Information and Analysis,
lists and names the top 50 employers in Greene County, Pennsylvania in the fourth quarter of
2023 (Pennsylvania Department of Labor & Industry Center for Workforce Information &
Analysis, 2023). These employers employ the most people in Greene County, Pennsylvania, and
need students from the West Greene School District to sustain their workforces. The only
identifying factor listed was the employers’ North American Industry Classification System
(NAICS) industry code. The NAICS is the standard used by federal statistical industries to
classify business establishments for the purpose of collecting, analyzing, and publishing
statistical data related to the United States business economy (U.S. Census Bureau, 2024d).
Table 8 illustrates the NAICS codes that employers in this study could choose from.
Table 8
NAICS Descriptors
Category
Subcategory
Goods-Producing Excluding Agriculture
Mining
Goods-Producing Excluding Agriculture
Construction
Goods-Producing Excluding Agriculture
Manufacturing
Service-Producing Excluding Special Industries
Utilities
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Service-Producing Excluding Special Industries
Wholesale Trade
Service-Producing Excluding Special Industries
Retail Trade
Service-Producing Excluding Special Industries
Transportation and Warehousing
Service-Producing Excluding Special Industries
Information
Service-Producing Excluding Special Industries
Financial Activities
Service-Producing Excluding Special Industries Professional and Business Services
Service-Producing Excluding Special Industries
Educational Services
Service-Producing Excluding Special Industries
Health Care and Social Assistance
Service-Producing Excluding Special Industries
Leisure and Hospitality
Service-Producing Excluding Special Industries
Other Services
Government
Federal Government
Government
State and Local Government
These descriptors are generally described by descriptor numbers based on NAICS coding. The
goal of collecting data from this list of participants was to create curricular programs to integrate
the soft skills that these employers desired the most in order for our school to educate graduates
best suited for the local workforce.
Each potential participant in the study was provided with a Participant Informed Consent
(Appendix B) before completing the survey. In order for participants to complete the survey,
participants were required to accept the informed consent. The purpose of informed consent was
to ensure that the person taking the survey agreed that they are freely and knowingly taking part
in the study before the study is completed. Informed consent serves as a critical safeguard that
ensures that participants understand that they are autonomous agents making an informed choice
about their participation (U.S. Department of Health and Human Services, 2025). Each
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participant knowingly entered into completing the survey once informed consent was received
eager to provide data about potential employees.
Research Plan
After a systematic review of the literature, it is clear that soft skills were essential
in modern workplaces, especially as automation has taken over many technical tasks.
Employers increasingly valued soft skills like communication, adaptability, teamwork, and
emotional intelligence (Iorio et al., 2022). Therefore, it was critical to our local economy
that the West Greene School District prepared students with these skills. This study
surveyed the top employers in Greene County to identify soft skills that were most
desirable to their businesses in order for the West Greene School District to make a plan to
implement a soft skills program at the junior/senior high school level. To reiterate, the
“Top” employers are defined in this study as businesses that employ the most people in
Greene County, Pennsylvania. Therefore, number one on the list of top employers,
employs more people than the second employer on the list, and so on. Therefore, the
largest employers in terms of number of people employed in Greene County,
Pennsylvania, were surveyed in this study to find the soft skills that they find most
desirable.
In reviewing the literature on types and categories of soft skills, it became
increasingly obvious that important soft skills were difficult to measure in a purely
quantitative way because of the sheer number of potential soft skills that could be required
by employers. Each piece of literature would point to different soft skills with different
definitions than the last piece of literature. There was not simply an aggregate list of soft
skills that employers could choose from to determine which ones were most valuable to a
49
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50
business. Therefore, a mixed methods approach needed to be employed in the research
design in order for the researcher to obtain results that were free from researcher bias to
aggregate the soft skills that were important to our local economy that may have been
overlooked by the researcher. The mixed methods approach with concurrent embedded
design allowed the researcher to explore statistical feedback from the employers, but also
qualitative employer feedback to gain a fuller picture of what soft skills were needed by
the local economy.
The study used a mixed methods approach with a concurrent embedded design,
primarily collecting quantitative data through survey responses about employer sectors,
workforce size, projected job openings, and valued soft skills. Participants could also
suggest additional soft skills that they felt were important to their operations. Qualitative
data was embedded into the survey to gather insights on current and future job
opportunities for students, compared with state and national trends. This method enabled
the researcher to gain a comprehensive understanding of the job market and how the
school can better prepare students for employment.
The basic premise of this research was to determine a way in which the West Greene
School District could develop programming in order to develop a graduate with the soft skills
necessary to thrive in the local economy. There was a clear disconnect between the soft skills
that have been historically ingrained in a West Greene graduate and what was needed by the
local workforce exhibited by the gradual outmigration of graduates and economic decline. This
research targeted local employers to determine the soft skills they valued, it compared those
skills with what is currently taught in the District, and it included questions to gain insights on
what would be available to our students in the local job market to determine the long-term needs
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51
of the workforce. The research plan met the needs of the research problem and used a robust,
mixed methods approach to gather valuable insights that were focused on localized, actionable
solutions to guide reform in the West Greene School District in an attempt to revitalize the local
economy.
Research Methods & Data Collection
The researcher gained approval from the Jefferson-Morgan School District
Superintendent on June 24, 2024, and the research timeline began with the Institutional Review
Board (IRB) approval on August 16, 2024 (Appendix C). However, after the researcher had been
given approval by the IRB, the researcher gained employment in the West Greene School District
as the Jr./Sr. High School Principal. Therefore, the researcher proposed a change of school
district as the basis of the research to the IRB on September 24, 2024, upon receipt of approval
from the West Greene School District Superintendent on September 22, 2024. The change was
approved and the research timeline began with the Institutional Review Board (IRB) approval on
September 30, 2024. The Google Form survey questionnaire was sent to qualifying employers in
early January. The scope of surveyed employers was increased from the top 10 to the top 20 in
March to ensure at least 10 responses from the top employers in Greene County, Pennsylvania.
The survey was open through April 2025. Table 9 illustrates the researcher’s timeline, research
questions, and correlated survey questions.
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52
Table 9
Data Collection Timeline and Survey Questions
Timeline for
survey
questions:
Surveys will be sent electronically and be available from December 23, 2024,
to April 30, 2025. After three weeks of the first ten employers having the
survey and being notified, five more employers will be sent the survey. I will
follow this pattern until the top twenty employers in Greene County,
Pennsylvania, have been provided the survey. Reminders will be sent every
three weeks to employers until ten surveys have been completed.
Research Question: How do graduates with the desired soft skills, as determined by the West
Greene School District administration, compare to the soft skills identified by local business
leaders to sustain the workforce of Greene County, Pennsylvania?
Data Type:
Quantitative
Survey Questions
On a scale from "Not Aligned" to "Perfectly Aligned", how closely do you
think the following Individual soft skills match the soft skills you consider
important to your workforce?
Short Descriptions:
Work Under Pressure- Time management involves effectively planning and
organizing priorities to optimize productivity and minimize stress. It enhances
performance under pressure and supports lifelong learning through continuous
self-assessment and improvement.
Innovative Problem-Solving- Innovative ideas and job-related activities are
vital for enhancing products and services, driving organizational growth.
Conducting cost-benefit analyses helps identify effective, long-term solutions
to business challenges.
Integrity and Empathy- Building trust and rapport fosters a compassionate
workplace while maintaining integrity and personal values. Empathy involves
understanding and appreciating others' perspectives, promoting positive
interactions and collaboration.
Emotional Intelligence- Emotional intelligence involves understanding,
managing, and utilizing emotions effectively. It encompasses skills like
self-awareness, empathy, influence, and collaboration. During crises or
conflicts, emotional intelligence fosters psychological safety, prevents
groupthink, and enhances organizational performance.
On a scale from "Not Aligned" to "Perfectly Aligned", how closely do you
think the following Collaborative soft skills match the soft skills you consider
important to your workforce? Short Descriptions: Communication- Business
communication skills include clear information sharing, active listening for
negotiations, and effective networking. Successful team collaboration requires
concise feedback to encourage creativity, while constructive feedback supports
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53
reflection and continuous improvement. Team Work- This involves
coordinating, cooperating, and collaborating to build trust and support among
team members while aligning actions with the team's mission. Effective
conflict management is key to resolving disputes and maintaining team
cohesion. Global and Cultural Diversity- This focuses on fostering an
inclusive environment that encourages creativity and a strong sense of
belonging. Leadership Skills- This highlights key leadership traits such as
self-confidence, enthusiasm, assertiveness, authenticity, trustworthiness,
humility, and humor. Effective leaders align their actions with their intentions,
demonstrating authenticity and fostering trust. Business Etiquette- Business
etiquette involves respecting workplace norms and differences. Actions like
remembering names, offering handshakes, and maintaining positive gestures,
such as nodding or smiling, demonstrate respect and active listening.
Awareness of cultural norms and effective communication practices helps
prevent miscommunication and fosters strong professional relationships. On a
scale from "Not Aligned" to "Perfectly Aligned", how closely do you think the
following Procedural soft skills match the soft skills you consider important to
your workforce? Short Descriptions: Quantitative Skills- These skills involve
reasoning and understanding numerical data to solve problems and make
decisions. Flexibility for Organizational Changes- These skills involve the
ability to adapt to dynamic tasks and changing circumstances, reflecting high
performance potential. Consistently completing defined activities ensures
reliability and fosters trust in outcomes. Critical Thinking- This is the ability
to research and create a critical analysis of information and relate a systemic
approach to problem solving. Ability to Make Decisive Decisions- This relates
to considering alternative solutions that will support the cognitive process of a
belief, or course of action based on several alternative options. Responsibility
for Getting the Job Done- This relates to applying work habits such as
maintaining wellness, time management, follow through, and initiative creates
the ability to contemplate information and skill development.
On a scale from "Not Aligned" to "Perfectly Aligned", how closely do you
think the following Procedural soft skills match the soft skills you consider
important to your workforce? Short Descriptions: Quantitative Skills- These
skills involve reasoning and understanding numerical data to solve problems
and make decisions. Flexibility for Organizational Changes- These skills
involve the ability to adapt to dynamic tasks and changing circumstances,
reflecting high performance potential. Consistently completing defined
activities ensures reliability and fosters trust in outcomes. Critical ThinkingThis is the ability to research and create a critical analysis of information and
relate a systemic approach to problem solving. Ability to Make Decisive
Decisions- This relates to considering alternative solutions that will support
the cognitive process of a belief, or course of action based on several
alternative options. Responsibility for Getting the Job Done- This relates to
applying work habits such as maintaining wellness, time management, follow
through, and initiative creates the ability to contemplate information and skill
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54
development.
On a scale from "No Gap" to "Significant Gap", to what degree do you believe
there is a gap between the Individual, Collaborative, and Procedural Soft
skills, identified above, and those needed for your workforce?
Data Type:
Qualitative
From your perspective, how do the Individual soft skills listed above compare
to the soft skills needed to sustain your workforce? Please provide specific
examples or experiences that highlight any similarities or differences.
From your perspective, how do the Collaborative soft skills listed above
compare to the soft skills needed to sustain your workforce? Please provide
specific examples or experiences that highlight any similarities or differences.
From your perspective, how do the Procedural soft skills listed above compare
to the soft skills needed to sustain your workforce? Please provide specific
examples or experiences that highlight any similarities or differences.
Research Question: To what extent do current job openings and projected job openings in
Greene County compare to statistics from the US Bureau of Labor and Statistics?
Data Type:
Quantitative
Survey Questions:
Which option best describes your industry? Goods- Producing Excluding
Agriculture- Mining, Goods- Producing Excluding Agriculture- Construction,
Goods- Producing Excluding Agriculture- Manufacturing, Service- Producing
Excluding Special Industries- Utilities, Service- Producing Excluding Special
Industries- Wholesale Trade, Service- Producing Excluding Special IndustriesRetail Trade, Service- Producing Excluding Special Industries- Transportation
and Warehousing, Service- Producing Excluding Special IndustriesInformation, Service- Producing Excluding Special Industries- Financial
Activities, Service- Producing Excluding Special Industries- Professional and
Business Services, Service- Producing Excluding Special IndustriesEducational Services, Service- Producing Excluding Special Industries- Health
Care and Social Assistance, Service- Producing Excluding Special IndustriesLeisure and Hospitality, Service- Producing Excluding Special IndustriesOther Services, Federal Government, State and Local Government.
How many employees does your company employ?
How many job openings do you anticipate hiring for within the next calendar
year?
How many job openings do you project hiring for five years from now?
Data Type:
Qualitative
Survey Questions:
What factors do you think will influence your projected hiring needs?
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55
Research Question: To what extent do the top Greene County business employers in the public
and private sectors value the soft skills that are being taught by the West Greene School
District for entry level positions?
Data Type:
Quantitative
Survey Questions:
Please rank the following "Individual Soft Skills" in order of most important
(1) to least important (4), on the list, in hiring a potential candidate in your
industry. Short Descriptions: Work Under Pressure- Time management
involves effectively planning and organizing priorities to optimize productivity
and minimize stress. It enhances performance under pressure and supports
lifelong learning through continuous self-assessment and improvement.
Innovative Problem-Solving- Innovative ideas and job-related activities are
vital for enhancing products and services, driving organizational growth.
Conducting cost-benefit analyses helps identify effective, long-term solutions
to business challenges. Integrity and Empathy- Building trust and rapport
fosters a compassionate workplace while maintaining integrity and personal
values. Empathy involves understanding and appreciating others' perspectives,
promoting positive interactions and collaboration. Emotional IntelligenceEmotional intelligence involves understanding, managing, and utilizing
emotions effectively. It encompasses skills like self-awareness, empathy,
influence, and collaboration. During crises or conflicts, emotional intelligence
fosters psychological safety, prevents groupthink, and enhances organizational
performance.
Please rank the following "Collaborative Soft Skills" in order of most
important (1) to least important (5), on the list, in hiring a potential candidate
in your industry. Short Descriptions: Communication- Business
communication skills include clear information sharing, active listening for
negotiations, and effective networking. Successful team collaboration requires
concise feedback to encourage creativity, while constructive feedback supports
reflection and continuous improvement. Team Work- This involves
coordinating, cooperating, and collaborating to build trust and support among
team members while aligning actions with the team's mission. Effective
conflict management is key to resolving disputes and maintaining team
cohesion. Global and Cultural Diversity- This focuses on fostering an
inclusive environment that encourages creativity and a strong sense of
belonging. Leadership Skills- This highlights key leadership traits such as
self-confidence, enthusiasm, assertiveness, authenticity, trustworthiness,
humility, and humor. Effective leaders align their actions with their intentions,
demonstrating authenticity and fostering trust. Business Etiquette- Business
etiquette involves respecting workplace norms and differences. Actions like
remembering names, offering handshakes, and maintaining positive gestures,
such as nodding or smiling, demonstrate respect and active listening.
Awareness of cultural norms and effective communication practices helps
prevent miscommunication and fosters strong professional relationships.
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56
Please rank the following "Procedural Soft Skills" in order of most important
(1) to least important (5), on the list, in hiring a potential candidate in your
industry. Short Descriptions: Quantitative Skills- These skills involve
reasoning and understanding numerical data to solve problems and make
decisions. Flexibility for Organizational Changes- These skills involve the
ability to adapt to dynamic tasks and changing circumstances, reflecting high
performance potential. Consistently completing defined activities ensures
reliability and fosters trust in outcomes. Critical Thinking- This is the ability
to research and create a critical analysis of information and relate a systemic
approach to problem solving. Ability to Make Decisive Decisions- This relates
to considering alternative solutions that will support the cognitive process of a
belief, or course of action based on several alternative options. Responsibility
for Getting the Job Done- This relates to applying work habits such as
maintaining wellness, time management, follow through, and initiative creates
the ability to contemplate information and skill development.
Please rank the following groupings of soft skills in order of most important
(1) to least important (3), on the list, in hiring a potential candidate in your
industry: Individual, Collaborative, and Procedural
Data Type:
Qualitative
Survey Questions:
In your experience, how does your workplace value the Individual soft skills
listed above for entry level and professional positions. Please provide
examples or anecdotes to illustrate your perspective.
In your experience, how does your workplace value the Collaborative soft
skills listed above for entry level and professional positions. Please provide
examples or anecdotes to illustrate your perspective.
In your experience, how does your workplace value the Procedural soft skills
listed above for entry level and professional positions. Please provide
examples or anecdotes to illustrate your perspective.
In your experience, how does your workplace value the three categories of soft
skills, as a whole, listed above for entry level and professional positions.
Please provide examples or anecdotes to illustrate your perspective.
The research method that was used in this research study was a mixed methods approach
with concurrent embedded design. According to Almeida (2018), an advantage of this type of
design is that it is very suitable when there is a predominant type of data being collected and
analyzed (p. 146). However, it must be noted that a disadvantage to this type of data collection
was that there could have been difficulties reconciling conflicting and antagonistic results
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57
(Almeida, 2018, p. 146). The predominant data type that was collected for this study was
quantitative data where respondents selected from a predetermined list of NAICS codes to
inform the researcher on the economic sector of respondents, the number of employees the
responder employed, the number of anticipated job openings the respondent expects within the
next calendar year and five years from now, and ranking the three sets of soft skills. In addition,
respondents had the ability to add soft skills that were not included in the survey that they saw as
valuable to their employment criteria. Furthermore, there were embedded qualitative questions to
determine current and employer projected positions that could be available to our students with
these skills/competencies compared to national and state level statistics. This type of research
design is being employed because of the time constraints associated with action research. This
mixed methods approach allowed both types of data to be collected simultaneously to gain a
comprehensive view of the job market and the school’s role in graduating students for the job
market.
When looking at the fiscal implications of the research, there were minimal fiscal
implications in the research methods or in data collection. Outside of administrative costs
associated with completing the work like the researcher’s time or the cost of the applications
used to aggregate data and to word process any documentation, the costs were incredibly limited.
Any and all fiscal implications of this research was based on the outcomes of the research and
data collection. These implications would have a significant impact on the budgeting priorities of
the district, resource allocation, and potential partnerships. The outcome of these research
questions would lead to a curriculum redesign in terms of revised curriculum materials,
purchasing new resources, or providing professional development for teachers to emphasize the
soft skills that local employers prioritize, in an effort to address misalignment. Potential
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58
outcomes could lead to program expansions and program contractions that could require
additional funding. On the other hand, there could be opportunities for cost saving measures as a
result of the potential research outcomes. Once alignment exists between our curriculum and
local employers, the district could leverage partnerships that involve co-funded programs,
student internships, mentorship opportunities; opportunities that could reduce the school’s
financial burden. These outcomes could result from the data collection and research design and
did not fiscally impact the study before it was conducted.
Validity
One aspect of a valid study is credibility. According to Hendricks (2017), having credible
data means having a dataset that is complete and accurate (p. 64). In creating credibility in this
study, the researcher focused on the accuracy of the findings in order to come to correct
interpretations with the correct conclusions. One strategy that was employed to maintain
accuracy and come to proper conclusions during data collection was triangulating survey
questions by using a mixed methods embedded design to gather data. Also, the researcher
worked to survey at least ten of the top employers in Greene County to ensure triangulation.
Another aspect of a valid study as it pertains to data collection is transferability, or the
extent to which the results of a study are applicable to other contexts and other individuals
(Hendricks, 2017, p. 64). In order to achieve transferability, the researcher has shown the
usefulness of the results in different settings and contexts. Some strategies that were employed to
help ensure transferability were describing in detail the setting, participants, intervention, and
research methods employed in the study (Hendricks, 2017, p.65). This will allow other
researchers to find commonality between this action research and their own.
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59
After the researcher had achieved credibility and transferability, the researcher needed to
achieve dependability, or the degree to which research results would replicate with the same or
similar participants and/or contexts (Hendricks, 2015, p. 64). The goal for any research study is
replicability to other participants, and in order to achieve this the researcher has provided a great
deal of detail to set the scene of the research. Make no mistake, Greene County, Pennsylvania, is
a very rural area of Appalachia, therefore, any results will most likely be dependable to other
school districts or to people in other contexts with similar demographics. Therefore, these
demographics needed to be explained in greater detail.
Lastly, a good research study has confirmability, or the showing of results that are an
accurate representation of what occurred, rather than a result of researcher bias (Hendricks, 2015,
p. 64). In order to achieve this, the research has provided evidence that biases have been taken
into account. In order to do this, the researcher has cleared any biases. This means that the
researcher has reflected and self-reported in the study any biases, including inherent biases that
might have existed in order to be fully transparent with the reader (Hendricks, 2017, p. 66). Since
the researcher engaged in triangulation and made biases clear, as well as engaged in a credible,
dependable, and transferable study, the research was and is valid.
Summary
In conclusion, this study offered a meaningful and localized approach to addressing the
pressing economic and educational challenges facing Greene County, Pennsylvania, and
specifically the West Greene School District. Rooted in the realities of a rural community
experiencing economic stagnation, workforce decline, and increasing poverty, the research
affirmed the critical role schools must play in regional revitalization (U.S. Census Bureau, 2023).
The West Greene School District, uniquely positioned as both an educational institution and a
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60
community anchor, has a responsibility to ensure that its graduates are equipped with the soft
skills essential for success in the contemporary job market.
The study's use of a mixed methods, concurrent embedded design allowed for the
collection of mostly quantitative and important qualitative data from a targeted group of Greene
County’s leading employers (Almeida, 2018, p. 146). This design proved instrumental in
capturing the nuances of employer needs while also producing measurable results that can
inform future decision-making. Quantitative survey responses offered insight into workforce
trends and soft skill priorities, while qualitative feedback enriched the data with contextual
understanding. Through this comprehensive approach, the research succeeded in highlighting
both current gaps and future opportunities in aligning educational outcomes with workforce
expectations.
Beyond academic implications, this research holds significant practical and fiscal
relevance. In the researcher’s estimation, the integration of employer-valued soft skills into the
district curriculum has the potential to reduce graduate outmigration, bolster local employment,
and create sustainable partnerships with area businesses. While implementation will require
resource investment and professional development, the long-term benefits include improved
student preparedness, greater employer satisfaction, and the strengthening of Greene County's
local economy.
To conclude, this research affirmed the necessity of aligning school programming with
local economic demands and provided a clear path forward for doing so. The West Greene
School District, through the development of a soft skills curriculum based on employer input,
can better prepare its graduates for meaningful, gainful employment while contributing to the
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revitalization of its community. This study marked an important step toward that goal, laying the
groundwork for future action that is both informed and impactful.
ARE OUR GRADUATES PREPARED?
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Chapter IV
Data Analysis & Results
The primary focus of this action research study is to determine the soft skills that the
largest employers in Greene County, Pennsylvania, see as the most important to their businesses,
to determine to what degree the West Greene School District is already meeting the demand for
needed skills, and to determine the number of jobs that may be available by these employers for
entry level prospective candidates with these specific soft skills. The data analysis and results
were guided by the following research questions:
1. To what extent do the top Greene County business employers in the public and
private sectors value the soft skills that are being taught by the West Greene
School District for entry level positions?
2. To what extent do current job openings and projected job openings in Greene
County compare to statistics from the US Bureau of Labor and Statistics?
3. How do graduates with the desired soft skills, as determined by the West Greene
School District administration, compare to the soft skills identified by local
business leaders to sustain the workforce of Greene County, Pennsylvania?
The goal of this capstone project is to determine where the soft skills curriculum in the
West Greene Junior/Senior High School is in relation to the desired soft skills of our local
employers in an effort to create the best soft skills curriculum in order to mold graduates who are
prepared and needed for the local workforce. The research was designed to incorporate multiple
data sources and types to ensure strong results through triangulation using a mixed methods
approach with a concurrent embedded design. Qualitative and quantitative data were collected
through multiple measures through the use of a survey. As listed in Table 9, each research
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question had multiple qualitative and quantitative questions associated with it to ensure
triangulation and valid results. Specifically, the first research question had five quantitative
questions and three qualitative questions, the second research question had four quantitative
questions and one qualitative question, and the third research question had four quantitative
questions and four qualitative questions. Each survey question was aligned with an associated
research question for the purpose of triangulated results for better overall analysis and
understanding.
Data Analysis
Data analysis in this action research study took many twists and turns based on the results
from each of the survey questions. The survey was conducted through Google Forms. The
quantitative data from the Google Form was transferred into a Google Sheet that would be coded
for SPSS. SPSS was used to analyze the raw data into comprehensible information. In addition to
SPSS, NVivo was used to analyze qualitative data. Once themes were established, either
inductively or deductively, responses were analyzed through NVivo by coding themes and then
separating responses into those themes. Quantitative data set the foundation of the survey and
study; whereas, qualitative data was used to fill in any gaps that could not be predicted by the
researcher.
The first questions on the survey that were analyzed were aligned with my second
research question: To what extent do current job openings and projected job openings in Greene
County compare to statistics from the US Bureau of Labor and Statistics? SPSS was not used to
aggregate this data as the data was simple, but NVivo 15 software was used to analyze the
qualitative responses through thematic analysis to identify trends amongst the themes
(Lumivero, 2024).
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The next questions in the survey were aligned with research question one: To what extent
do the top Greene County business employers in the public and private sectors value the soft
skills that are being taught by the West Greene School District for entry level positions? SPSS
was used to find the mean and standard deviation of how each employer ranked soft skills within
each of the three categories: Individual, Collaborative, and Procedural. SPSS was only used on
the questions finding quantitative results. When looking at the mean for each question, finding a
mean closer to one meant that the employer ranked the soft skill higher, and having a lower
standard deviation meant that there was more consensus of the ranking among respondents (IBM
Corp., 2021). Once these measures were found, the researcher ran a Friedman Test through SPSS
to ensure that the differences in ranks occurred as a matter of fact and not by accident (IBM
Corp., 2021). If the Friedman Test resulted in a p-value of .05 or lower, it was clear that there
were strong correlations between the data. In order to find these correlations, a Wilcoxon Signed
Rank Test was run through SPSS (IBM Corp., 2021). If a p-value of less than .05 was shown
between two variables, then there were significant correlations. These tests were run on the
quantitative survey questions intended to rank soft skills. On the other hand, the qualitative
questions were thematically analyzed and then coded to find trends through NVivo 15 software
(Lumivero, 2024).
The next set of survey questions were aligned with the third research question: How do
graduates with the desired soft skills, as determined by the West Greene School District
administration, compare to the soft skills identified by local business leaders to sustain the
workforce of Greene County, Pennsylvania? SPSS was used on the quantitative questions
aligned with this research question to first find mean, standard deviation, and skewness because
these are Likert scale questions (IBM Corp., 2021). Again, a lower standard deviation meant
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more consensus in the respondents’ responses on the Likert scale. A mean closer to five meant
that the soft skill was highly aligned with the needs of their industry. Skewness was determined
to find the degree in which answers were skewed one way or the other, and a skewness closer to
zero meant that responses were less skewed. In addition, valid percentages were found to
determine the rate in which respondents responded at each level of the Likert scale. On the other
hand, qualitative data went through a thematic analysis, either inductively or deductively, and
then the responses were coded into those themes to find trends using NVivo 15 software
(Lumivero, 2024).
Results
As noted above, the data from each survey question, aligned to each research question
went through extensive data analysis. This goal of this analysis is to answer the following
research questions: To what extent do the top Greene County business employers in the public
and private sectors value the soft skills that are being taught by the West Greene School District
for entry level positions?; To what extent do current job openings and projected job openings in
Greene County compare to statistics from the US Bureau of Labor and Statistics?; and How do
graduates with the desired soft skills, as determined by the West Greene School District
administration, compare to the soft skills identified by local business leaders to sustain the
workforce of Greene County, Pennsylvania?
Quantitative Industry Demographics
The survey must first be deconstructed to the types of questions asked of the survey
participants. The first five survey questions were meant to gain data on the respondents with the
goal of comparing that data to state or national level data in correlation with the second research
question: To what extent do current job openings and projected job openings in Greene County
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compare to statistics from the US Bureau of Labor and Statistics? The first four questions
relating to the second research question were quantitative questions. The goal of the first
question was to gain information on the type of industry the respondents are in to help the
researcher understand the industries being represented. The survey was distributed to the 50
largest employers in Greene County (Appendix A). Out of the 50 potential respondents, 10
surveys were collected for a 20% participation rate. The goal of the study was to survey the top
10 businesses, but to expect a 100% participation rate was not likely. So the study was expanded
to the top 50 largest employers with a goal of at least 10 respondents. The researcher achieved
that goal. Table 10 refers to the NAICS descriptors of the respondents.
Table 10
NAICS Descriptors of Respondents
NAICS Descriptor
Percent of Respondents
Service- Producing Excluding
Special IndustriesEducational Services
(Includes Public and Private
Schools)
70%
Goods- Producing Excluding
Agriculture- Construction
20%
Service- Producing Excluding
Special Industries- Health
Care and Social Assistance
10%
The next quantitative question was meant to find out how large the company is by
requesting the total number of employees employed with the company. Table 11 illustrates a
breakdown of the number of employees the respondents have.
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Table 11
Number of Employees
Range
Percent of Respondents
1-49 employees
10%
50-99 employees
30%
100-199 employees
40%
200-299 employees
10%
300 or more employees
10%
The next quantitative question was meant to find how many job openings would be
available and filled within each company in the next year, and the last quantitative question
aligned with this research question was meant to determine how many openings the employer
plans on filling five years from now. Table 12 refers to the number of job openings each
respondent plans to fill this year compared to the number of positions that respondents plan to fill
in five years.
Table 12
Comparison of Job Openings to be Filled Within a Year Compared to Within Five Years
Range
Openings to be filled within the
year
Projected openings to be filled in
five years
Respondent 1
3-5
0
Respondent 2
5
15
Respondent 3
2-5
5
Respondent 4
3-5
12-15
Respondent 5
1-5
10-15
Respondent 6
0
1-5
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Respondent 7
10-15
0
Respondent 8
5-10
20
Respondent 9
1-2
4-6
Respondent 10
5-10
25
Qualitative Industry Demographics
The next survey question was an embedded qualitative question: What factors do you
think will influence your projected hiring needs? Through a thematic analysis, some very
pronounced themes arose in the manual coding of the qualitative data. These themes are as
follows: Retirements and turnover, program/company expansion or reduction, and industry
specific external factors. These themes were inductively developed, meaning that the researcher
analyzed responses and created a list of broad topics/ themes that were pronounced in responses
(Braun & Clarke, 2006, p. 12).
Once the themes were established, the qualitative data were analyzed using Nvivo 15
software (Lumivero, 2024). Using the software, the researcher found that industry specific
external factors were overwhelmingly the major theme of the returned data for this research
question. Included in these industry specific external factors is people changing positions or
school districts; school enrollment trends; the company’s increased involvement in oil/gas,
landfills, civil work, and trucking needs; school program expansions/contractions; insurance
reimbursements, aging population, and the expansion of larger healthcare organizations growing
in the area. The last two themes, retirements and turnover and program/company expansion or
reduction were still redundant themes but not as pronounced as industry specific external factors.
The factors associated with the theme industry specific external factors were shown to be the
greatest factors influencing projected hiring needs by a one to five ratio of the other themes.
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Quantitative Ranking of Individual Soft Skills
The next survey questions are aligned with the first research question: To what extent do
the top Greene County business employers in the public and private sectors value the soft skills
that are being taught by the West Greene School District for entry level positions? These
questions are intended to determine which of the soft skills valued by the West Greene School
District are most valued by the largest employers in Greene County. Respondents were asked to
rank different soft skills under each category of soft skills: Individual, Collaborative, and
Procedural. For Individual Soft Skills, respondents were asked to rank: Work under pressure,
innovative problem-solving, integrity and empathy, and emotional intelligence. Table 13
illustrates the mean and standard deviation of the responses. This data was run through the data
analysis tool SPSS (IBM Corp., 2021). Responses that have a mean closer to one were deemed
more important by respondents and the lower the standard deviation, the more consensus there
was about the particular rating of a soft skill.
Table 13
Mean and Standard Deviation of Ranking Individual Soft Skills
Individual Soft Skills
Mean
Standard Deviation
Work Under Pressure
2.5
1.269
Innovative ProblemSolving
2
.943
Integrity and
Empathy
2.2
1.135
Emotional
Intelligence
3.3
.823
When looking at this data it is important to delineate if these differences in ranking are
real or if the differences occurred by a random occurrence. In order to make this delineation the
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researcher used SPSS to run a Friedman Test to determine if the data was reliable and not
random. Table 14 provides the outcome of the Friedman Test. The p-value of .188 indicates that
there is no clear correlation in the differences and they could be a result of random occurrence.
Table 14
Friedman Test of Individual Soft Skills
Friedman Test
Chi- Square
df
Statistics
5.880
3
p-value
.118
Qualitative Aggregation of Individual Soft Skills
The next survey question was an embedded qualitative question that aimed to fill any
gaps that the researcher could have missed in their aggregation of Individual Soft Skills. Through
a thematic analysis, some very pronounced themes arose in the manual coding of the qualitative
data. These themes include “variances in desired soft skills between professional roles and entry
level roles” and “variances in desired soft skills between education sector positions and business
sector positions”. These themes were deductively developed, meaning that the researcher
analyzed responses that were aligned with a pre-existing framework of soft skills (Braun &
Clarke, 2006, p. 12).
Once the themes were established, the qualitative data were analyzed using Nvivo 15
software (Lumivero, 2024). The most prominent theme was the differences in desired soft skills
between entry level positions and professional level positions. In professional roles there is
increased emphasis on leadership, problem-solving, initiative, and independent decision-making;
whereas, for entry level positions the soft skills focus is on communication, teamwork,
adaptability, and time management. The next, less prominent theme is that there are differences
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between the needs of the business sector and the education sector in terms of soft skills.
Respondents from the education sector valued emotional intelligence and empathy much more
than the other sectors; whereas, service industry and business sector respondents value stress
management, reliability, and initiative. These stark contrasts represent a major theme of the data.
Quantitative Ranking of Collaborative Soft Skills
The next category of soft skills that was ranked by respondents was Collaborative Soft
Skills. For Collaborative Soft Skills, respondents were asked to rank the following soft skills:
Communication, teamwork, global and cultural diversity, leadership skills, and business
etiquette. Table 15 illustrates the mean and standard deviation of the responses. This data was
run through the data analysis tool SPSS. Responses that have a mean closer to one were deemed
more important by respondents and the lower the standard deviation, the more consensus there
was about the particular ranking of a soft skill.
Table 15
Mean and Standard Deviation of Ranking Collaborative Soft Skills
Collaborative Soft
Skills
Mean
Standard Deviation
Communication
1.1
.316
Teamwork
2.3
.823
Global and Cultural
Diversity
4.6
.516
Leadership Skills
3.4
.966
Business Etiquette
3.6
1.075
Likewise with Individual Soft Skills, when looking at this data it is important to delineate
if these differences in ranking are real or if the differences occurred by a random occurrence. In
order to make this delineation the researcher used SPSS to run a Friedman Test to determine if
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the data was reliable and not random. Table 16 provides the outcome of the Friedman Test. The
p-value of <.001 indicates that there is a strong correlation in the differences and are not a result
of potential random occurrences.
Table 16
Friedman Test of Collaborative Soft Skills
Friedman Test
Statistics
Chi Square
28.720
df
4
p-value
<.001
It was important for the researcher to dig deeper into the strong correlation p-value from
the ranking of Collaborative Soft Skills. With such a high correlation it is important to find
where that correlation exists within the data. In order to find these correlations, a Wilcoxon
Signed Rank Test was used in SPSS. In order to run this test, the researcher had to compare the
values of each of the soft skills to one another. The results of the Wilcoxon Signed Rank Tests
are illustrated in Table 17. With p-values under .05, the researcher can ascertain that these
differences are not by chance.
Table 17
Wilcoxon Signed Rank Tests
Comparisons
Z
2 Tailed p-value
Teamwork vs.
Communication
-2.489
.013
Global and Cultural
Diversity vs.
Communication
-2.877
.004
Leadership Skills vs.
Communication
-2.871
.004
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Business Etiquette vs.
Communication
-2.831
.005
Global and Cultural
Diversity vs.
Teamwork
-2.859
.004
Leadership Skills vs.
Teamwork
-1.998
.046
Business Etiquette vs.
Teamwork
-2.021
.043
Leadership Skills vs.
Global and Cultural
Diversity
2.235
.025
Business Etiquette vs.
Global and Cultural
Diversity
1.999
.046
Business Etiquette vs.
Leadership Skills
-.263
.793
Qualitative Aggregation of Collaborative Soft Skills
The next embedded qualitative question was aimed to fill any gaps that the researcher
could have missed in their aggregation of Collaborative Soft Skills. Through a thematic analysis,
themes such as communication and teamwork with mentorship and trust-building as a key
subtheme and leadership are pronounced themes. These themes were deductively developed,
meaning that the researcher analyzed responses that were aligned with a pre-existing framework
of soft skills and these themes were most pronounced (Braun & Clarke, 2006, p. 12).
Once the themes were established, the qualitative data were analyzed using Nvivo 15
software (Lumivero, 2024). From the data analysis, it is clear that communication is valued most
by each industry because of its interplay with building effective teams that lead to enhanced
mentorship opportunities. Leadership was also an important theme amongst respondents because
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leadership is an expectation of the most and least tenured employees in an organization. These
themes were most prominent in the analysis of this qualitative dataset.
Quantitative Ranking of Procedural Soft Skills
The next category of soft skills that was ranked by respondents was Procedural Soft
Skills. For Procedural Soft Skills, respondents were asked to rank the following soft skills:
Quantitative skills, flexibility for organizational change, critical thinking, ability to make
decisive decisions, and responsibility to get the job done. Table 18 illustrates the mean and
standard deviation of the responses. This data was run through the data analysis tool SPSS.
Responses that have a mean closer to one were deemed more important by respondents and the
lower the standard deviation, the more consensus there was about the particular ranking of a soft
skill.
Table 18
Mean and Standard Deviation of Ranking Procedural Soft Skills
Procedural Soft Skills
Mean
Standard Deviation
Quantitative Skills
4.3
1.494
Flexibility for
Organizational
Change
3.2
.919
Critical Thinking
2.4
1.350
Ability to Make
Decisive Decisions
2.9
.876
Responsibility to Get
the Job Done
1.89
1.269
Just as with Individual and Collaborative Soft Skills, when looking at this data it is
important to delineate if these differences in ranking are real or if the differences occurred by a
random occurrence. In order to make this delineation the researcher used SPSS to run a Friedman
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Test to determine if the data was reliable and not random. Table 19 provides the outcome of the
Friedman Test. The p-value of <.002 indicates that there is a strong correlation in the differences
and are not a result of potential random occurrences.
Table 19
Friedman Test of Procedural Soft Skills
Friedman Test
Statistics
Chi Square
16.622
df
4
p-value
.002
The result of the Friedman Test produced a very low p-value, indicating a strong
correlation. Therefore, It was again important for the researcher to dig deeper into the strong
correlation p-value from the ranking of Procedural Soft Skills. The results of the Wilcoxon
Signed Rank Test, made through SPSS, are illustrated in Table 20. With p-values under .05, the
researcher can ascertain that these differences are not by chance; however, there are a few
comparisons that do not guarantee a correlation.
Table 20
Wilcoxon Signed Rank Tests
Comparisons
Z
2 Tailed P-Score
Quantitative Skills vs.
Flexibility for
Organizational
Change
-1.658
.097
Quantitative Skills vs.
Critical Thinking
-2.265
.024
Quantitative Skills vs.
Ability to Make
Decisive Decisions
-1.813
.070
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Quantitative Skills vs.
Responsibility to Get
the Job Done
-2.534
.011
Flexibility for
Organizational
Change vs. Critical
Thinking
-1.412
.158
Flexibility for
Organizational
Change vs. Ability to
Make Decisive
Decisions
-.690
.490
Flexibility for
Organizational
Change vs.
Responsibility to Get
the Job Done
-2.228
.026
Critical Thinking vs.
Ability to Make
Decisive Decisions
.777
.437
Critical Thinking vs.
Responsibility to Get
the Job Done
-.889
.374
Ability to Make
Decisive Decisions
vs. Responsibility to
Get the Job Done
-2.145
.032
Qualitative Aggregation of Procedural Soft Skills
The next embedded qualitative survey question aimed to fill any gaps that the researcher
could have missed in their aggregation of Procedural Soft Skills. Through a thematic analysis,
the theme “Procedural Soft Skills are non-negotiable for successful work performance” and
subtheme “necessary Procedural Soft Skills vary across industries”. These themes were
deductively developed, meaning that the researcher analyzed responses that were aligned with a
pre-existing framework of soft skills (Braun & Clarke, 2006, p. 12).
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Once the themes were established, the qualitative data were analyzed using Nvivo 15
software (Lumivero, 2024). Once the data was analyzed it was clear that the major consensus
was that Procedural Soft Skills are non-negotiable to a successful workforce; however, the
specific sets of skills varied by industry. In education, time management and problem-solving
were emphasized; in healthcare informed decision-making, consistency, and professional
standards were emphasized; and in construction safety, flexibility, and independent
problem-solving was emphasized. This theme and subtheme was very pronounced in the
responses.
Quantitative Ranking of Soft Skills Categories: Individual, Collaborative, and Procedural
After respondents ranked each soft skill in each category, the researcher also wanted to
know how these employers would rank each of the categories in order to determine the main
categorical focus of the soft skills program. Table 21 illustrates how respondents ranked each of
the categories of soft skills. This data was run through the data analysis tool SPSS. Responses
that have a mean closer to one were deemed more important by respondents and the lower the
standard deviation, the more consensus there was about the particular ranking of a category.
Table 21
Mean and Standard Deviation of Ranking Soft Skills Categories
Category
Mean
Standard Deviation
Individual
1.6
.699
2
.943
2.40
.699
Collaborative
Procedural
The Friedman Test was performed to delineate if these differences in ranking are real or if
the differences occurred by a random occurrence. In order to make this delineation the researcher
used SPSS to run a Friedman Test to determine if the data was reliable and not random. Table 22
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provides the outcome of the Friedman Test. The p-value of .202 indicates that there is not a
strong correlation in the differences and could be a result of potential random occurrences.
Table 22
Friedman Test of Ranking Soft Skills Categories
Friedman Test
Chi Square
df
Statistics
3.2
2
p-value
.202
Qualitative Aggregation Soft Skills Categories: Individual, Collaborative, and Procedural
The last embedded qualitative survey question for the ranking questions is aimed to fill
any anecdotal gaps that could not have been ascertained through quantitative data about ranking
the three soft skills categories in terms of value to entry and professional level positions.
Through a thematic analysis, a very pronounced theme arose in the manual coding of the
qualitative analysis. This theme indicated that all of these soft skill categories are very valuable
to each industry; however, each comes with its specific drawbacks. These themes were
deductively developed, meaning that the researcher analyzed responses that were aligned with a
pre-existing framework of soft skills (Braun & Clarke, 2006, p. 12). This topic was the most
pronounced.
Once the themes were established, the qualitative data were analyzed using Nvivo 15
software and subthemes became apparent (Lumivero, 2024). Collaborative Skills are critical for
teamwork, but are the hardest to teach in the professional setting. Procedural skills ensure
organizational efficiency and can be developed with practice over time. Lastly, Individual Skills
are foundational skills that enhance the other categories. These subthemes enhance the larger
theme that each skillset is important, but have skill-specific drawbacks.
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Quantitative Alignment of Individual Soft Skills
Whereas the previous questions of the survey were ranking questions aligned with the
first research question, the next set of survey questions were aligned with the third research
question: How do graduates with the desired soft skills, as determined by the West Greene
School District administration, compared to the soft skills identified by local business leaders to
sustain the workforce of Greene County, Pennsylvania? For these questions, respondents were
asked to identify the alignment between the soft skills identified by the West Greene School
District and the soft skills needed in the respondents’ industry. Respondents answered on a Likert
scale with the following descriptors: Not aligned, somewhat not aligned, indifferent to the soft
skill in our industry, somewhat aligned, and perfectly aligned. The scale used in the survey
demonstrated high reliability, with Cronbach's Alpha (α) equaling .919. This score was
determined by a test using SPSS. The first Likert scale question asked respondents to scale the
Individual Soft Skills: “Work Under Pressure,” “Innovative Problem-Solving,” “Integrity and
Empathy,” and “Emotional Intelligence,” using the aforementioned scale. Table 23 illustrates the
mean, standard deviation, and skewness of the responses. This data was run through the data
analysis tool SPSS. Responses that have a mean closer to five were deemed more aligned to the
needs of the industry, the lower the standard deviation the more consensus there was about the
particular scale of a soft skill, and the closer the skewness number is to zero the less skewed the
results are one way or another.
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Table 23
Mean and Standard Deviation of Likert Scale Individual Soft Skills
Individual Soft
Skills
Mean
Standard Deviation
Skewness
Work Under
Pressure
2.56
1.509
-.697
3
1.225
-2.100
Integrity and
Empathy
3.67
.500
-.857
Emotional
Intelligence
3.33
7.07
-.606
Innovative
ProblemSolving
In addition to mean, standard deviation, and skewness, it is also valuable to determine the
frequencies by which respondents chose each rating. Table 24 illustrates the Valid Percent
frequencies of each descriptor in the Likert scale.
Table 24
Valid Percents of Scale Descriptors
Scale
Individual
Soft Skills
Not
Aligned
Somewhat Not
Aligned
Indifferent to
the Soft Skill
in Our
Industry
Somewhat
Aligned
Perfectly
Aligned
Valid Percents
Work
Under
Pressure
11.1%
22.2%
0%
33.3%
33.3%
Innovative
Problem-
11.1%
0%
0%
55.6%
33.3%
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Solving
Integrity
and
Empathy
0%
0%
0%
33.3%
66.7%
Emotional
Intelligence
0%
0%
11.1%
44.4%
44.4%
Qualitative Alignment of Individual Soft Skills
The first embedded qualitative survey question for the alignment questions aimed to
ascertain the level of alignment of Individual Soft Skills to sustain the industries of the
respondents. Through a thematic analysis, a very pronounced theme arose in the manual coding
of the qualitative analysis. This theme was: High alignment of Individual Soft Skills but varied
between sectors. These themes were deductively developed, meaning that the researcher
analyzed responses that were aligned with a pre-existing framework of soft skills (Braun &
Clarke, 2006, p. 12).
Once the themes were established, the qualitative data were analyzed using Nvivo 15
software (Lumivero, 2024). Through this analysis, respondents cited that their industry needs
align with the Individual Soft Skill category because soft skills like communication, adaptability,
and emotional intelligence are essential skills in a candidate to sustain their workforces. This
theme analysis indicated a high alignment.
Quantitative Alignment of Collaborative Soft Skills
The next Likert scale question asked respondents to scale the Collaborative Soft Skills:
Communication, teamwork, global and cultural diversity, leadership skills, and business
etiquette. Table 25 illustrates the mean, standard deviation, and skewness of the responses. This
data was run through the data analysis tool SPSS. Responses that have a mean closer to five were
deemed more aligned to the needs of the industry, the lower the standard deviation the more
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consensus there was about the particular scale of a soft skill, and the closer the skewness number
is to zero the less skewed the results are one way or another.
Table 25
Mean and Standard Deviation of Likert Scale Collaborative Soft Skills
Collaborative
Soft Skills
Mean
Standard Deviation
Skewness
Communication
3.78
.441
-1.620
Teamwork
3.44
.527
.271
Global and
Cultural
Diversity
2.22
1.202
-.537
Leadership
Skills
3.33
.500
.857
Business
Etiquette
2.78
.833
-1.166
In addition to mean, standard deviation, and skewness, it is also valuable to determine the
frequencies by which respondents chose each rating. Table 26 illustrates the Valid Percent
frequencies of each descriptor in the Likert scale.
Table 26
Valid Percents of Scale Descriptors
Scale
Collaborative
Soft Skills
Not
Aligned
Somewhat
Not Aligned
Indifferent to
the Soft Skill
in Our
Industry
Somewhat
Aligned
Perfectly
Aligned
Valid Percents
Communication
0%
0%
0%
22.2%
77.8%
Teamwork
0%
0%
0%
55.6%
44.4%
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Global and
Cultural
Diversity
11.1%
11.1%
33.3%
33.3%
11.1%
Leadership
Skills
0%
0%
0%
66.7%
33.3%
Business
Etiquette
0%
11.1%
11.1%
66.7%
11.1%
Qualitative Alignment of Collaborative Soft Skills
The next embedded qualitative survey question for the alignment questions aimed to
ascertain the level of alignment of Collaborative Soft Skills to sustain the industry. Through a
thematic analysis and manual coding, some thematic soft skills that arose were teamwork and
communication. These themes were deductively developed, meaning that the researcher analyzed
responses that were aligned with a pre-existing framework of soft skills (Braun & Clarke, 2006,
p. 12).
Respondents noted that communication is a foundational soft skill; however, there is a
generational gap reinforcing the importance of non-digital communication, and that
communication is embedded in organizational culture. Next, teamwork is not just nice to have, it
is a requirement to sustain a functional workforce. A sub- theme that emerged is that leadership,
adaptability, and professionalism support the aforementioned theme.
Quantitative Alignment of Procedural Soft Skills
The next Likert scale question asked respondents to scale the Procedural Soft Skills:
Quantitative skills, flexibility for organizational change, critical thinking, ability to make
decisive decisions, and responsibility to get the job done. Table 27 illustrates the mean, standard
deviation, and skewness of the responses. This data was run through the data analysis tool SPSS.
Responses that have a mean closer to five were deemed more aligned to the needs of the
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industry, the lower the standard deviation the more consensus there was about the particular scale
of a soft skill, and the closer the skewness number is to zero the less skewed the results are one
way or another.
Table 27
Mean and Standard Deviation of Likert Scale Procedural Soft Skills
Procedural
Soft Skills
Mean
Standard Deviation
Skewness
Quantitative
Skills
2.22
1.394
-.146
Flexibility for
Organizational
Change
3.22
1.093
-1.289
Critical
Thinking
3.33
1.0000
-1.821
Ability to
Make Decisive
Decisions
3.22
.972
-1.600
Responsibility
to Get the Job
Done
3.33
1.0000
-1.821
In addition to mean, standard deviation, and skewness, it is also valuable to determine the
frequencies by which respondents chose each rating. Table 28 illustrates the Valid Percent
frequencies of each descriptor in the Likert scale.
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Table 28
Valid Percents of Scale Descriptors
Scale
Procedural Soft
Skills
Not
Aligned
Somewhat
Not Aligned
Indifferent to
the Soft Skill
in Our
Industry
Somewhat
Aligned
Perfectly
Aligned
Valid Percents
Quantitative
Skills
11.1%
22.2%
22.2%
22.2%
22.2%
Flexibility for
Organizational
Change
0%
11.1%
11.1%
22.2%
55.6%
Critical
Thinking
0%
11.1%
0%
33.3%
55.6%
Ability to Make
Decisive
Decisions
0%
11.1%
0%
44.4%
44.4%
Responsibility
to Get the Job
Done
0%
11.1%
0%
33.3%
55.6%
Qualitative Alignment of Procedural Soft Skills
The last embedded qualitative survey question for the alignment questions aimed to
ascertain the level of alignment of Procedural Soft Skills to sustain the industries of the
respondents. Through a thematic analysis and manual coding this theme emerged: Different
sectors value different alignments. These themes were deductively developed, meaning that the
researcher analyzed responses that were aligned with a pre-existing framework of soft skills
(Braun & Clarke, 2006, p. 12).
Once the themes were established, the qualitative data were analyzed using Nvivo 15
software (Lumivero, 2024). It became clear that respondents from the education sector stress
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autonomy, critical thinking, organization, and quantitative skills for operational success. On the
other hand, the respondents in healthcare also value critical thinking, but also emphasize rapid
decision-making and professionalism. Respondents in the construction sector value flexibility,
safety, and independent decision-making. These subthemes all evolved out of the major theme.
Quantitative Alignment of Soft Skill Categories: Individual, Collaborative, and Procedural
The last Likert scale question asked the respondent to scale the three categories of soft
skills: Individual, collaborative, and procedural. This data was run through the data analysis tool
SPSS. Table 29 illustrates the mean, standard deviation, and skewness, whereas a mean closer to
five is deemed more aligned with the needs of the industry and a lower standard deviation means
more consensus amongst the respondents. In addition, a skewness number closer to zero
indicates less skew either way.
Table 29
Mean and Standard Deviation of Likert Scale Soft Skills Gap
Category
Mean
Standard Deviation
Skewness
Individual
1.33
1.0000
1.071
Collaborative
1.67
1.581
.705
Procedural
1.67
1.581
.217
In addition to mean, standard deviation, and skewness, it is also valuable to determine the
frequencies by which respondents chose each rating. Table 30 illustrates the Valid Percent
frequencies of each descriptor in the Likert scale.
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Table 30
Valid Percents of Scale Descriptors
Scale
Category
Not
Aligned
Somewhat
Not Aligned
Indifferent to
the Soft Skill
in Our
Industry
Somewhat
Aligned
Perfectly
Aligned
Valid Percents
Individual
11.1%
66.7%
0%
22.2%
0%
Collaborative
22.2%
44.4%
0%
11.1%
22.2%
Procedural
33.3%
22.2%
0%
33.3%
11.1%
Conclusion
This action research study examined the relationship between the soft skills taught by the
West Greene School District and the soft skills most valued by the largest employers in Greene
County, Pennsylvania. Through a mixed methods concurrent embedded design, this study
triangulated quantitative data, analyzed through SPSS, with qualitative data, thematically
analyzed using NVivo 15 software, to ensure a comprehensive understanding of workforce needs
and the district’s current alignment with those needs.
The results of the study indicate that while there is a degree of alignment between the
district’s soft skills curriculum and employer expectations, notable distinctions emerged.
Communication, teamwork, and responsibility were consistently rated as essential across
industries and for both entry-level and professional roles. However, variations by sector were
also apparent. The education sector emphasized emotional intelligence and critical thinking;
healthcare employers prioritized rapid decision-making and professionalism; and construction
industry leaders placed significant importance on flexibility, independent problem-solving, and
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safety. Additionally, differences in the expectations for entry-level versus professional positions
highlighted the need for a differentiated approach in preparing students for various career
trajectories.
Quantitative analyses provided statistical insight into the ranking and alignment of
individual, collaborative, and procedural soft skills, while qualitative analyses offered rich,
contextual perspectives that underscored the complexity of workforce expectations. Although not
all quantitative findings yielded statistically significant results, the qualitative data provided
valuable nuance, reinforcing the need for a curriculum that is responsive to the diverse demands
of the local economy.
Summary
In sum, the findings from this study provide a critical foundation for enhancing the West
Greene School District’s soft skills curriculum. By addressing both the universally valued
competencies and sector-specific needs identified by local employers, the district can better
prepare its graduates to enter and sustain successful careers within the Greene County workforce.
These results not only inform curriculum development but also contribute to broader efforts
aimed at bridging the gap between education and employment, ensuring that students are
equipped with the competencies necessary to thrive in an evolving labor market. The following
chapter will discuss these findings in greater depth, interpreting their implications for practice,
policy, and future research, and offering recommendations for the continued development of a
responsive and effective soft skills curriculum.
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Chapter V
Conclusions and Recommendations
This Doctoral Capstone Action Research Project was designed to survey the top
employers, by total number of employees, of Greene County, Pennsylvania, in order to create an
updated positive behavior model for the West Greene School district that focuses on the soft
skills that these employers find most valuable. While the District already has a positive behavior
model, it is in need of a facelift that is rooted in action research that will provide the best
economic outcomes for its students. This chapter will share conclusions, recommendations, and
future implications as the research is centered on the following research questions:
Research Question 1
To what extent do the top Greene County business employers in the public and private
sectors value the soft skills that are being taught by the West Greene School District for entry
level positions?
Research Question 2
To what extent do current job openings and projected job openings in Greene County
compare to statistics from the US Bureau of Labor and Statistics?
Research Question 3
How do graduates with the desired soft skills, as determined by the West Greene School
District administration, compare to the soft skills identified by local business leaders to sustain
the workforce of Greene County, Pennsylvania?
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Conclusions
Research Question 1
The researcher asked, “To what extent do the top Greene County business employers in
the public and private sectors value the soft skills that are being taught by the West Greene
School District for entry level positions?” Quantitative data taken from the survey was analyzed
using SPSS. Qualitative data taken from the survey was analyzed using Nvivo 15. Based on the
data returned from SPSS, respondents ranked Individual Soft Skills as most important of the
three soft skills categories with a mean response of 1.6/3. With a standard deviation of .699,
there was consensus amongst respondents that Individual Soft Skills ranked either first or second
amongst respondents. The second ranked soft skill category was Collaborative Soft Skills with a
mean response of 2/3. With a standard deviation of .943, there was less consensus amongst
respondents of this ranking, but not enough to invalidate the consensus of the group of
respondents that Collaborative Soft Skills was the second most valued category of soft skills.
Lastly, the third and lowest ranked category of soft skill was Procedural Soft Skills with a mean
ranking of 2.4/3. With a standard deviation of .699, there was consensus that this is the lowest
ranked category of soft skills. However, it must be determined if the differences in these ranks
occurred at random or if there was a true statistically significant difference in the data. Therefore
a Friedman Test was administered. The goal of the Friedman Test was to indicate if a statistically
significant difference existed in the data or if the outcome was a result of chance. When
analyzing a Friedman Test, or the Wilcoxon Signed Rank Test, any p-value over .05 is not seen
as statistically significant; therefore, our p-value of .202 indicated that there are no real
differences between group medians and that the differences in rank most likely occurred by
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statistical chance. Therefore, the researcher cannot make definitive conclusions based on the data
collected from these survey questions.
Likewise, the qualitative data suggested split valuing amongst respondents. Respondents
pointed out that while Individual Soft Skills enhance the other categories of soft skills, it has its
own skill-specific drawbacks. Additionally, Collaborative Soft Skills are very difficult to teach in
the workplace, and while Procedural Soft Skills ensure organizational efficiency, people can get
better at them over time. These themes reinforce the notion that respondents do not conclusively
value one category of soft skills over another. Since it cannot be definitively ascertained which
category of soft skills as a whole is valued most by employers, we must dive deeper to determine
which soft skills from each category are valued most in order to offer suggestions of which soft
skills will provide the best grounds for a positive behavior model.
Individual Soft Skills
Quantitative data from these survey questions was analyzed using SPSS. The resulting
analysis has shown that “Work Under Pressure” returned a mean value of 2.5/4 soft skills in this
category with a standard deviation of 1.269, “Innovative Problem-Solving” returned a mean
value of 2/4 soft skills in this category with a standard deviation of .943, “Integrity and
Empathy” returned a mean value of 2.2/4 soft skills in this category with a standard deviation of
1.135, and “Emotional Intelligence” returned a mean value of 3.3/4 soft skills in this category
with a standard deviation of .823. These averages and standard deviations reflect a noncommittal
rank valuation for each of the soft skills amongst respondents. Not one soft skill stuck out as
more or less valued than another and the standard deviations reflect moderate to strong
consensus of those values. The results of the Friedman Test, with a p-value of .118, reflect that
the outcome of this dataset is more than likely a result of chance. Any p-value over .05 indicates
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that there is no evidence of a statistically significant difference between the soft skill and any
differences in value are more than likely due to a random chance and does not show a true or
statistically significant consensus amongst respondents; therefore, no further tests were
completed because consensus amongst ranks could not be statistically concluded. Therefore, the
researcher cannot make definitive conclusions based on the collected data because it is
statistically inconclusive.
In surveying respondents, it was also important to identify any potential Individual Soft
Skills that are valued by employers that were not listed by the researcher on the survey in order
to have a holistic view of the Individual Soft Skills valued by each employer. Using Nvivo 15 to
analyze qualitative data themes from the survey, it became clear that respondents valued different
soft skills in professional positions compared to entry-level positions, and that different sectors
valued different Individual Soft Skills. Respondents noted that in professional level positions
Individual Soft Skills that are valued are “Leadership,” “Problem-Solving,” “Initiative,” and
“Independent Decision-Making;” whereas, for entry level positions, respondents indicated that
Individual Soft Skills like “Communication,” “Teamwork,” “Adaptability,” and “Time
Management” were valuable. On the other hand, respondents from the education sector valued
“Emotional Intelligence” and “Empathy” as valuable Individual Soft Skills, and respondents
from business sectors and service industries value “Stress Management,” “Reliability,” and
“Initiative” as important Individual Soft Skills. While the qualitative input added an additional
layer of data, it did not conclusively indicate the preference of any additional soft skills over the
soft skills indicated in the survey.
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Collaborative Soft Skills
The next set of data to be reviewed is the resulting data on Collaborative Soft Skills. In
analyzing the data, it has shown that “Communication” returned a mean value of 1.1/5 soft skills
in this category with a standard deviation of .316, “Teamwork” returned a mean value of 2.3/5
soft skills in this category with a standard deviation of .823, “Leadership Skills” returned a mean
value of 3.4/5 soft skills in this category with a standard deviation of .966, “Business Etiquette”
returned a mean value of 3.6/5 soft skills in this category and a standard deviation of 1.075, and
“Global and Cultural Diversity” returned a mean value of 4.6/5 soft skills in this category with a
standard deviation of .966. Based on the raw averages combined with the standard deviations,
“Communication” was valued most with high consensus. When the Friedman Test was
completed on these skills, a p-score of <.001 was found, meaning that these numbers did not
happen by mere coincidence and that there is some actionable data in this dataset. There is a
statistically significant chance that the respondents valued certain Collaborative Soft Skills over
others. Therefore, a Wilcoxon Signed Rank Test was completed on each Collaborative Soft Skill
against one another to find which soft skills actually ranked highest.
When analyzing a Wilcoxon Signed Rank Test, you must look at the “Z- Score” and
“p-score” of each of the comparisons. The Z- Score measures how many standard deviation
points away from the mean of zero that the data returned. Therefore, the larger the number, the
more statistically significant the comparison and higher likelihood that most of the respondents
felt one way and that numbers were less likely skewed by extreme values (Welkowitz, 2011, p.
92). When evaluating the returns from SPSS, the researcher must use the absolute value of the
Z-Score. The indication in the SPSS note will denote whether the Z- Score is “based on negative
ranks” or “based on positive ranks.” If the Z-Score is based on negative ranks, then the second of
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the two in the comparison group is the more likely choice, and if the Z-score is based on positive
ranks, then the first of the two in the comparison group is the more likely choice. When
evaluating the two-tailed p-value, anything less than .05 is considered a significant correlation
and extremely likely to occur (Welkowitz, 2011, p. 127). When evaluating these two scores
together, the Z-Score informs you which of the two compared soft skills was chosen more and a
p-score < .05 informs you the likelihood that the mean was not influenced by extreme outliers or
that it is the true choice of most respondents. First, the test determined that “Communication”
was ranked higher than “Teamwork” with a Z-Score of 2.489 and a two-tailed p-score of .013,
meaning that respondents do, in fact, rank “Communication” higher than “Teamwork”. Then,
the test determined that “Communication” overwhelmingly beat out “Global and Cultural
Diversity” with a Z- Score of 2.877 and a two-tailed p-score of .004 indicating that there is a
significant correlation to determine that respondents preferred “Communication” over “Global
and Cultural Diversity.” Next, “Communication” beat out “Leadership Skills” with a Z- Score of
2.871 with a two- tailed p-score of .004. This means that respondents overwhelmingly chose
“Communication” over “Leadership Skills”. “Communication” also outranked “Business
Etiquette" with a Z-Score of 2.831 and two-tailed p-score of .005. It must be noted that
“Communication” was seemingly the most obviously chosen soft skill of any soft skill in any of
the three categories. The next Collaborative Soft Skill to outrank another was “Teamwork.”
“Teamwork” outranked “Global and Cultural Diversity” with a Z-Score of 2.859 and two-tailed
p-score of .004, meaning that “Teamwork” was beyond a statistical significance chosen over
“Global and Cultural Diversity.” “Teamwork” was chosen over “Leadership Skills” with a
Z-Score of 1.998 and a two-tailed p-score of .046. Again, this p-score shows that “Teamwork”
was the clear choice between the two. Then, “Teamwork” outranked “Business Etiquette” with a
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Z-Score of 2.021 and a two-tailed p-score of .043. This p-score indicates that the rank was true
amongst respondents. Next, “Leadership Skills” outranked “Business Etiquette” with a Z-Score
of .263 and a two-tailed p-score of .793, indicating that “Leadership Skills” cannot be
definitively ranked higher than “Business Etiquette” because it returned a p-score over .05,
indicating that the rank could have been a result of extremes in the data. Then “Leadership
Skills” outranked “Global and Cultural Diversity” with a Z-Score of 2.235 and a two-tailed
p-score of .025 indicating that “Leadership Skills” was the clear choice amongst respondents.
The last Collaborative Skill to outrank another was “Business Etiquette,” outranking “Global and
Cultural Diversity” with a Z-Score of 1.999 and a two-tailed p-score of .046. This indicates that
respondents verifiably chose “Business Etiquette” over “Global and Cultural Diversity.” “Global
and Cultural Diversity” did not outrank any of the Collaborative Soft Skills. The Z-Scores and
p-scores of the Collaborative Soft Skills indicate that the respondents overwhelmingly, in a
statistically verifiable way, value “Communication” above the other soft skills of the category.
Therefore it is the suggestion of the researcher, based on this data return, that a positive behavior
model must be rooted in “Communication” first.
In surveying respondents, it was important to identify any potential Collaborative Soft
Skills that were valued by employers that were not listed by the researcher on the survey in order
to have a holistic view of the Collaborative Soft Skills valued by each employer. Using Nvivo 15
to analyze qualitative data themes from the survey, it became clear that “Communication” is
valued by each industry because of its interplay between teaming and mentorship opportunities.
While this soft skill is not new or different from the pre-identified list that was aggregated for
respondents, the qualitative data reinforced the quantitative data that “Communication” was the
highest valued Collaborative Soft Skill. The second theme that “Leadership” is an expected skill
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at all levels of tenure does not add to our aggregated list of Collaborative Soft Skills. While the
qualitative questions did not add to the list, it reinforced the value of “Communication” as an
integral soft skill to each industry, reinforcing the importance of its inclusion in the positive
behavior model.
Procedural Soft Skills
The next dataset to be examined was Procedural Soft Skills. The resulting analysis of the
data has shown that “Responsibility to Get the Job Done” returned a mean value of 1.89/5 of soft
skills in this category with a standard deviation of 1.269, “Critical Thinking” returned a mean
value of 2.4/5 of soft skills in this category with a standard deviation of 1.350, “Ability to Make
Decisive Decisions” returned a mean value of 2.9/5 of soft skills in this category with a standard
deviation of .876, “Flexibility for Organizational Change” returned a mean value of 3.2/5 of soft
skills in this category with a standard deviation of .919, and “Quantitative Skills” returned a
mean value of 4.3/5 of soft skills in this category with a standard deviation of 1.494. Based on
the raw averages combined with the standard deviations, “Responsibility to Get the Job Done”
was valued most with but not with a very high consensus. When the Friedman Test was
completed on these skills, a p-score of .002 was found, meaning that these numbers should result
in actionable data. There is a statistically significant chance that the respondents valued certain
Procedural Soft Skills over others, meaning that a Wilcoxon Signed Rank Test was also
administered.
When analyzing a Wilcoxon Signed Rank Test, you must look at the “Z- Score” and
“p-score” of each of the comparisons, as previously noted. The Z- Score measures how many
standard deviation points away from the mean of zero that the data returned. Therefore, the larger
the number, the more statistically significant the comparison and higher likelihood that most of
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the respondents felt one way and that numbers are less likely skewed by extreme values
(Welkowitz, 2011, p. 92). When evaluating the returns from SPSS, the researcher must use the
absolute value of the Z-Score. The indication in the SPSS note will denote whether the Z- Score
is “based on negative ranks” or “based on positive ranks.” If the Z-Score is based on negative
ranks, then the second of the two in the set is the more likely choice, and if the Z-score is based
on positive ranks, then the first of the two in the set is the more likely choice. When evaluating
the two-tailed p-value, anything less than .05 is considered a significant correlation and
extremely likely to occur (Welkowitz, 2011, p. 127). When evaluating these two scores together,
the Z-Score informs you which of the two compared soft skills was chosen more and the p-score
informs you the likelihood that the mean was influenced by extreme outliers or if it is the true
choice of most respondents. Therefore, a Wilcoxon Signed Rank Test was completed on each
Procedural Soft Skill as a comparison against one another to find true rank that was not
determined by chance. First the test determined that “Responsibility to Get the Job Done” was
ranked higher than “Quantitative Skills” with a Z-Score of 2.534 and a p-score of .011, meaning
that respondents do, in fact, rank “Responsibility to Get the Job Done” higher than Quantitative
Skills. Then, the test determined that “Responsibility to Get the Job Done” largely beat out
“Flexibility for Organizational Change” with a Z- Score of 2.228 and a two-tailed p-score of .026
indicated that there is likely a significant enough correlation to determine that respondents
preferred “Responsibility to Get the Job Done” over “Flexibility for Organizational Change”.
Next, “Responsibility to Get the Job Done” beat out “Ability to Make Decisive Decisions” with a
Z- Score of 2.145 with a two- tailed p-score of .032. This means that there is an excellent chance
that “Responsibility to Get the Job Done” is actually more valued than “Ability to Make
Decisive Decisions” amongst respondents. Respondents seemed to rank “Responsibility to Get
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the Job Done” higher than “Critical Thinking” with a Z-Score of .889; however, with a twotailed p-score of .374, it cannot be statistically verified as higher ranked in each case. The next
Procedural Soft Skill, “Ability to Make Decisive Decisions”, outranked “Quantitative Skills” and
“Flexibility for Organizational Change” with respective Z-Scores of 1.813 and .690; however,
with respective two- tailed p-scores of .070 and .490, the researcher cannot guarantee anything
more than coincidence between respondents. “Critical Thinking,” the next Procedural Soft Skill,
outranked “Quantitative Skills” with a Z-Score of 2.265 and a p-score of .024, meaning that it is
clear that “Critical Thinking” outranked “Quantitative Skills” amongst respondents. Although
“Critical Thinking” seemingly outranks “Flexibility for Organizational Change” and “Ability to
Make Decisive Decisions,” it cannot be proven with a two- tailed p-score of .158 and .437
respectively. The last Procedural Soft Skill to outrank at least one other Procedural Soft Skill,
“Flexibility for Organizational Change” outranked “Quantitative Skills” with a Z-Score of 1.658,
but it cannot be proven with consensus from respondents with a two- tailed p-score of .097.
Quantitative Skills did not outrank any of the Procedural Soft Skills. Therefore the consensus,
highest ranked Procedural Soft Skill was “Responsibility to Get the Job Done,” which aligns
with the means from the respondents. Therefore, the researcher can conclude that a positive
behavior model should include “Responsibility to Get the Job Done.”
In surveying respondents, it was important to identify any potential Procedural Soft Skills
that are valued by employers that were not listed by the researcher on the survey in order to have
a holistic view of the Procedural Soft Skills valued by each employer. Using Nvivo 15 to analyze
qualitative data themes from the survey, it became clear that Procedural Soft Skills are
non-negotiable soft skills to a successful workforce, but the consensus amongst respondents
varied in terms of which soft skills were non-negotiable to specific industries. Respondents in the
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education sector noted that “Time Management” was an important Procedural Soft Skill that
could have been included, while respondents from the healthcare field indicated that “Informed
Decision-Making,” “Consistency,” and “Professional Standards” are procedural-type soft skills
of high importance. Then, respondents from the construction sector indicated “Safety” and
“Flexibility” as important soft skills that are key to the industry. Whereas these added soft skills
seemed important to respondents, it is clear from quantitative data that “Communication” is of
the highest importance and value amongst respondents. While respondents added
“Communication” to this soft skill category through their qualitative responses, it does not take
away from the quantitative data suggesting the importance of “Responsibility to Get the Job
Done.” It only reinforces “Communication’s” place in the positive behavior plan.
Based on the results from the respondents, it must be noted that only the rank order from
Collaborative and Procedural Soft Skill categories could be verified to not be a result of skewed
numbers. Therefore, the researcher will only provide conclusions and recommendations from
those two datasets as it pertains to the first research question. The highest ranked Collaborative
Soft Skill was “Communication” and the highest ranked Procedural Soft Skill was
“Responsibility to Get the Job Done.” Based on this feedback from respondents, the West Greene
School District will certainly use these two soft skills as the cornerstone of its positive behavior
support plan moving forward.
Research Question 2
The researcher asked, “To what extent do current job openings and projected job
openings in Greene County compare to statistics from the US Bureau of Labor and Statistics?”
The results from this question will allow the researcher to determine to what degree the labor
market of the respondents is representative of the labor market of the area as a whole in terms of
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their projected needs. An overwhelming majority of respondents were from the education sector
meaning that only 20% of the respondents were from the construction sector, while 10% were
from health care and social assistance sectors. While this is very clearly not representative of
Greene County employers, it does say a great deal about the willingness of local school districts
and intermediate units to work and collaborate with one another. Also, 70% of the respondents
have between 50 and 200 employees. In a county with 677 total employer establishments and
9,637 employed people, the average employer establishment has roughly 14 employees that have
an expected year-over-year growth of 2.78% (Data USA, 2024). Therefore, a reasonable observer
can ascertain that the US Bureau of Labor and Statistics would expect these industries to grow
between 1.39 and 5.56 people over the next year. Based on the feedback of respondents,
respondents are expecting between four and five openings needed to be filled within the next
year and five year projections vary. With this data being taken into consideration, Greene
County, Pennsylvania, and the respondents of this survey seem to be fairly representative of each
other.
Research Question 3
The researcher asked, “How do graduates with the desired soft skills, as determined by
the West Greene School District administration, compare to the soft skills identified by local
business leaders to sustain the workforce of Greene County, Pennsylvania?” Respondents were
asked Likert scale style questions with zero equaling “Not Aligned,” one equaling “Somewhat
Not Aligned,” two equaling “Indifferent to the Soft Skill in Our Industry,” three equaling
“Somewhat Aligned,” and four equaling “Perfectly Aligned.” Therefore, means derived from
SPSS closer to four illustrate higher alignment. Standard deviations were also reported from
SPSS. For Likert scale questions, standard deviation shows how clustered responses are to the
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mean, and the higher the standard deviation, the more scores are spread out with less consensus.
Valid Percent frequencies were also reported in an effort to compare the means and the frequency
of each Likert response. Comparing these two data points will determine if there was consensus
amongst respondents. Along with SPSS to analyze quantitative data, Nvivo 15 software was used
to analyze qualitative data for each soft skill category to determine a deeper understanding of the
alignment between the soft skills listed and the needs of each sector. First, each soft skill
category was evaluated but the results came back low and relatively inconclusive. Individual Soft
Skill returned a mean value of 1.33, a standard deviation of 1 and a skewness of 1.071. Since the
skewness indicated that the mean is actually higher than the median value this leads the
researcher to conclude that there is a consensus of low value for this category. The next category
analyzed was Collaborative Soft Skills, which returned a mean of 1.67, a standard deviation of
1.581, and a skewness of .705. This leads one to conclude that there is moderate to low
consensus amongst respondents. The same applies to the third soft skill category: Procedural Soft
Skills. With a mean valuation of 1.67, a standard deviation of 1.581, and a skewness of .217, the
same logic applies as Collaborative Soft Skills. With this being said, there is inconclusive data to
suggest that one group is valued more so than the others. Therefore, each soft skill must be
evaluated to determine their overall value to employers.
Individual Soft Skills
The first group of soft skills that were analyzed for their relative importance to local
employers were the Individual Soft Skills. The mean for “Work Under Pressure” was 2.56, the
standard deviation was 1.509, and the skewness was -.697. While the results of this data indicate
that respondents viewed “Work Under Pressure” between somewhat indifferent and somewhat
aligned, the standard deviation in combination with the negative skew indicate that while some
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respondents rated it low, a notable number of respondents rated it higher leading the researcher to
conclude that there is a mixed perception amongst respondents as indicated in Table 24. The next
soft skill to be analyzed was “Innovative Problem-Solving.” The reported mean was 3, the
standard deviation was 1.225, and the skewness was -2.100. While the respondents indicated, on
average, that they somewhat valued this soft skill, the standard deviation and skewness indicated
there was no real consensus amongst the respondents as some respondents marked it as very
important while others, not important at all, as shown in Table 24. The third soft skill that was
analyzed was “Integrity and Empathy,” returning a mean of 3.67, a standard deviation of .500,
and a skewness of -.857. Compared to the other Individual Soft Skills, “Integrity and Empathy”
returned consensus that it is a valuable soft skill to local industries. The last soft skill of this
grouping to be analyzed was “Emotional Intelligence.” This soft skill returned a mean of 3.33, a
standard deviation of 7.07, and a skewness of -.606. The returns from this data did not indicate
any consensus towards the mean and therefore unusable. From the embedded qualitative
question, it was the consensus of respondents that Individual Soft Skills as written showed high
consensus; however, this could not be verified in all cases with quantitative data. Based on
quantitative and qualitative returns, there was consensus that “Integrity and Empathy” is a
valuable soft skill in its employees. Since this is the only definitive data to indicate the
importance of an Individual Soft Skill, the West Greene School District should use this soft skill
in its positive behavior plan.
Collaborative Soft Skills
The next group of soft skills that were analyzed for their relative importance to local
employers were Collaborative Soft Skills. The mean for “Communication” was 3.78, the
standard deviation was .441, and the skewness was -1.620. This means that “Communication” is
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between somewhat and perfectly valued with relatively high consensus. The negative skewness
indicates that the median is slightly higher than the mean; however, “Communication” is very
valuable to employers. “Teamwork” returned a mean of 3.44 with a standard deviation of .527
indicating that it is the consensus of respondents that “Teamwork” is valuable. The positive
skewness indicates that the mean is slightly less than the actual median; however, the value for
“Teamwork” is high enough with enough consensus to possibly include it in a positive behavior
plan for students. Next, “Global and Cultural Diversity” returned a mean of 2.22 with a standard
deviation of 1.202 and skewness of -.537, indicating that this soft skill not only lacks consensus,
but it also lacks value in the eyes of the top employers in the area. Next, Leadership Skills
returned a mean of 3.33 with a standard deviation of .500 and a skewness of .857. This indicates
that “Leadership Skills” are valued with consensus. The last Collaborative Soft Skill analyzed
was “Business Etiquette.” This soft skill returned a mean of 2.78, standard deviation of .833, and
a skewness of -1.166. The negative skewness indicates that the mean is slightly higher than the
mean with relatively high consensus; therefore, “Business Etiquette” could be of value in a
positive behavior plan. While the quantitative data indicates that there is some consensus
between a few Collaborative Soft Skills, the qualitative data reinforced the importance of those
soft skills and provided some sub-themes that reinforce the importance of Collaborative Soft
Skills.
Procedural Soft Skills
The next set of soft skills that were evaluated were Procedural Soft Skills. The first
Procedural Soft Skill was “Quantitative Skills.” This soft skill returned a mean value of 2.22, a
standard deviation of 1.394, and a skewness of -.146. This indicates very little consensus in value
for this soft skill. The next soft skill “Flexibility for Organizational Change” returned a mean
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value of 3.22 with a standard deviation of 1.093 and skewness of -1.289. These numbers indicate
that while the soft score averages highly, there is little consensus amongst respondents
determining its actual value. Next, “Critical Thinking” returned a mean value of 3.33 with a
standard deviation of 1 and skewness of -1.821. These numbers indicate a small amount of
consensus based on the skewness leaning towards high median valuations. “Ability to Make
Decisive Decisions” returned a mean value of 3.22. The standard deviation indicates that there is
moderate consensus amongst respondents and the skewness indicates that the median value is
higher than the mean. This indicates, as posited by Table 28, that there is certainly value in this
soft skill. The same holds true for the final Procedural Soft Skill: Responsibility to Get the Job
Done. This soft skill returned a mean value of 3.33, standard deviation of 1, and a skewness of
-1.821. The logic of this data would be the same as “Critical Thinking” and informs the
researcher of it higher than stated value. The qualitative questions indicated a high alignment of
value between the employer and the listed soft skills.
The analysis of Research Questions 1, 2, and 3 reveals several nuanced insights into the
alignment between soft skills valued by Greene County employers and those emphasized in the
West Greene School District. While quantitative data provided a measurable perspective on
employer preferences, qualitative responses added critical context to these findings, highlighting
sector-specific priorities.
In regards to the first research question, although the overall ranking of the three soft skill
categories, Individual, Collaborative, and Procedural, suggested a trend, the Friedman Test
revealed no statistically significant differences among them, indicating that employers may view
all three as relatively comparable in importance. Qualitative data supported this ambiguity,
noting that skill categories are interdependent. However, within each category, clearer
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preferences emerged. Specifically, “Communication” in the Collaborative Soft Skills category
and “Responsibility to Get the Job Done” in the Procedural Soft Skills category emerged as
statistically significant, verifiable preferences. These findings suggest that these two skills should
serve as foundational elements in any behavior or soft skills curriculum.
Next in regards to the second research question, while there was overrepresentation from
the education sector, the hiring projections from survey participants were consistent with the
U.S. Bureau of Labor Statistics trends, suggesting a moderate degree of representativeness. The
feedback also highlights a strong willingness among local educational employers to engage in
regional workforce development conversations.
Lastly in regards to the third research question, the alignment between graduates’ soft
skills and employer expectations yielded mixed results. While overall means indicated moderate
alignment, high standard deviations and skewness pointed to inconsistencies in perception
among respondents. Notably, “Integrity and Empathy,” “Communication,” and “Responsibility
to Get the Job Done” stood out as skills with both high mean values and relative consensus,
suggesting they are more widely valued across sectors. Qualitative themes reinforced these
quantitative findings, especially the primacy of “Communication” and “Responsibility” as core
workplace competencies.
Overall, the study concludes that while employers in Greene County recognize the value
of a range of soft skills, only a select few demonstrate statistically significant consensus across
respondents. These results offer practical direction for the West Greene School District to
prioritize specific soft skills like “Communication,” “Responsibility to Get the Job Done,” and
“Integrity and Empathy,” within its positive behavior and workforce preparation initiatives. This
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alignment may ultimately enhance graduate preparedness and better serve the region’s evolving
economic needs.
Limitations
While this study was designed to provide a comprehensive understanding of the
alignment between soft skills valued by local employers and those taught within the West Greene
School District, several limitations must be acknowledged that affect the interpretation and
generalizability of the findings. These limitations span methodological, geographic, and
analytical domains and are important to consider when applying the results beyond the scope of
this study. Specifically, challenges related to sample size and response rate, geographic and
economic specificity, reliance on self-reported data, potential for researcher bias, and limitations
in mixed methods integration all impacted the depth and breadth of the conclusions that could be
drawn. The following subsections outline each of these limitations in detail and provide insight
into how they may have influenced the study's results.
The first apparent limitation of this study is its limited sample size and low response rate.
Initially, only the top 10 on the list of 50 were sent surveys to be completed; however, the
researcher soon began to realize that the scope would need to be broadened in order to get ten
respondents. Therefore, more potential respondents were notified and previous respondents were
reminded. I repeated this cycle until I had notified the top 50 employers, which had exhausted
the list in Appendix A. At that point, potential respondents were reminded and kindly asked to
take the survey until the 10th survey response had been submitted. This did, however, create a
response rate of 20%. This lower response rate than previously anticipated, limits the
generalizability of the findings and may not represent the full spectrum of employer perspectives
across the county.
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The next limitation of the study is the geographic and economic specificity. While this
study aimed to help the West Greene School District create a positive behavior plan for its
district, it must be understood that there is limited transferability in the findings because Greene
County, Pennsylvania is a very rural region with a unique economic profile. Therefore, findings
might not easily transfer to urban or suburban school districts or areas more economically
diverse.
After the limitation of geographic specificity, the next limitation is in self-reported data.
The survey relies solely on data that is self-reported which may include bias. In addition to
self-reported data, data collected from each employer may have been collected from people of
varying backgrounds, educational levels, and positions within the company/school district. This
increases the likelihood of data that is inconsistent across respondents as scientific controls could
not be further implemented in the collection of data to maintain a higher degree of anonymity.
While the data that was submitted was submitted by people working in each of those industries
and were employed by the employer, specific and consistent employee positions were not
requested to fill out the survey.
In addition to self-reporting bias, there is also the potential for researcher bias and mixed
methods integration challenges. Despite the use of the Nvivo 15 software, qualitative analysis is
susceptible to researcher bias in theme development and coding. In addition, respondents were
unable to fully differentiate between the three categories of soft skills, leading to overlap in skill
reporting in qualitative questions. This limited the potential interpretation of data because solid
outcomes could not be aggregated from the responses. In addition to these types of biases,
respondents from the education sector responded at 70% of the overall participation meaning that
certain soft skills might be accounted for more than others based on the nature of the sector.
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In conclusion, while the study offers valuable insights into the alignment of soft skills
between local industry expectations and school-based instruction, the aforementioned limitations
underscore the need for caution when interpreting its findings. The small sample size, regional
specificity, and inherent biases within self-reported and researcher-analyzed data all contribute to
constraints in generalizability and replicability. These factors, combined with disproportionate
sectoral representation and overlapping soft skill interpretations, suggest that in further research
incorporating a broader sample, clearer role delineation amongst respondents, and more refined
qualitative coding practices would strengthen the applicability of the results. Despite these
limitations, this study serves as an important foundation for ongoing efforts to bridge educational
practices with workforce demands in rural communities like Greene County, Pennsylvania.
Recommendations for Future Research
While the findings of this study provide valuable insight into the alignment between local
employer expectations and the soft skills emphasized in the West Greene School District, several
opportunities exist to expand and strengthen future research in this area. As with many
exploratory studies, limitations in sample size, sector representation, and data collection methods
suggest important directions for continued investigation. Future studies should aim to engage a
broader and more diverse group of participants, adopt more targeted respondent roles, and
incorporate additional qualitative methods such as interviews or focus groups to enhance data
richness and triangulation. Furthermore, longitudinal and comparative research would deepen
understanding of how soft skills alignment evolves over time and across educational and
economic contexts. The following recommendations are offered to guide researchers seeking to
build upon the foundation of this study and extend its relevance across both rural and broader
workforce development settings.
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While it is not unique to this research study, future studies should aim for a larger and
more diverse sample. The goal of this study was to have ten respondents because the researcher
understood the potential limitations of the population. However, a larger sample size means that
more diverse voices will be heard in the data analysis. While ten was always the goal, having
70% of respondents from the education sector was not. In future studies, efforts need to be made
to have a better cross section, and more representative group of participants. This will avoid
overrepresentation of a single industry, which this study is. In addition, having a larger sample
size will increase the generalizability of results.
Next, future research might track and gather data from specific job roles or specify hiring
personnel as the main data contributors. This will provide a more consistent perspective on skill
importance in the hiring process, not just to the industry as a whole. This will reduce the
variability introduced by respondents’ differing organizational rolls or backgrounds.
If this study were to be replicated, additional qualitative data collection methods should
be employed to guarantee a higher level of triangulation of data. In doing this, it would limit the
misunderstanding that clearly took place in the data collection of this study. Respondents were
inadvertently going between soft skill categories in a way that made the results for the qualitative
questions mostly inconclusive. By adding in follow-up interviews or focus groups, the researcher
could gain a better understanding of employer needs and wants, beyond the survey responses.
This would in turn refine the integration of mixed methods as the appropriate tool used to gain
data from respondents. In addition, a team based coding of themes could be used to limit
researcher bias.
In addition to methodology recommendations, it is important to determine where this
research can go from here to potentially deepen the study as it is and to provide better breadth.
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Based on the conclusions gathered from data analysis, the West Greene School District can
implement a revised soft skills curriculum. Based on these revisions to the curricula, follow-up
studies could assess its effectiveness through pre- and post- measures, employer feedback, and
graduate success rates. These findings could be used to broaden the scope of the study using this
study as a blueprint. Urban and suburban populations could use this outline to add to the body of
research to compare and contrast their findings. Ultimately, based on the outcomes of this
research study and others that build upon it, researchers could generate and include longitudinal
studies to determine the overall effectiveness of this process over time. This research study is a
snapshot in time and is not reflective of historic economic or educational trends. Future research
could track the effectiveness of revised soft skills curricula over time, from this data, by
examining student outcomes and local employment rates. This would ultimately determine
whether alignment improvements actually influence workforce readiness and job placement.
In summary, this study lays the groundwork for understanding the relationship between
local workforce demands and soft skills instruction within a rural school district. However, to
build on this foundation and enhance both the depth and breadth of future research, intentional
methodological improvements and broader study scopes are necessary. Increasing sample
diversity, refining respondent roles, incorporating richer qualitative methods, and conducting
longitudinal assessments will strengthen the reliability, validity, and applicability of findings.
Furthermore, extending this research to include urban and suburban contexts can offer valuable
comparative insights and contribute to the development of scalable, data-informed soft skills
curricula. Ultimately, continued exploration of this topic will not only support regional
workforce readiness but also help educational institutions more effectively prepare students for
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the evolving demands of the 21st-century labor market, all based on the findings related to the
West Greene School District and the labor market of Greene County, Pennsylvania.
Summary
This Doctoral Capstone Project surveyed the local workforce, more specifically the top
employers in Greene County, Pennsylvania by number of employees in order to answer the
following research questions:
1. To what extent do the top Greene County business employers in the public and
private sectors value the soft skills that are being taught by the West Greene
School District for entry level positions?
2. To what extent do current job openings and projected job openings in Greene
County compare to statistics from the US Bureau of Labor and Statistics?
3. How do graduates with the desired soft skills, as determined by the West Greene
School District administration, compare to the soft skills identified by local
business leaders to sustain the workforce of Greene County, Pennsylvania?
The study reviewed survey responses from ten of the fifty top employers in Greene
County, Pennsylvania, in terms of total employed. A Google Form was sent out to these fifty
employers and ten responded for a total response rate of 20%, indicating what type of industry
they work in, the number of employees the business employs, the number of projected openings
the company will have, the soft skill that they most value, and a rank of soft skills from a
predefined list.
The survey results enabled the researcher to determine that there is not one group of soft
skills that are valued higher than other groups, but specific soft skills like “Communication,”
“Responsibility to Get the Job Done,” and “Integrity and Empathy” should be used a building
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blocks for positive behavior models and workforce readiness within the West Greene School
District.
Ultimately, the value of this study lies not just in the insights it provides into local
employer expectations, but in its call to action. By identifying key soft skills such as
“Communication,” “Integrity and Empathy,” and “Responsibility to Get the Job Done,” this
research offers a roadmap for aligning educational priorities with workforce demands. In an era
where rural schools face mounting pressures to prepare students for an uncertain economic
future, this study affirms that success begins not only with academic proficiency but with
personal and professional character. If embraced with intention, the findings of this study can
help school leaders forge stronger partnerships with industry, enhance curriculum relevance, and
ultimately, empower students with the tools to succeed in both work and life to bridge
classrooms and communities.
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APPENDICES
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Appendix A
Top 50 Employers in Greene County
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Appendix B
Informed Consent Statement
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Informed Consent
Title of Study: Are Our Graduates Prepared: Comparing West Greene School District
Graduates’ Skills to the Needs of Greene County Employers
KEY INFORMATION
You are being asked by Michael Hildreth, Dr. Stephanie Williams, and Dr. Bart Donley to
participate in a research study. Participation in the study is voluntary, and you may stop anytime.
The purpose of the study is to identify the soft skills that are needed of the local businesses in
Greene County, Pennsylvania. In addition, local businesses will provide feedback as to whether a
local school district is providing the workforce with potential employees with the pertinent soft
skills who are capable of gaining positions for these businesses to sustain the local economy.
In this study, you will be asked to answer survey questions about how your business values the
soft skills that a local school district values for its students for entry into your workforce, how
your current job openings and projections compare with the US Bureau of Labor and Statistics,
and the degree to which the needs of your workforce are being met by the soft skills valued by a
local district.
It will take approximately 20 minutes to complete the study.
The potential risks during the study are: Potentially revealing sensitive, competitive information
while being an unidentified responder; negative feedback could potentially impact how
businesses are generally perceived to outside stakeholders of the school district; and your
responses could help dictate policy or curriculum adjustments that you may not personally agree
with. In an effort to mitigate these potential risks the purpose of the research will be clearly
communicated, confidentiality and anonymity practices will be observed, you may skip
questions that you are uncomfortable answering, and honest and accurate responses will be
collected without repercussion from the research team. Remember, you may stop taking the
survey at any time. In addition, if you feel the need to talk with someone, you may contact the
PennWest Edinboro counseling center at 814-732-2252, or for emergencies, call 814-732-2911.
There are no direct benefits to participants from the research. It will help researchers better
understand the steps that the West Greene School District can take to graduate students who can
thrive in the current job market and to not leave Greene County upon high school or
postsecondary graduation to pursue non-local economic opportunities.
SECURITY OF DATA
The online study is completely anonymous; you will not be asked to give any information that
could identify you (e.g., name). The survey is NOT linked to IP addresses. Individual responses
will not be presented, just the aggregated data.
Remember, taking part in this study is voluntary. If, while taking the survey, you feel
uncomfortable or no longer want to participate, you may stop at any time. To stop taking the
survey, you may either:
(1) proceed to the last page of the survey and press “Submit,” or (2) if you wish
to exit the survey, close your browser completely.
There are no consequences if you decide to stop participating in this study.
There is no identifiable information collected from you during this study; all other information
from this study will be confidential within local, state, and federal laws. The PennWest
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University Institutional Review Board (IRB) may review the research records. The study results
may be shared in aggregate form at a meeting or journal, but there is no identifiable information
to be revealed. The records from this study will be maintained for a minimum of three (3) years
after the study is complete.
Your information collected in this research will not be used or distributed for future research,
even if all your identifiers are removed.
If you have questions about the research or a research-related injury, you can contact Dr.
Stephanie Williams at williams_s@pennwest.edu. If you have a question about your rights as a
research participant that you need to discuss with someone, you can contact the PenWest
University Institutional Review Board at InstReviewBoard@pennwest.edu.
If you would like a copy of this informed consent, please print this screen or contact Dr.
Stephanie Williams at williams_s@pennwest.edu. .
By clicking on the “I agree” box and continuing with the survey, you have acknowledged that
you have read the informed consent and are at least 18 years old. Also, you acknowledge that
you agree to participate in the study and have the right not to answer any or all the questions in
the survey. Finally, you understand your participation is entirely voluntary, and you may quit the
study at any time without penalty.
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Appendix C
IRB Approval