ANALYSIS OF SMALL GROUP READING INTERVENTION SUCCESS AT A RURAL
ELEMENTARY SCHOOL IN PENNSYLVANIA: A CASE STUDY
by
Kara L. Thorp
Slippery Rock University

A Case Study Presented in Partial Fulfillment
Of the Requirements for the Degree
Doctor of Education

Slippery Rock University, Slippery Rock, Pennsylvania
2025

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ANALYSIS OF SMALL GROUP READING INTERVENTION SUCCESS AT A RURAL
ELEMENTARY SCHOOL IN PENNSYLVANIA: A CASE STUDY
By
Kara L. Thorp

A Case Study Presented in Partial Fulfillment
Of the Requirements for the Degree
Doctor of Education
Slippery Rock University, Slippery Rock, PA
2025

APPROVED BY:
Whitney M. Wesley, D.Ed, Committee Chair
Professor, Slippery Rock University

Elizabeth S. LaGamba, EdD, Committee Member
Associate Professor, Slippery Rock University

Amy R. Orville, Ed.D., Committee Member
Assistant Professor, Slippery Rock University

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ABSTRACT
This quantitative quasi-experimental case study examined the effectiveness of two Tier 2
reading intervention strategies—teacher-led small group instruction and an adaptive computerbased program (HMH Waggle)—in improving reading outcomes among sixth-grade students at a
rural elementary school in Pennsylvania. The study aimed to address literacy challenges
commonly faced in rural settings, such as limited instructional resources, teacher shortages, and
underperformance on standardized assessments. Participants included 42 general education
students divided into two pre-existing classes: one received small group intervention from the
classroom teacher, and the other used the Waggle program. Both groups were assessed using the
Measures of Academic Progress (MAP) reading assessment before and after an 18-week
intervention period. The study compared growth in three key reading domains: reading
informational texts, reading literature, and vocabulary acquisition and use.
Findings indicated no statistically significant differences between groups in reading
informational texts or reading literature. However, students who received adaptive online
intervention demonstrated significantly greater gains in vocabulary acquisition and use compared
to those receiving small group instruction. Grounded in Self-Determination Theory and
Vygotsky’s Zone of Proximal Development, the study emphasizes the importance of motivation,
scaffolding, and differentiated instruction. The findings hold implications for rural educators and
policymakers seeking to implement effective, scalable reading interventions tailored to diverse
student needs. Recommendations for future research include exploring hybrid models, increasing
sample sizes, and examining long-term literacy outcomes.

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ACKNOWLEDGEMENTS
This dissertation would not have been possible without the guidance, support, and
encouragement of many individuals who have contributed to my journey both academically and
personally. First, I would like to thank my chair and committee for all their hard work throughout
the writing and research process. Dr. Whitney Wesley, all your help during this time has been
greatly appreciated. Dr. Elizabeth LaGamba and Dr. Amy Orville, I am grateful to have found
both of you to assist throughout this process as well. I am so thankful to have had the three of
you provide all the encouragement to complete my research!
To my family, thank you for being there for me and supporting my dreams. You have all been an
important part of my journey of furthering education, and always there to support me when
things got tough, and willing to plan a trip to destress after tough semesters. To my parents, thank
you for instilling in me the value of education and hard work. I will never be able to put into
words how lucky I am to have the support system that I do.
Thank you to my district who allowed me to conduct my research, and all my amazing
coworkers who have become some of my closest friends. Thank you for cheering me on,
checking in on me, and giving me the space and understanding I needed to see this project
through. Your encouragement, humor, and belief in me made even the most stressful days more
manageable. I am especially grateful for your willingness to listen, lend a hand, and celebrate
milestones along the way. 
Finally, I thank God for giving me the strength, perseverance, and clarity of mind to
complete this work. I am humbled and grateful for the opportunity to contribute to a field I am
deeply passionate about.

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TABLE OF CONTENTS
ABSTRACT………………………………………………………………………………3
Acknowledgments………….…………………………………………………………......4
List of Tables………………..…………………………………………………...…….....7
CHAPTER ONE: INTRODUCTION…….……………...…………………………….....8
Overview…………………………………………..……………………………8
Background………..………………………………........………………………8
Historical Context……………………………..…...…………………….8
Social Context……………………………………...…………………...12
Theoretical Context…………………………………...………………...14
Problem Statement……………………………………………………………...16
Purpose Statement………………………………………………………………17
Significance of the Study………………………………………...……………..17
Research Questions………………………………………………..……………19
Definitions………………………………………………………..……………..19
CHAPTER TWO: LITERATURE REVIEW………………………..…………………20
Overview………………………………………………………..………………20
Theoretical Framework…………………………………………..……………..20
Self-Determination Theory……………………………………………..20
Zone of Proximal Development Theory………………………………..22
Related Literature……………………………………………………………….23
Teacher-Led Small Group Interventions……………………………….24
Online and Technology Based Interventions……………...……………29
Comparative Analysis of Teacher-Led Versus Online Interventions…..33
HMH Into Reading Curriculum…………………………...……………41
Summary………………………………………...………………………………44
CHAPTER THREE: METHODS………………………...…………………………….45
Overview…………………………………………...……………………………45
Design………………………………………………..…………………………46
Research Questions…………………………………...…………………………47
Hypotheses……………………………………………...……………………….48
Participants and Setting……………………………………...…………………..48
Population………………………………………...……………………..48
Participants………….…………………………….…..………………....50
Setting…………………………………....……………...………………51
Instrumentation………………………………..………………………………..51
Procedures………………………..……………………………………………..52
Data Analysis……………...………………………………………………….....54
CHAPTER FOUR: FINDINGS ………………………………………………………57
Overview……………………………………………………….......…………57

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Research Questions……….……………………………………………….…57
Null Hypotheses ………….……………………….…………………………57
Descriptive Statistics……..…………………………………………………..58
Group A Descriptive Statistics……..……..……………………………..58
Group B Descriptive Statistics……..………..…………………………..61
Results …………………..…………………………………………………...64
Hypothesis 1……….……………………..……………………………..64
Hypothesis 2……….……………………..……………………………..65
Hypothesis 3……….……………………..……………………………..66
CHAPTER FIVE: CONCLUSIONS……………………………………………………67
Overview…………….…….………………………………...………………67
Discussion…..…..………..………………………………………………….67
Research Question 1……….……………………..……………………..67
Research Question 2……….……………………..……………………..69
Research Question 3……….……………………..……………………..70
Implications………….……………………………………...………………71
Limitations…………….……………………………………………………72
Recommendations for Future Research…………..…...…………….......….73
REFERENCES………………………………………………………………………….76
APPENDIX A…………...………………………………………………………………87
APPENDIX B……………………………………………………………...……………88

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LIST OF TABLES/FIGURES
Page
Table 1 Descriptive Statistics of MAPs scores for Group A ......................................................58
Table 2 Descriptive Statistics of Reading Information Texts scores for Group A .....................59
Table 3 Descriptive Statistics of Reading Literature scores for Group A ...................................60
Table 4 Descriptive Statistics of Vocabulary Acquisition and Use scores for Group A ............60
Table 5 Descriptive Statistics of MAPs scores for Group B ......................................................61
Table 6 Descriptive Statistics of Reading Informational Texts scores for Group B ..................62
Table 7 Descriptive Statistics of Reading Literature scores for Group B ..................................62
Table 8 Descriptive Statistics of Vocabulary Acquisition and Use scores for Group B ...........63
Table 9 Summary of t-Test Results for Reading Information Texts .........................................64
Table 10 Summary of t-Test Results for Reading Literature.....................................................65
Table 11 Summary of t-Test Results Vocabulary Use and Acquisition .....................................66

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CHAPTER ONE: INTRODUCTION
Overview
Reading proficiency is a cornerstone of educational success, yet many students in rural
schools continue to struggle with achieving grade-level standards. Recent data underscores this
challenge: in 2023, 60.4% of 6th-grade students at a rural Pennsylvania school scored at the
basic or below-basic level on the English Language Arts Pennsylvania System of School
Assessment (PSSA) exam, a rate significantly higher than the state average of 44.4%
(Pennsylvania Department of Education, 2024). This concerning trend underscores the need for
effective reading interventions, particularly in rural settings where limited resources and unique
demographic challenges can exacerbate disparities in educational outcomes. The purpose of this
study is to compare the growth of sixth grade students in a rural school, using small group
interventions and an adaptive computer program. The participants in this group are general
education students and range from performing below grade level to performing above grade
level. Progress will be measured using a diagnostic assessment and comparing growth between
the two intervention strategies. By examining their relative effectiveness, the research aims to
inform best practices and help educators address the persistent challenges that hinder literacy
development in these underserved communities.
Background

Historical Context

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The history of reading interventions reflects a continuous evolution shaped by
educational philosophies, policy changes, and evidence-based methodologies. Early foundational
efforts were influenced by Horace Mann in the 19th century, who emphasized the necessity of
universal public education to foster an informed and engaged learning experience for children.
Mann's vision underscored the importance of structured, accessible instruction for all, setting the
stage for later reforms for student success in reading (Eakin, 2000). His work laid the
groundwork for a more systematic approach to literacy instruction, ensuring that all children had
the opportunity to develop foundational reading skills.
In the late 19th century, the Progressive Education Movement, led by John Dewey,
emphasized child-centered learning and experiential education. His beliefs built off Horace
Mann’s idea of keeping children engaged in their learning. Dewey’s philosophy of learning
through real-world problem-solving influenced later educational interventions, including reading
programs that combined structured phonics with holistic approaches (Hayes, 2015). He
emphasized that learning should be student-centered, engaging, and connected to real-world
experiences rather than solely focused on rote memorization and skill drills. Progressive
educators believed that while essential reading skills—such as phonics, vocabulary, and
comprehension—were necessary, they should be taught in ways that encouraged student interest
and motivation. Mann and Dewey had a direct impact to American society, particularly in
addressing educational disparities and promoting individual and community development.
While individual philosophers made strides in the foundational development of reading
interventions, policy makers and educators began working together to find the best practices for
reading success in America. By the mid-20th century, structured phonics instruction gained
prominence, focusing on the systematic teaching of letter-sound relationships to improve

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decoding and spelling skills. This method addressed the limitations of earlier "look-say"
techniques and became a cornerstone for addressing reading challenges, particularly among
students with learning difficulties (Nikiforuk, 1993). However, the 1970s and 1980s introduced
the whole-language movement, which emphasized natural language acquisition and the joy of
reading through exposure to literature. While its intentions were admirable, critics noted that it
lacked the structured support necessary for students with limited linguistic exposure (Nikiforuk,
1993).
With a need for this structured support, new interventions systems were created and put
into practice, including Reading Wars, whole language instruction, and balanced literacy. A
prominent program also developed during this time was the Wilson Reading System, which
introduces the idea of breaking reading and spelling down into smaller skills involving letters
and sounds and then building on these skills over time. The Wilson Reading System employs a
sequential approach to teach decoding and spelling, particularly benefiting students with dyslexia
(Education Commission of the States, 1999). This highly structured program gave support to
learners with reading disabilities and shifted reading interventions to a more intensive and
systematic approach. This shift in reading instruction began the movement to create
individualized support to students who exhibited difficulties in reading.
In the early 2000’s, government policies continued to make strides in developing more
successful literacy programs. Specific initiatives like the No Child Left Behind Act further
shaped reading interventions by emphasizing accountability and standardized assessments. No
Child Left Behind was created to help the United States close the gaps in achievement, especially
targeting these economically disadvantaged areas. No Child Left Behind was initiated to support
standards-based education programs, and initiate Title 1 services in disadvantaged school

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districts. The success of No Child Left Behind has been mixed. In a study completed by Dee and
Jacob (2011), they revealed that while No Child Left Behind generated improvements in math
performance, they found that its impact on reading was more limited. The results from No Child
Left Behind highlighted ongoing challenges in implementing broad, effective literacy reforms,
and continued to leave America needing to develop successful reading instruction and
interventions.
In response to the lack of success with No Child Left Behind in reading development,
modern intervention programs have sought to balance foundational skill development. The
emergence of balanced literacy models, which integrate phonics-based instruction with authentic
reading experiences, reflects an effort to incorporate both explicit skill instruction and
meaningful literacy engagement. Additionally, evidence-based intervention frameworks such as
Response to Intervention (RTI) and Multi-Tiered Systems of Support (MTSS) have been
implemented to provide targeted reading interventions based on student needs. These models
recognize that students learn at different paces and require varying levels of support, combining
systematic phonics instruction, fluency-building strategies, and comprehension development to
ensure long-term reading success (Austin et al., 2019).
Societal impacts continue to propel changes in intervention strategies. With the COVID19 pandemic, there was a need to change the delivery of teaching due to schools moving to
remote learning. Teachers were no longer able to provide interventions in person and needed to
switch to online formats. Districts had to rely heavily on online intervention programs that could
be utilized at home, and not teacher directed. Teachers could use these online programs to
provide to students while they were at home, and the teacher could monitor student progress
through the program without seeing them in person. Research showed success in online

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programs that initiated interventions that were adaptive to student progress, and showed that
repeated reading interventions, when implemented online, can effectively enhance reading
fluency, maintaining consistency with in-person outcomes (Romig & Jetton, 2023). The use of
online intervention programs has continued to rise since returning to school after the COVID-19
shut down.
Throughout history, there have been numerous adaptations in reading interventions.
These changes include adapting instructions to meet the needs of the students, and instructional
techniques used during intervention time. There is a continued focus on adapting to diverse
learner needs and integrating technological advancements in reading education. The evolution of
reading interventions demonstrates an ongoing commitment to refining educational practices to
meet the diverse needs of learners while maintaining a structured yet engaging approach to
literacy instruction.
Social Context
Low proficiency scores on Pennsylvania state assessments prove the need for focused
literacy strategies, especially in rural schools (PA Department of Education, 2023). These
communities face unique literacy challenges due to socioeconomic factors, limited funding, and
teacher shortages, exacerbating educational inequities. These factors lead to both teacher and
administrator burnout due to the added workload and stress. (Klocko & Justis, 2019). These
conditions hinder students' ability to achieve reading proficiency and create obstacles to
implementing effective interventions (Rogers, 2023).
Tailored interventions like small group instruction and adaptive online programs have
shown promise in addressing these challenges. In a study by Stein et al. (2022), they demonstrate

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that tools such as Lexia and iStation improve reading skills while addressing resource limitations
in these underfunded schools. Lexia and iStation are two technology-based reading intervention
programs that function as Integrated Learning Systems (ILSs), providing adaptive, computerassisted instruction to students. These programs are particularly designed to support students at
risk for reading deficits by offering individualized, data-driven literacy instruction. Lexia is a
cloud-based literacy program that tailors instruction to each student's needs based on an initial
assessment and continuous performance monitoring. It is structured around six thematic strands:
phonological awareness, phonics, structural analysis, fluency, vocabulary, and comprehension.
The program integrates both digital instruction and teacher-guided lessons, making it a blended
learning model. iStation is another computer-adaptive literacy intervention program that provides
reading instruction through engaging digital content. Like Lexia, iStation begins with a
diagnostic assessment that determines the student's starting level, followed by customized
lessons that adapt to their progress. The program is built around the five core pillars of reading:
phonemic awareness, alphabetic knowledge, fluency, vocabulary, and reading comprehension.
iStation also offers supplemental teacher-led lessons for students who struggle with concepts
(Stein et al., 2022).
Furthermore, contemporary frameworks such as the Response to Intervention (RTI)
model provide a structured approach to literacy instruction by offering tiered support tailored to
individual student needs. RTI is a multi-tiered system designed to identify students at risk for
reading difficulties early and provide increasingly intensive interventions as needed. Research
has shown that students with learning disabilities benefit from targeted, supplemental reading
interventions beyond the core curriculum (Austin et al., 2019). These interventions, implemented
within RTI frameworks, help to remediate reading difficulties and prevent long-term academic

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failure. The multitiered system of RTI allows educators to implement evidence-based
interventions that range from general classroom instruction (Tier 1) to more intensive,
personalized interventions (Tier 2 and 3) (Austin et al., 2019). Tier 1 involves high-quality,
universal instruction that all students receive. A tiered level of learning emphasizes inclusive
teaching practices that aim to prevent learning difficulties from developing in the first place. For
students who continue to struggle, Tier 2 provides targeted, small-group interventions that
address specific skills, while Tier 3 offers individualized, intensive support (Robinson, 2013).
The RTI tiered structure is beneficial in rural schools, has been proven in multiple studies that
teachers need to manage diverse student abilities within a single classroom and cannot always
rely on specialized staff for additional support (Austin et al., 2019; Robinson, 2013). This model
has been particularly effective in rural settings, where its flexibility allows for maximizing
limited resources and fostering collaboration among educators (Capin et al., 2024). RTI fosters
collaboration and is a flexible model of providing interventions for students and meeting their
needs. The RTI model can be an effective intervention strategy to meet the needs of struggling
readers in rural areas.
This overview reveals that literacy interventions are not only tools for academic success
but also vehicles for societal advancement. By addressing systemic inequities and adapting to
diverse learner needs, reading interventions continue to play a critical role in fostering equity and
opportunity within educational systems and broader society.
Theoretical Context
The present study focused on reading interventions at a rural elementary school in the
form of small group and adaptive computer software. The use of these interventions is supported
by two primary theoretical frameworks: Self-Determination Theory (SDT), and Zone of

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Proximal Development (ZPD). Both theories provide insights into the motivation and cognitive
processes driving learning for students and will help support the research question of which
intervention provides the most reading success to students attending rural schools.
Self-Determination Theory (SDT) was developed by Deci and Ryan, and the theory
explores the psychological needs of competence, autonomy, and relatedness, which are critical
for fostering intrinsic motivation (Ryan & Deci, 2000). In educational settings, SDT emphasizes
the importance of creating environments that promote student choice, provide feedback to
enhance competence, and foster meaningful social interactions to satisfy relatedness needs
(Stone, Deci, & Ryan, 2009). Self-Determination Theory (SDT) provides a valuable framework
for understanding how reading interventions can be designed to enhance student motivation,
engagement, and long-term success in literacy development. When these needs are met,
individuals are more likely to be intrinsically motivated, persist in learning, and achieve higher
levels of engagement. Applying SDT to reading interventions helps educators create
environments that not only address cognitive skill development but also foster the motivation
necessary for sustained reading progress. Throughout this study, the teacher will work to create
an environment to inspire intrinsic motivation during intervention time that includes meaningful
engagement for students and providing purpose-driven reading activities.
The second theory to support the study is Zone of Proximal Development (ZPD). This
theory was developed by Lev Vygotsky and describes the space between what a learner can
accomplish independently and what they can achieve with guidance or collaboration (Doolittle,
1995). ZPD emphasizes the importance of scaffolding, where educators provide targeted support
to help students progress through tasks just beyond their current ability (Clapper, 2015). This
framework is highly relevant to this study’s focus on teacher-led small group instruction, as it

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supports differentiated strategies tailored to individual students’ learning needs and using online
programs that are tailored to each student’s specific needs. For example, the researcher will use
data from a diagnostic assessment to place students in groups with peers functioning on the same
reading level. The researcher will adapt the small groups to meet the needs in areas that need
improvement based on assessment results. Students who are using the online program for
intervention will receive an individualized instruction plan that will adapt the program to meet
their needs, based on their progress within the program. Research suggests that scaffolding
within the ZPD helps students internalize knowledge and skills, enabling them to achieve greater
independence over time (Silalahi, 2019).
In summary, this study is aimed to compare the success of sixth grade students in rural
schools when receiving Tier 2 reading interventions in small group, compared to students
receiving Tier 2 interventions using an adaptive computer program.
Problem Statement
Rural schools face a multitude of issues, including lack of funding, teacher shortages, and
a lack of technology access (Rogers, 2023; Klocko & Justis, 2019). Studies show a variety of
results between the success of using online reading intervention programs and the success of
using small group reading interventions for students in rural schools (Stein et al., 2022; Donegan
& Wanzek, 2021). There is no concrete research that has been done comparing the intervention
types for students who attend these rural schools. My research aims to see which reading
intervention type works best with this population.
This study is focused on sixth grade students at a rural elementary school in Pennsylvania
consistently averaging below average performance on English Language Arts Pennsylvania
System of School Assessment (PSSA) tests and continue to score under the state average,

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according to the PSSA results. The school has consistently been below the state average over the
last five years (Pennsylvania Department of Education, 2023). In 2023, 60.4% of 6th grade
students at a rural school in Pennsylvania scored either basic or below basic on the ELA PSSA
exam (Pennsylvania Department of Education, 2023). The school average is larger than the state
average of 44.4% of students scoring basic or below basic, showing the need for targeted
interventions. A change needs to occur within the district to help increase reading achievement
among students who attend this rural school.
Purpose Statement
The purpose of this quantitative quasi-experimental case study was to analyze and
compare reading intervention outcomes among two classes of 6th grade students in a rural school.
6th grade general education students in a rural school were chosen to complete the study. Students
were in two classes, taught by the researcher. Students received instruction using the Into
Reading curriculum in whole group and received intervention time in a small group. One of the
classes receiving online intervention with the online program Waggle served as the control
group, while the second class receiving small group intervention led by the general education
teacher served as the experimental group. The intervention groups were the independent variable.
Reading success was measured by performance in the pre- and post-test, which was performed
using the Measure of Academic Progress (MAPs) assessment. The MAP assessment served at the
dependent variable. At the end of the experiment, the average increase in the MAPs assessment
was compared to show which group had more growth over the course of 18 weeks.
Significance of the Study

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The study on reading interventions is significant because it addresses the pressing issue
of literacy disparities in rural schools and contributes to a broader understanding of effective
educational practices. Reading proficiency is a critical factor in academic success and societal
participation, yet rural schools often face unique challenges, such as limited funding, teacher
shortages, and high poverty rates, which hinder students' ability to achieve proficiency. Online
interventions can begin to target the needs of students, helping resolve the challenges.
The findings from this research will contribute both theoretically and empirically to the
field of reading interventions. By comparing the outcomes of small-group instruction and
adaptive computer-based programs, the study aims to identify the most effective strategies for
improving literacy outcomes in underserved rural settings. Studies from numerous researchers,
including Donegan and Wanzek (2021) have shown that small-group instruction offers targeted
and individualized support, enhancing reading comprehension and fluency. In contrast,
technology-based interventions, such as Lexia and iStation, have demonstrated efficiency and
adaptability in addressing the resource constraints typical of rural schools (Stein et al., 2022).
This research also holds broader societal implications. Addressing literacy disparities in
rural areas contributes to narrowing educational gaps, fostering community development, and
preparing students for active societal participation. The application of frameworks like the
Response to Intervention model provides scalable and evidence-based approaches to literacy
instruction, promoting equity in education systems (Kehoe & McGinty, 2023). Moreover, the
study's insights can inform educational policy and practice, supporting the development of
tailored interventions that accommodate the unique needs of rural learners.
In summary, this study is important not only for its potential to enhance literacy outcomes
in a specific rural district but also for its contributions to the broader knowledge base on effective

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reading interventions. It emphasizes the need for innovative and adaptable strategies that address
systemic inequities and prepare students for lifelong learning and civic engagement.
Research Questions
RQ1: Which intervention showed the most significant growth in reading informational
texts on the MAPs assessment?
RQ2: Which intervention showed the most significant growth in reading literature on the
MAPs assessment?
RQ3: Which intervention showed the most significant growth in vocabulary acquisition
and use on the MAPs assessment?
Definitions
1. Adaptive Computer-Based Intervention Programs- programs and resources that are
accessed online and designed to help readers improve their literacy skills and
accelerate learning. These programs adapt their activities based on student
performance to meet the needs the student is showing. (Cleaver, 2023).
2. Waggle- an adaptive computer-based program for Grades K–8 delivers adaptive,
personalized practice and instruction for students at all proficiency levels (HMH,
2022).
3. Small Group Reading Interventions- a type of differentiated instruction that involves
grouping three to five students based on their learning needs and other factors
(Corujo, 2024).

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Chapter 2: Review of Literature
Overview
The purpose of this study is to analyze and provide teachers with the most effective
reading intervention strategies to improve the practice of reading instruction in to improve
reading proficiency in 6th grade students in a rural school in Pennsylvania, comparing two
intervention strategies. 6th-grade students at the target school struggled to maintain proficient
reading scores on Pennsylvania System of School Assessment (PSSA) tests and continue to score
under the state average, according to the PSSA results (Pennsylvania Department of Education,
2024). The Literature Review presents the Theoretical Framework, Literature Review, and the
Summary of Findings.
Theoretical Framework
A systematic review of the literature was conducted to deepen understanding of using
Tier 2 interventions with 6th grade students at a rural elementary school in Pennsylvania. This
chapter provides theories to support the logistics behind Tier 2 interventions that are offered
during this study, along with theories to support why they are effective. Theories that are
analyzed are self-determination theory and zone of proximal development theory.
This study compares the success of sixth grade students when receiving Tier 2 reading
interventions in small group, compared to students receiving Tier 2 interventions using an
adaptive computer program. Both of these theories support the use of Tier 2 interventions,
regardless of format.
Self-Determination Theory

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Deci and Ryan's self-determination theory (SDT) is a prominent psychological
framework explaining human motivation and well-being. Self-determination theory is an
approach to human motivation and personality that uses tradition empirical methods while
employing an organismic metatheory that highlights the importance of humans evolved inner
resources for personality development and behavioral self-regulation (Deci and Ryan, 2000).
They believe that humans are inherently motivated to grow and engage in uninteresting tasks
when their meaning and value is understood (Deci and Ryan, 2000).
According to SDT, humans have three core psychological needs: competence,
relatedness, and autonomy. Competence is the belief that one can influence important outcomes.
Relatedness is the experience of having satisfied and supportive social relationships. Autonomy
concerns the experience of acting with a sense of choice, volition, and self-determination (Stone,
Deci, and Ryan, 2009).
In the context of education, SDT emphasizes creating learning environments that foster
intrinsic motivation by supporting needs, leading to more engaged, persistent, and self-motivated
learners. Contexts yield autonomous regulation if they are autonomy supportive, thus allowing
the person to feel competent, related, and autonomous. This will instill the highest level of
motivation (Stone, Deci, and Ryan, 2009). When students experience autonomy and are provided
opportunities to feel competent and connected, they are more likely to develop a sustained love
for learning. This is especially important to this study due to the population of students attending
the target school. In this rural district, 64.5% of the students enrolled are reported to be
economically disadvantaged (PA Ready Index, 2024). Additionally, a large percentage of
students are being raised by adults who are not their biological parents. This can lead to
inconsistency at home with these students and can equate to low morale in school. As a teacher

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in a rural district, the responsibility to inspire intrinsic motivation is vital for student success. The
researcher in this study had to ensure that they were making strides to build relationships with
their students to gain their trust and provide instruction/activities that allow the students to be
successful to help build this intrinsic motivation. Students who feel successful in the classroom
and respected by the teacher are more likely to work harder and develop that drive to success for
themselves when in an environment that promotes success.
Deci and Ryan’s Self-Determination Theory (SDT) provides a strong theoretical
foundation for the effectiveness of Tier 2 reading interventions, both in small-group settings and
online programs. SDT emphasizes that learners are intrinsically motivated when their
psychological needs for competence, relatedness, and autonomy are met (Deci & Ryan, 2000). In
Tier 2 interventions, whether conducted in small groups or through online adaptive programs,
these needs can be intentionally supported to enhance student engagement, persistence, and
literacy growth.
Zone of Proximal Development (ZPD) Theory
Vygotsky’s zone of proximal development theory (ZPD) describes the gap between what
a learner can accomplish independently and what they can achieve with guidance or
collaboration. ZPD theory emphasizes the importance of scaffolding, where a more
knowledgeable individual (such as a teacher or peer) provides support to help the learner
progress through tasks they could not complete alone (Clapper, 2015). Furthermore, the region of
immediate potential for cognitive growth is the zone of proximal development (Doolittle, 1995).
In education, ZPD is the idea that optimal learning occurs just beyond the learner’s
current ability, where support from educators or peers is most effective. Children internalize the
knowledge and skills from interactions with their peers or educators and eventually use them to

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guide and direct their own behavior (Doolittle, 1995). ZPD framework supports differentiated
instruction, ensuring that students are appropriately challenged and receive the guidance
necessary to build their competence. A facilitator can oversee the learning process and when
faced with a challenge, can use techniques such as demonstration, discussion, and real-life
examples to help solve the problems (Clapper, 2015). It also promotes the use of social
interaction as a vital part of the learning process, aligning with collaborative learning practices in
classrooms.
Vygotsky’s theory is particularly relevant in interventions such as reading instruction,
where teachers tailor support based on individual students’ needs to help them progress from
current capabilities toward higher proficiency. ZPD can be supported in putting students into
small groups based on ability levels, and explicitly teaching skills based on the level that they are
at. ZPD can also be met by utilizing computer programs that are adaptive to student needs and
are constantly analyzing student success in the program and then creating interventions at their
skill level. Zone of proximal development suggests that the child is immersed in a cooperative
activity within a specific learning environment (Doolittle, 1995). ZPD is all about learning and
development, and the learning should be targeted at the student’s potential development, not
actual development (Silalahi, 2019). The ZPD provides a basis for understanding how students
can advance with structured assistance, making it a valuable framework for designing
instructional strategies that push learners toward independent mastery.
Related Literature
The purpose of this literature review is to understand current research that would support
best practices for intervention techniques to improve student success in reading in rural schools.

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Research includes challenges rural schools face, preparing teachers to be successful in rural
environments, and intervention strategies to promote reading success.
Teacher-Led Small Group Interventions
Rationale of Teacher-Led Small Group Interventions
Teacher-led small group interventions play a crucial role within the Response to
Intervention (RTI) framework by providing targeted instruction to struggling readers. RTI is a
tiered system designed to identify and support students with learning difficulties, and smallgroup instruction is a critical component, particularly in Tier 2 interventions (Austin et al., 2019).
One of the central benefits of the RTI model in rural schools is its adaptability. The multitiered
system allows educators to implement evidence-based interventions that range from general
classroom instruction (Tier 1) to more intensive, personalized interventions (Tier 2 and 3)
(Austin et al., 2019). Tier 1 involves high-quality, universal instruction that all students receive.
A Tiered level of learning emphasizes inclusive teaching practices that aim to prevent learning
difficulties from developing in the first place. For students who continue to struggle, Tier 2
provides targeted, small-group interventions that address specific skills, while Tier 3 offers
individualized, intensive support (Robinson, 2013). The RTI tiered structure is beneficial in rural
schools, has been proven in multiple studies that teachers need to manage diverse student
abilities within a single classroom and cannot always rely on specialized staff for additional
support (Austin et al., 2019; Robinson, 2013).
Small-group instruction allows educators to personalize learning experiences, addressing
students’ specific academic needs while fostering deeper engagement. This approach is
especially beneficial in rural schools, where teachers often manage diverse student needs with
limited instructional resources (Batista, 2019).

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The benefits of personalized, face-to-face instruction are well-documented. Research has
shown that small-group interventions allow students to receive more immediate feedback,
participate in interactive discussions, and engage with material in a structured manner (Donegan
& Wanzek, 2021). These interventions support foundational reading skills, including phonemic
awareness, fluency, decoding, and comprehension, which are critical for literacy development. In
rural schools, where specialized support such as reading specialists is often unavailable, teacherled small groups provide an effective means of delivering evidence-based instruction (Robinson,
2013).
Evidence of Effectiveness
Implementing RTI in rural schools has shown promising results in addressing the
educational needs of diverse learners. One of the key factors contributing to the success of RTI is
its structured, tiered approach, which allows educators to provide varying levels of support
tailored to individual student needs (Capin et al., 2024). The flexibility of RTI is particularly
beneficial in rural settings, where resources are often scarce. RTI helps rural schools by offering
targeted interventions. Targeted interventions will maximize the impact of limited resources,
leading to improved student outcomes. The multitiered level of support that RTI offers also
ensures that students receive the appropriate amount of support, ranging from universal
instruction through Tier 1 to more intensive interventions at Tier 2 or Tier 3 levels, depending on
student needs (Robinson et al., 2013).
Research indicates that RTI can significantly improve core academic areas, particularly
reading (Capin et al., 2024). When students receive Tier 2 interventions, they get small groups,
targeted instruction to meet their needs. Tier 2 interventions are effective in improving reading
fluency and comprehension among at-risk students in reading. A study showed that second

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graders who received Tier 2 interventions during disruptions caused by COVID-19 demonstrated
significant gains in reading skills (Cadime et al., 2022). Data that was collected through studies
shows adaptability through the RTI framework and the ability to provide structured support
regardless of educational setting. Early, targeted instruction within a Multitiered System of
Support (MTSS) framework, which aligns with RTI principles, helped mitigate long-term
academic difficulties, underscoring the importance of early intervention (Coyne et al., 2018).
Numerous studies highlight the effectiveness of small group reading interventions in
improving literacy outcomes. A review of small group reading interventions found that groups of
two to five students achieved significantly greater gains in reading comprehension and skills than
larger groups (Donegan & Wanzek, 2021). Focused attention in small settings enables educators
to tailor instruction, reinforcing essential reading strategies such as decoding, fluency, and
comprehension (Opatz & Kocherhans, 2023).
Furthermore, explicit instruction within small-group interventions has been shown to
enhance both word recognition and reading fluency (Solari et al., 2018). Research also suggests
that structured Tier 2 interventions that integrate multiple components—such as phonics, fluency,
and comprehension—yield better results than those that address skills in isolation (Opatz &
Kocherhans, 2023). These findings support the integration of teacher-led small-group instruction
as a key element of RTI implementation, particularly in rural schools where students may lack
additional literacy support.
While small-group interventions have proven effective, some studies indicate that their
success depends on consistent implementation and alignment with Tier 1 instruction. For
example, research found that small-group interventions improved vocabulary and content
knowledge but had less impact on overall reading comprehension (Stevens et al., 2020). This

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suggests that a systematic approach, in which small-group interventions complement whole-class
instruction, is essential for maximizing student gains.
Challenges & Considerations
Despite their effectiveness, implementing teacher-led small-group interventions in rural
schools presents several challenges. The RTI framework in rural schools is only successful when
evidence-based instructional strategies are effectively integrated. A systematic review was
conducted to highlight the effectiveness of small-group interventions within the RTI framework
(Dietrichson et al., 2020). They found that small-group interventions allow for more significant
interaction among students and teachers and individualized attention, which have shown success
in rural schools where students could otherwise lack access to those specialized resources.
Studies show that success of RTI interventions depends on selecting strategies that align with
rural students' specific needs and contexts. Along with using effective evidence-based practices,
another component that affects the success of RTI implementation is continuous progress
monitoring and adjusting interventions when needed. Van Norman et al. (2020) explored the
profiles of students exiting Tier 2 interventions. At the same time, many showed progress; those
with lower initial skills required ongoing, sustained support to maintain their gains. Their
research highlights how crucial regular progress monitoring is and that rural schools need to be
flexible in their approach to RTI implementation, which involves assessing students and
analyzing data frequently. Frequent assessments will identify which interventions the students
benefit from and point out students who might need additional or alternative support (Van
Norman et al., 2022).
Another significant issue is staffing shortages, which limit the availability of educators to
provide individualized support (Goldhaber et al., 2020). Rural schools often face difficulties in

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recruiting and retaining qualified teachers, leading to increased workloads and limited
opportunities for small-group instruction (Vaughn & Fletcher, 2012). When schools lack
adequate personnel, interventions may be inconsistently applied, reducing their overall
effectiveness.
Limited resources also hinder the successful implementation of small-group interventions
in rural settings. Rural schools often struggle with inadequate funding, making it difficult to
provide essential instructional materials, technology, and progress monitoring tools (Shenoy et
al., 2024). Additionally, teachers may not receive sufficient professional development on how to
implement evidence-based reading interventions effectively (Kehoe & McGinty, 2023). Without
ongoing training, educators may struggle to adapt instruction to meet the diverse needs of
struggling readers.
To address these challenges, schools must invest in professional development and support
systems that equip teachers with the necessary skills and knowledge to implement small-group
interventions effectively. Programs such as Targeted Reading Instruction (TRI) have
demonstrated success by providing structured coaching sessions and real-time feedback to
educators, enhancing their ability to deliver effective literacy instruction (Aiken et al., 2021).
Additionally, instructional coaches can offer continuous support, ensuring that teachers apply
research-based strategies consistently in small-group settings (Amendum & Liebfreund, 2018).
Consistent progress monitoring is another critical component for ensuring the success of
small-group interventions. Rural schools must develop systematic data collection processes to
track student progress and adjust interventions as needed (Van Norman et al., 2020). Combining
quantitative assessments, such as fluency and comprehension tests, with qualitative observations

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can help educators refine instructional strategies and ensure that interventions are meeting
students’ needs (Hoover, 2011).
Ultimately, the success of teacher-led small-group interventions in rural schools depends
on careful planning, professional development, and strategic resource allocation. By addressing
staffing shortages, enhancing professional training, and implementing robust progress
monitoring systems, rural schools can overcome barriers and improve literacy outcomes for
struggling readers.
Online and Technology-Based Reading Interventions
Introduction to Integrated Learning Systems
Implementing reading interventions in rural schools can be challenging. Different
approaches have shown varying degrees of success. Rural schools have found success in
implementing integrated learning systems, which are computer-based instructional programs
designed to provide individualized learning experiences for students. They typically involve a
one-to-one student-to-computer setup, where lessons adapt to each student's performance by
adjusting the difficulty level or repeating lessons as needed (Stein et al., 2022). Using online
interventions benefits rural schools due to scarce resources and a need for more funds.
Integrated learning systems, such as Lexia and iStation, offer computer-based
instructional models that provide individualized learning experiences for students. A study
compared two integrated learning systems in a rural setting, Lexia and iStation, and found that
both programs effectively supported reading development, with Lexia showing advantages
regarding instructional efficiency (Stein et al., 2022). Lexia's adaptive learning model allowed
for individualized instruction, enabling students to progress independently. The adaptive learning
model takes student progress in the program and adapts it to meet the needs of each individual

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student. These models were particularly beneficial in rural schools where staffing shortages face
the challenge to offer consistent one-on-one support (Stein et al., 2022). However, the study also
noted that while Lexia and iStation facilitated comparable improvements in reading skills, Lexia
required less staff time to implement, making the online program more efficient for rural settings
with limited personnel.
One of the primary advantages of integrated learning systems is their ability to reduce
teacher workload while maintaining instructional quality. Traditional pull-out intervention
programs (a widely used reading intervention strategy in which students who require additional
literacy support are temporarily removed from the general education classroom for targeted,
small-group instruction) require trained interventionists, which can be difficult to sustain in rural
areas due to budget constraints and staffing shortages (Ingersoll & Tran, 2023). In contrast,
online programs provide structured, data-driven instruction that allows students to work
independently while teachers monitor progress and provide supplementary support when
necessary (Szili et al., 2022). By leveraging technology-based interventions, rural schools can
address resource limitations while ensuring students receive high-quality, individualized literacy
instruction.
Adaptive Learning & Game-Based Interventions
Adaptive learning systems and game-based interventions provide personalized instruction
while enhancing student engagement and motivation. Adaptive programs continuously adjust
their content based on student performance, allowing learners to receive instruction at an
appropriate difficulty level. Research on fifth-grade students using adaptive reading programs
found significant improvements in vocabulary, comprehension, and overall reading achievement,

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demonstrating the potential of personalized learning models to support struggling readers
(Campbell et al., 2022).
Game-based interventions have also gained traction as effective tools for literacy
instruction. Digital programs such as Missions with Monty integrate strategy-based reading
instruction with interactive elements that maintain student motivation (Syal & Nietfeld, 2024).
Studies have shown that students using game-based reading interventions exhibit higher
comprehension gains and increased intrinsic motivation compared to those using traditional
online programs (Syal & Nietfeld, 2024). This approach is particularly useful in rural settings,
where students may have limited access to extracurricular activities and external literacy support.
However, research suggests that engagement levels significantly impact the success of gamebased interventions. While programs like GraphoLearn have effectively enhanced phonemic
awareness and letter-sound correspondence, some studies indicate that long-term engagement
declines without additional motivational elements, such as reward systems or progress tracking
(Ronimus et al., 2019). These findings highlight the need for educational game developers to
incorporate sustained engagement strategies to maximize student learning outcomes.
Evidence of Effectiveness
Several studies have demonstrated the effectiveness of computer-based reading
interventions in improving literacy skills. Research comparing Lexia and iStation in rural schools
found that both programs successfully supported reading development, with Lexia requiring less
staff time and offering greater instructional efficiency (Stein et al., 2022). Additionally, a study
researching the programs Funnix and Headsprout revealed that these computer-based programs
significantly improved phonemic awareness and vocabulary among at-risk students when
implemented in after-school tutoring sessions (Pindiprolu & Forbush, 2021).

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Another study evaluating a web-based reading comprehension program in rural and highpoverty schools found that students using the digital intervention outperformed their peers in
identifying main ideas and summarization tasks (Wijekumar et al., 2024). These improvements
were particularly evident in researcher-designed assessments, suggesting that technology-based
interventions can effectively teach specific literacy strategies. However, the study also indicated
that gains on standardized tests were less pronounced, emphasizing the need for careful
consideration of assessment methods when evaluating program success.
Despite the positive impact of online interventions, some research has yielded mixed
results. A study on the GraphoLearn mobile app found that while the program improved lettersound correspondence and word reading fluency, it had a limited effect on broader reading
comprehension skills (Ronimus et al., 2020). This suggests that while digital interventions can
effectively build foundational reading skills, their success depends on integration with broader
literacy instruction.
Implementation Challenges
While technology-based reading interventions offer promising solutions for rural schools,
several challenges must be addressed to ensure successful implementation. One major issue is
internet connectivity. Many rural communities experience unreliable internet access, which can
hinder students' ability to consistently engage with online learning platforms (Pindiprolu &
Forbush, 2021). Additionally, some schools may lack sufficient devices to provide equitable
access to technology-based interventions, further limiting their effectiveness.
Another significant challenge is staff training. Teachers must be equipped with the
knowledge and skills to integrate online programs effectively into their curricula. Studies
indicate that schools that provide structured professional development see better outcomes in

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technology-based interventions (Wijekumar et al., 2024). However, rural schools often face
funding and staffing shortages that make it difficult to offer comprehensive training programs
(Ingersoll & Tran, 2023). Without proper training, teachers may struggle to implement digital
interventions effectively, reducing their impact on student learning.
Furthermore, online reading programs require consistent monitoring and oversight to
ensure instructional depth. While adaptive programs are designed to adjust based on student
performance, research suggests that teacher intervention is still necessary to guide instruction
and analyze student progress data (Pindiprolu & Forbush, 2021). In rural schools with limited
staff, maintaining regular monitoring of online interventions can be challenging, potentially
reducing their effectiveness.
Online and technology-based reading interventions provide valuable opportunities to
support literacy development in rural schools. Adaptive learning systems such as Lexia and
iStation offer personalized instruction while reducing teacher workload, and game-based
programs enhance engagement and motivation. Research demonstrates that digital interventions
can significantly improve reading outcomes, particularly for at-risk students. However,
successful implementation requires addressing challenges such as internet connectivity, staff
training, and program integration into existing curricula. By strategically planning for these
challenges, rural schools can maximize the benefits of technology-based literacy interventions
and enhance student achievement.
Comparative Analysis of Teacher-Led vs. Online Interventions
Outcome Comparisons
Teacher-led and online reading interventions each offer unique benefits and challenges in
addressing literacy gaps, particularly in rural settings. Studies indicate that both intervention

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models improve reading achievement, though their effectiveness varies depending on
implementation fidelity, student engagement, and resource availability (Stein et al., 2022; Szili et
al., 2022).
Teacher-led interventions, such as small-group instruction within the Response to
Intervention (RTI) framework, have demonstrated success in developing foundational literacy
skills, particularly in phonemic awareness, fluency, and comprehension (Cadime et al., 2022).
Research suggests that small groups of two to five students show more significant gains in
reading comprehension than larger groups due to increased interaction with instructors and
targeted instruction (Donegan & Wanzek, 2021). However, challenges such as staffing shortages
and high teacher workloads can limit the effectiveness of these interventions in rural schools
(Goldhaber et al., 2020).
Conversely, online interventions offer flexibility and scalability, making them a viable
solution for rural schools facing resource constraints. Programs such as Lexia and iStation
provide adaptive learning experiences that adjust to student progress, reducing the need for direct
teacher involvement while maintaining instructional quality (Stein et al., 2022). Research
comparing these systems found that both improved reading skills, with Lexia being particularly
efficient in terms of instructional time (Stein et al., 2022). Additionally, game-based
interventions, such as Missions with Monty, have been shown to enhance student motivation and
engagement, which are critical factors in literacy development (Syal & Nietfeld, 2024).
While both models yield improvements, teacher-led interventions often produce deeper
learning due to the personalized support students receive. However, online programs provide
consistent, self-paced instruction, which can be particularly beneficial for students who lack
access to in-person tutoring.

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Advantages & Disadvantages
Teacher-led interventions provide several advantages, particularly in their ability to offer
personalized instruction tailored to individual student needs (Cadime et al., 2022). With direct,
face-to-face interaction, educators can adjust instruction in real-time based on student responses,
ensuring that struggling readers receive immediate feedback and targeted support (Donegan &
Wanzek, 2021). Additionally, strong student-teacher relationships in teacher-led models have
been linked to increased engagement and academic motivation, fostering a supportive learning
environment for students (Robinson, 2013). However, the success of teacher-led interventions is
often limited by time and staffing constraints, particularly in rural areas where teacher shortages
are prevalent (Goldhaber et al., 2020). Delivering small-group interventions requires substantial
resources, and schools with limited personnel may struggle to provide consistent, high-quality
instruction. Furthermore, the effectiveness of these interventions depends on teacher expertise,
and many rural educators lack access to professional development that would allow them to
implement evidence-based strategies effectively (Kehoe & McGinty, 2023). Because teacher-led
interventions require a significant investment of time and effort, they may not always be scalable
in districts with limited instructional staff (Shenoy et al., 2024).
In contrast, online interventions offer the advantage of adaptive learning, ensuring that
instruction is tailored to student needs while minimizing the demand for direct teacher oversight
(Stein et al., 2022). These programs can reduce teacher workload by automating lesson delivery
and progress tracking, allowing educators to allocate their time more efficiently (Szili et al.,
2022). Additionally, online programs are easily scalable, making them a practical solution for
rural schools with limited staff but many students needing intervention (Pindiprolu & Forbush,
2021). Digital tools, particularly those with game-based elements, can enhance student

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engagement and motivation, which is critical for struggling readers (Ronimus et al., 2020; Syal
& Nietfeld, 2024). Despite these advantages, online interventions also present challenges.
Reliable internet access and sufficient technology infrastructure are necessary for successful
implementation, and many rural schools struggle with connectivity issues (Pindiprolu &
Forbush, 2021). Additionally, the effectiveness of online programs depends on student
motivation and engagement—while some students thrive in digital learning environments, others
may disengage without direct oversight (Ronimus et al., 2019). Moreover, teacher involvement
remains necessary to monitor progress and ensure that students receive adequate support,
meaning that online interventions cannot fully replace human instruction (Wijekumar et al.,
2024).
Implications for Rural Settings
There can be significant stress faced by rural school principals, who often need more
resources to juggle multiple responsibilities. Rural principals can feel isolated due to small
districts' need for more administrative staff (Rogers, 2023). The added responsibility can affect
their ability to manage tasks effectively, which contributes to a high stress level for rural school
principals and, in turn, impacts their effectiveness in leading their schools (Klocko & Justis,
2019).
In rural areas, schools also suffer from teacher shortages. The teacher shortage issue is
highlighted by multiple researchers who note that rural schools often need more staff than in
urban areas (Rogers, 2023; Goldhaber et al., 2020). Factors that affect teacher shortages include
low salaries and challenging working conditions, which make attracting and retaining qualified
teachers to their district more difficult. The reliance on emergency-certified and long-term
substitute teachers can diminish educational quality (Goldhaber et al., 2020).

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Rural schools face a unique set of challenges that stem from geographic isolation, socioeconomic factors, and teacher shortages, all of which impact the quality of education and student
support services. Many families in rural communities are classified as low-income, which can
limit access to educational resources and contribute to disparities in student achievement. At the
same time, the geographic spread of rural schools makes collaboration between districts difficult,
further isolating educators and reducing opportunities for shared resources and professional
development (Klocko & Justis, 2019). These factors are compounded by persistent teacher
shortages, which create significant barriers to recruiting and retaining qualified educators in rural
areas (Goldhaber et al., 2020). As a result, school leaders struggle to provide essential services to
students due to low staffing levels, limiting the availability of intervention groups and
supplemental instruction for struggling learners (Rogers, 2023). All these issues create a
combination of challenges for staff to provide adequate reading interventions to meet the needs
of their students.
Rural school districts frequently experience lower funding due to their smaller size and
reliance on local tax bases, which significantly affects their ability to provide essential
educational resources (Rogers, 2023). Limited financing restricts access to updated instructional
materials, competitive teacher salaries, and necessary student support services, impacting overall
student success. Beyond classroom instruction, insufficient funding also affects facility
maintenance, transportation, and access to mental health services, which are crucial for fostering
a supportive learning environment (Klocko & Justis, 2019).
Moreover, rural schools face unique financial challenges due to lower enrollment
numbers and a reduced property tax base, which serve as critical sources of local district funding.
As a result, these schools often struggle to afford intervention programs, specialized reading

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curricula, and professional development for teachers, limiting their ability to address literacy
challenges effectively (Klocko & Justis, 2019). Additionally, high transportation costs in rural
areas further strain budgets, reducing funds available for instructional improvements (Rogers,
2023).
Trying to find a balance between raising local school taxes and the high poverty rate in
rural communities makes it extremely difficult for administrators to decide what materials are
necessary for student success in the classroom (Klocko & Justis, 2019). High poverty rates can
also affect early education before kindergarten. Within rural areas, there is typically limited
access to early care and education for children. The limit on access to early care and education
for children which can contribute to school readiness when children in rural areas are at an age to
attend kindergarten (Morrissey et al., 2020). Public early care and education programs are critical
in supporting children coming from low-income families. Rural areas often need more funding
for early childhood programs, which leads to lower participation in high-quality early care
programs. Children start kindergarten without prior education experience, leading to a lack of
foundational knowledge (Morrissey et al, 2020). Along with a lack of access to resources within
the schools, students are limited to mental health services within rural areas. The shortage of
mental health providers, combined with the stigma surrounding mental health issues, makes it
even more difficult for individuals to access essential services. To address this challenge,
innovative solutions like placing mental health counselors in schools have been proposed (Smith
et al., 2023).
The prevailing "one size fits all" approach to educational policy often overlooks the
specific needs of rural schools. Policymakers must advocate for tailored policies that address the

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unique challenges faced by rural communities, emphasizing the importance of local input in
policy formulation to create practical solutions (Klocko & Justis, 2019; Rogers, 2023).
The choice between teacher-led and online interventions has significant implications for
rural education, where schools must balance effectiveness with cost, scalability, and
sustainability.
Teacher-led interventions address the individualized learning needs of students but
require substantial staffing and training. Given the persistent teacher shortages and funding
limitations in rural areas, these interventions can be challenging to maintain at scale (Rogers,
2023; Goldhaber et al., 2020). Additionally, rural educators often juggle multiple responsibilities,
making it difficult to allocate sufficient time for small-group instruction (Klocko & Justis, 2019).
Online interventions provide a cost-effective alternative that allows rural schools to
deliver consistent instruction without requiring additional personnel (Stein et al., 2022).
However, access to technology and internet connectivity remains a barrier in many rural
communities, limiting the effectiveness of digital programs (Pindiprolu & Forbush, 2021).
Cost, Scalability, and Sustainability Considerations
The cost of implementing reading interventions is a critical factor for rural schools.
Teacher-led interventions require ongoing investments in teacher salaries, training, and
instructional materials, which can strain already-limited school budgets (Kehoe & McGinty,
2023). In contrast, online programs involve initial technology costs and annual subscription fees,
but they reduce long-term staffing expenses by automating certain aspects of instruction (Stein et
al., 2022). While technology-based programs may require an upfront investment, they can

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provide cost savings in the long run, particularly in districts that struggle to recruit and retain
intervention specialists.
When considering scalability, online interventions hold a clear advantage. Teacher-led
interventions are difficult to scale due to the need for small class sizes and individualized
attention, making it challenging to serve many struggling readers (Donegan & Wanzek, 2021).
Online programs, on the other hand, can be expanded with minimal additional cost, making them
more feasible for districts with large student populations and limited instructional staff (Szili et
al., 2022). Additionally, because digital tools allow students to work independently, schools can
support more learners without requiring additional personnel. However, the scalability of online
interventions depends on reliable internet infrastructure and adequate device availability, which
are not guaranteed in all rural districts (Pindiprolu & Forbush, 2021).
The sustainability of reading interventions in rural settings depends on factors such as
staffing stability, infrastructure maintenance, and professional development opportunities.
Teacher-led approaches rely on consistent staffing and ongoing professional development, both
of which can be unstable in rural areas due to high turnover rates and limited training
opportunities (Goldhaber et al., 2020). Without well-trained, long-term staff, sustaining highquality small-group instruction can be difficult. Online interventions, while potentially more
sustainable from a staffing perspective, require ongoing infrastructure support, such as regular
software updates, device maintenance, and IT support, to remain effective (Pindiprolu &
Forbush, 2021). Schools must also ensure that teachers receive training on how to integrate
digital tools effectively, as poor implementation can reduce the impact of online programs
(Wijekumar et al., 2024).

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Both teacher-led and online interventions offer viable solutions for improving literacy in
rural schools. While teacher-led approaches provide highly personalized instruction, they require
more staffing and resources, making them difficult to sustain in underfunded districts. Online
interventions offer adaptive, scalable learning models, but they require technology access and
consistent student engagement.
For rural schools, a hybrid approach may be the most effective strategy—leveraging the
engagement and scalability of online programs while maintaining teacher-led interventions for
targeted support. Future research should explore best practices for integrating both models to
maximize reading achievement in resource-limited environments.
HMH Into Reading Curriculum
In the target district, the researcher utilized the HMH Into Reading Curriculum in their
classroom. HMH Into Reading is a comprehensive literacy curriculum designed for grades K-6.
It focuses on structured literacy and aims to improve reading and writing skills through engaging
literature and knowledge-building connections. The program is organized by modules that
explore central topics through various texts and projects, promoting student self-actualized
learning. Additionally, it aligns with the Science of Reading research, ensuring effective
instructional practices (HMH Education Company, 2025).
HMH Into Reading Components
The HMH Into Reading curriculum is designed to build literacy skills through a
combination of reading, writing, vocabulary, and grammar instruction. It is organized into units,
each focusing on a central theme or essential question. Within each unit, students will read a

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variety of fiction and nonfiction texts, including short stories, poetry, myths, articles,
biographies, and historical tests (HMH Company, 2025).
Reading instruction emphasizes close reading strategies, where students analyze text
structures, themes, and author’s craft. They practice summarizing, making inferences, and
comparing text-based responses. Vocabulary development is integrated into the curriculum, with
explicit instruction on academic words, Greek and Latin words, affixes, and contest clues.
Writing instruction follows a process-based approach, guiding students through drafting,
revising, editing, and publishing their work. They engage in different types of writing, including
narrative, informational, and argumentative pieces. Grammar and language conventions are
embedded within writing lessons to reinforce proper use.
In addition to reading and writing, the curriculum emphasizes speaking and listening
skills. Students participate in collaborative discussions, group activities, and oral presentations,
strengthening their communication abilities.
Assessments include formative and summative evaluations, such as comprehension
quizzes, unit tests, and performance tasks. The Into Reading curriculum also provides support to
diverse learners by providing scaffolded instruction, offering resources for struggling readers.
HMH Small Group Interventions and Waggle Online Program
Embedded within the HMH curriculum are materials that align with the RTI model to
provide support across tiers. The researcher used Tier 2 interventions methods provided by the
curriculum for this study. They used the small group intervention piece, and the online program
Waggle to compare reading gains with small group interventions to adaptive computer program
interventions.

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The HMH Into Reading curriculum emphasizes personalized instruction through small
group reading sessions, allowing the researcher to address individual student needs effectively.
Within the Teacher’s Corner on the HMH platform, resources are available to guide teachers in
implementing these sessions. Additionally, a Teacher's Guide is included with the curriculum to
drive small group instruction and reinforce skills taught during the whole group lesson. Small
group instruction focuses on targeted skill development, helping students strengthen
comprehension strategies, fluency, and vocabulary based on their specific needs (HMH Ed,
2025). The grouping of students is flexible and based on the diagnostic assessments the students
take. They are then put into groups of three to five students and grouped based on ability level.
Also provided in the Into Reading curriculum is the online adaptive computer program
Waggle. It is designed to complement classroom instruction by offering personalized learning
experiences that target individual students' needs (HMH Company, 2025). The platform uses an
adaptive practice approach, tailoring sessions to each student’s proficiency level to reinforce
skills and address areas needing improvement. Additionally, interactive activities engage students
in active learning, allowing them to apply the concepts in various contexts, which enhances
comprehension and retention (HMH Teacher’s Corner, 2025).
Teachers can tailor the assignments on Waggle to the lesson they are teaching in class to
reinforce those skills. The program also aligns to the scores students received on the MAPs
assessment, which ensures that the practice materials align to each learner’s performance level.
Furthermore, progress monitoring features allow educators to track student growth over time and
adjust instruction as needed.
Within the target district, the researcher was able to utilize both forms of Tier 2
instruction within the study. Data shows that the students received essentially the same

44
READING INTERVENTIONS
instruction during intervention time, but one group received the practice in a small group while
the other received practice on Waggle.
Summary
The purpose of this study is to analyze and provide teachers with the best reading
intervention strategies to improve the practice of reading instruction for 6th grade students in a
rural Pennsylvania school, comparing two intervention strategies. Students at the target school
consistently scored under the state average on the ELLA PSSA tests, according to the PSSA
results. The Literature Review presented the Narrative Review, Theological Framework, and the
Summary of this research.

45
READING INTERVENTIONS
Chapter 3: Methods
Overview
The purpose of this study is to analyze and compare reading intervention outcomes
among two classes of 6th grade students in a rural school. The 2022 National Assessment of
Educational Progress reading assessment revealed notable declines in average reading scores for
both fourth and eighth graders compared to 2019 (NAEP, 2022). Additionally, the school district
used the diagnostic tool of the Growth Measure in the 2023-2024 school year to measure
academic achievement. The Reading Growth Measure is a computer-based assessment designed
to evaluate students' reading comprehension and language arts skills in relation to grade-level
expectations. This research-based tool tracks student progress over time using scaled scores and
performance levels to provide meaningful data. It measures student performance in three
keyways: scaled scores, which align with specific performance levels; grade-level equivalency,
which indicates how close a student is to meeting end-of-year grade-level expectations; and
overall progress tracking. The assessment is administered at the beginning, middle, and end of
the year to monitor student achievement and identify areas for improvement (Explanation of
Growth Measure Scores and Metrics, 2024). Data shows the need for reform in reading
instruction and interventions. To complete the study, two 6th grade reading classes in a rural
district participated, taught by the general education teacher and researcher. Students received
instruction using the Into Reading curriculum in whole group and received intervention time in a
small group, serving as the independent variable. One of the classes receiving online intervention
with the online program Waggle served as the control group, while the second class receiving
small group intervention led by the general education teacher served as the experimental group.
Reading success was measured by performance in the pre- and post-test, which was performed

46
READING INTERVENTIONS
using the Measure of Academic Progress (MAPs) assessment, represented as the dependent
variable. At the end of the experiment, the average increase in the MAPs assessment was
compared to show which group had more growth over the course of the second half of the school
year. The Methods Chapter includes the Design Methods, Research Question, Hypothesis,
Participants and Setting, Instrumentation, Procedures, and Data Analysis.
Design
This study employs quasi-experimental, non-equivalent groups designed to compare the
reading success of students utilizing an online intervention program with those participating in
small group, teacher-led interventions. The quasi-experimental design is a research approach that
compares existing groups rather than randomly assigning participants to experimental and
control groups (Gall et al., 2007). This method is often used in educational and social science
research when randomization is not feasible, allowing researchers to examine the effects of an
intervention or treatment in real-world settings. This research design was appropriate for this
study because random assignment of students to intervention types is not feasible, due to reading
classes already being predetermined before the start of the experiment. Instead, two pre-existing
groups will be studied: Group A-students who are assigned to the online intervention program,
and Group B-students participating in teacher-led small group interventions. I separated these
groups to best answer my research question, with one group utilizing the district’s web-based
intervention program, and one group focusing on small-group intervention, led by the classroom
teacher, in the general education classroom. Both groups were created from general education,
6th grade students, and the groups were similar in achievement scores and baseline reading data.
They are part of the same school district and receive identical instruction from the classroom
teacher, with the exception of the designated intervention period. Several unique challenges in

47
READING INTERVENTIONS
rural schools could impact the ability to provide a quality education to the students who attend,
including technology integration, personalized and one-on-one instruction, and the stability of
teaching staff (Stein et al., 2022). Findings from this study can help rural districts customize
reading intervention strategies that best meet the needs of their students.
The study will use a pre-test/post-test approach, with standardized reading assessments
administered to both groups before the intervention begins and after its completion. The test that
will be used is the MAPs assessment, which is the diagnostic tool that is used within the district
to assess reading ability. MAPs is a computer adaptive assessment, which allows a student to
respond to questions, and the test responds to the student, adjusting up or down the difficulty of
the questions presented to the student. This creates a personalized assessment for every student.
When students finish their MAP Growth test, they receive a number called a Rasch Unit scale
(RIT) score for each area they are tested in. The RIT score is compared to other students across
the country and given a percentile where they are performing based on the comparison. The pretest was administered at the beginning of the second quarter, in February 2025, and the post-test
was administered at the end of the 2025 school year, in May. The average scores from both the
pre- and post-test were compared to analyze growth in reading achievement over the course of
this time.
Research Questions
RQ1: Which intervention showed the most significant growth in reading informational
texts on the MAPs assessment?
RQ2: Which intervention showed the most significant growth in reading literature on the
MAPs assessment?

48
READING INTERVENTIONS
RQ3: Which intervention showed the most significant growth in vocabulary acquisition
and use on the MAPs assessment?
Hypothesis
Ho1: Students receiving small group interventions will not demonstrate significantly
greater gains in reading informational texts compared to students using the online intervention
program, based on the MAPs assessment data.
Ho2: Students receiving small group interventions will not demonstrate significantly
greater gains in reading literature compared to students using the online intervention program,
based on the MAPs assessment data.
Ho3: Students receiving small group interventions will not demonstrate significantly
greater gains in vocabulary acquisition and use compared to students using the online
intervention program, based on the MAPs assessment data.
Participants and Setting
Within this section, information will be found regarding the population of where the data
was collected, participants in the study, and setting.
Population
The rural school being studied is located in central Pennsylvania. Within this county,
there are 77,904 residents; 96% of the population is white, and 71% is categorized as
economically disadvantaged, with 14% living in poverty. 54% of the population is in the
workforce, and the median income for families is $52,826, which is lower than the national
average of $69,021 (Future PA Ready Index, 2024).

49
READING INTERVENTIONS
There are 1,057 students enrolled at the rural elementary school, which houses
kindergarten through sixth grade. The school continues to face setbacks that align with the
challenges of a rural school. On the Pennsylvania System of School Assessment (PSSA) in 2023,
the performance level for the district was 37.5% proficient or advanced in English Language Arts
(ELA), 33% proficient or advanced in Math, and 57.4% proficient or advanced in Science (PA
Department of Education, 2023). The district falls below the state average in Math and ELA but
did perform above the state average in science. When focusing on 6th grade specifically, the
average is well below the state standard. In 2023, the state average for PSSA scores on the ELA
test for 6th graders was 18.8% advanced, 36.8% proficient, 36.3% basic, and 8.1% below basic.
In the rural school district, 9.1% scored advanced, 30.5% proficient, 44.2% basic, and 16.2%
below basic (PA Department of Education, 2024). The gap between the school district’s PSSA
scores and the state averages is significant, which shows a need for a change in instruction and
intervention delivery.
The participants in this study were selected from a 6th-grade class in a rural elementary
school in Pennsylvania using purposive, typical case sampling. This sampling method was
chosen to ensure that the participants represented a typical demographic of rural 6th-grade
students, making the findings more applicable to similar educational settings. Purposive
sampling allowed for the intentional selection of students based on specific criteria, such as
enrollment in a general education classroom, comparable baseline reading levels, and exposure
to the same instructional methods, aside from the intervention. By using typical case sampling,
the study aimed to examine reading interventions within a setting that reflects common
characteristics of rural schools, ensuring that the results could be meaningfully interpreted in the
context of similar educational environments. Data was collected over the course of the second

50
READING INTERVENTIONS
half of the 2024-2025 school year. Within this grade, there are eight Language Arts classes, but
only two were selected. Two classes were selected because these classes have the same teacher
and receive the same instruction. Incorporating other classroom teachers could skew results since
the students would be receiving different Tier 1 instruction. All participants received Tier 1
instruction using the Houghton Mifflin Harcourt (HMH) Into Reading Program.
Participants
Students selected were in 6th grade in a rural elementary school, serving grades K-6. The
rural school is a Title 1 school, and all students receive a free and reduced lunch, as 65% of the
population is classified as economically disadvantaged (Future PA Ready Index, 2024). The
student body consists of 1,020 students, 51% being male and 49% being female, and the
following population percentages: 94.8% white, 3.2% more than two races, 1.4% Hispanic, and
0.5% Asian (Future PA Ready Index, 2024). For this study, the number of participants sampled
were 42 sixth grade, general education students. There were 157 students in this grade, and 42 of
the students were selected to participate in the study. Students were selected based on which ones
were receiving the general education 6th grade reading curriculum and were assigned to the
classes of the researcher/general education teacher. Students who were in reading classes
receiving either remediation or accelerated curriculum were eliminated from the sample because
they would not consistently be receiving the same instruction, due to using a different Tier 1
curriculum. Participants range in age from 11-12 and are spread across two classes. The classes
are set up as followed:
Class #

Boy Students

Girl Students

Total Students

Class 1

7

10

17

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READING INTERVENTIONS
Class 2

14

11

25

The study consisted of two groups (a) students who received twenty minutes on the
online intervention program Waggle, twice a week and; (b) students who received small group,
direct instruction led by the teacher for twenty minutes, twice a week. Group A was the control,
and Group B was the experimental group. Intervention time was administered during class, by
the general education teacher. The teacher used intervention materials for small group instruction
provided by the HMH Into Reading curriculum.
For small group instruction, the students were assigned to their groups based on their
beginning of the year MAPs assessment scores. These scores assigned students in groups of
equal levels. Intervention was then determined based on needing supplemental instruction or
accelerated instruction, based on if the student is performing on a 6th grade reading level.
Setting
The students received whole group instruction using the HMH Into Reading Curriculum.
Students received in-person instruction, and intervention within the general education classroom
where they received whole-group instruction. Students used the online intervention program
Waggle, which aligns to their needs based on their performance on the MAPs assessment, and
adjusts interventions based on program success.
Instrumentation
The Measures of Academic Progress (MAP) assessment is designed to measure a
student’s academic achievement and growth over time in reading and mathematics (Map Growth
Fact Sheet, 2023). MAP is a computer adaptive diagnostic assessment. In a computer adaptive
assessment, as a student responds to questions, the test responds to the student, adjusting up or

52
READING INTERVENTIONS
down the difficulty of the questions presented to the student. This creates a personalized
assessment for every student. Due to this, there is not a specific number of questions on the
MAPs assessment. When students finish their MAP Growth test, they receive a number called a
Rasch Unit scale (RIT) score for each area they are tested in. The RIT score is compared to other
students across the country and given a percentile where they are performing based on the
comparison. According to the Northwest Evaluation Association (NWEA) (2023):
The NWEA 2020 MAP Growth norms study provides achievement status and growth
norms for individual students and grade levels within schools in each of the four subject
areas: reading, language usage, mathematics, and general science. The study’s results are
based on K–12 grade level samples. Records are sampled from between 3.6 and 5.5
million test scores from 500,000 to 700,000 students attending over 24,500 public
schools in 5,800 districts spread across all 50 states.
This population size ensures that the data collected from the MAPs assessment is valid. The
MAP assessment will be used as a pre- and post-test to evaluate the difference in reading growth
between the control and experimental groups (Map Growth Fact Sheet, 2023). According to Gall
et al. (2007), a t-test is the most appropriate for data comparison, as we are comparing the
averages in Rasch Unit scale (RIT) scores between the two groups, using the pre- and post-tests.
Procedures
Participants were chosen from a 6th grade class in a rural school. The Language Arts
classes in which the interventions took place were 80 minutes every day, and these classes
received one week of whole group instruction, and one week of independent practice and
intervention through centers. For the independent practice, the students would first receive a 20-

53
READING INTERVENTIONS
minute whole-group grammar lesson and then be separated into their small groups. Students
would go through six centers across two days, and the centers included the following: Center 1intervention, Center 2-vocabulary, Center 3-Rigby Reader assigned through HMH, Center 4supplemental story to reiterate the skills that were taught in the whole group instruction, Center
5-writing, Center 6-independent reading. The students rotated through the centers in 20-minute
intervals, so that they got through three centers a day. Once they got through all six centers over
the course of two days, the students would be given new activities, utilizing the same centers, for
the next two days. Students had time on the last day of the week to complete work they did not
finish during center time that week. One class categorized as Group A utilized the online
intervention program Waggle for 20 minutes three times a week, while the second class
categorized as Group B received small group, teacher-led intervention for 20 minutes three times
a week. Small groups consisted of a range of three to five students per group. The teacher was
trained in using the Waggle program and analyzing data, showing student use and student
success within the program. The teacher using small group instruction in their classroom used
the intervention piece embedded into the HMH Into Reading Curriculum. The intervention piece
provides instruction for students performing below grade level, on grade level, and above grade
level. Interventions that were used were determined using data from the MAPs assessment.
Small group instruction was focused on comprehension strategies, reading strategies, and
vocabulary building activities.
When determining small groups, students were placed with others who achieved a similar
score on the MAPs assessment. The district used the MAPs assessment as their diagnostic tool to
show student achievement in reading. Student performance data on the MAPs assessment was
used to determine the appropriate interventions needed during small group instruction.

54
READING INTERVENTIONS
Students received intervention time for 18 weeks of the 2024-2025 school year. At the
end of the year, students took the MAPs assessment again, and the growth of the students was
compared between the control group receiving the online intervention program and the
experimental group receiving small group teacher-led interventions.
At all stages of data collection, all information that could identify the participants was
protected. Data were stored securely on an Excel spreadsheet, and only the researcher had access
to records. Data was stored on a password-protected computer. When not being utilized, the
computer was stored in a locked classroom. The data will be retained for a period of five years
after the completion of this research study. IRB permission and district consent forms were
obtained prior to starting the research.
Data Analysis
Data from the middle of the year MAPs assessment to the end of the school year will be
analyzed for reading achievement. The dependent variable is the test scores, while the
independent variable is the type of intervention the students receive (small group vs. online
program). A t-Test was used to compare the mean gain scores between the two independent
variables. According to Gall (2007), a t-test will determine whether there is a statistically
significant difference in the mean gain scores of the two groups. Averages of the RIT scores from
both groups in the pre-test will be compared to the average RIT scores from both classes in the
post-test, assessing the three areas of research- reading informational texts, reading literature,
and vocabulary acquisition and use. Descriptive statistics including mean, standard deviation,
and range will be calculated for both groups to summarize pre-test and post-test performance.
According to Gall (2007), there are three assumptions when conducting a t-test, which are that
the scores form an interval or ratio scale of measurement, scores in the populations under study

55
READING INTERVENTIONS
are normally distributed, and score variances for the populations under study are equal. The
students are all in 6th grade and receiving the same Tier 1 instruction from the same classroom
teacher.
Statistical procedures will be used for each hypothesis as the following:
Hypothesis 1 (Ho1)
Students receiving small group interventions will demonstrate significantly greater gains in
reading informational texts compared to students using the online intervention program.
•

Statistical Procedure: Independent samples t-Test to compare the mean gain scores.

•

Effect Size: Cohen’s d to quantify the magnitude of differences. According to Cohen’s
conventions, effect sizes are interpreted as small (d = 0.2), medium (d = 0.5), and large (d
= 0.8).

•

Alpha Level: Set at 0.05 to determine statistical significance.

Hypothesis 2 (Ho2)
Students receiving small group interventions will demonstrate significantly greater gains in
reading literature compared to students using the online intervention program.
•

Statistical Procedure: Independent samples t-Test to compare the mean gain scores.

•

Effect Size: Cohen’s d to report the practical significance of the observed differences.
According to Cohen’s conventions, effect sizes are interpreted as small (d = 0.2), medium
(d = 0.5), and large (d = 0.8).

•

Alpha Level: Set at 0.05 to determine statistical significance.

56
READING INTERVENTIONS
Hypothesis 3 (Ho3)
Students receiving small group interventions will demonstrate significantly greater gains in
vocabulary acquisition and use compared to students using the online intervention program.
•

Statistical Procedure: Independent samples t-Test to compare the mean gain scores.

•

Effect Size: Cohen’s d to report the practical significance of the observed differences.
According to Cohen’s conventions, effect sizes are interpreted as small (d = 0.2), medium
(d = 0.5), and large (d = 0.8).

•

Alpha Level: Set to 0.05 to determine statistical significance.

57
READING INTERVENTIONS
CHAPTER FOUR: FINDINGS
Overview
The purpose of this quantitative quasi-experimental case study was to analyze and
compare reading intervention outcomes among two classes of 6th grade students in a rural school.
This chapter presents descriptive statistics of the three research questions along with an analysis
of the results.
Research Questions
RQ1: Which intervention showed the most significant growth in reading informational
texts on the MAPs assessment?
RQ2: Which intervention showed the most significant growth in reading literature on the
MAPs assessment?
RQ3: Which intervention showed the most significant growth in vocabulary acquisition
and use on the MAPs assessment?
Hypothesis
Ho1: Students receiving small group interventions will not demonstrate significantly
greater gains in reading informational texts compared to students using the online intervention
program, based on the MAPs assessment data.
Ho2: Students receiving small group interventions will not demonstrate significantly
greater gains in reading literature compared to students using the online intervention program,
based on the MAPs assessment data.

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READING INTERVENTIONS
Ho3: Students receiving small group interventions will not demonstrate significantly
greater gains in vocabulary acquisition and use compared to students using the online
intervention program, based on the MAPs assessment data.
Descriptive Statistics
Group A Descriptive Statistics
The descriptive statistics for Group A’s Measures of Academic Progress (MAP) scores
provide a clear snapshot of student performance across four key domains: overall RIT scores,
Reading Literature, Reading Informational Texts, and Vocabulary Acquisition and Use.
Seventeen students were analyzed in Group A, which received small group, teacher-led
interventions. The MAP assessment was given in the middle of the year (MOY) and end of the
year (EOY). The data from this assessment are described in the following paragraphs.
The RIT MOY (middle of year) mean was 215.12, with a median of 214 and a standard
deviation of 8.51, indicating moderate variability in student performance. By the EOY (end of
year), the mean decreased slightly to 214.82, with a consistent median of 214 and a slightly
lower standard deviation of 7.26, suggesting slightly less variation in scores. The most frequent
scores (modes) were 213 for MOY and 221 for EOY, showing that while the average remained
steady, the most common EOY score was higher (see Table 1).
Table 1
Descriptive Statistics of MAPs scores for Group A

RIT MOY

Count

Mean

17

215.12

Standard
Deviation
8.51

Minimum

Maximum

Median

Mode

204

230

214

213

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READING INTERVENTIONS
RIT EOY

17

214.82

7.26

203

232

214

221

For the Reading Information Texts domain at MOY, the mean score was 214.06, with a
median of 213.0 and a mode of 203.0. The standard deviation was 9.68, reflecting a relatively
wide spread of scores ranging from 200 to 230. This suggests that while the average performance
was moderate, there was significant variability, with some students scoring considerably lower
than others. By EOY, the mean remained virtually the same at 214.00, but the median rose to
216.0 and the mode also increased to 216.0, indicating a shift in the most common performance
level. The standard deviation dropped to 7.26, and scores ranged from 198 to 224, showing a
reduction in performance variability (see Table 2).
Table 2
Descriptive Statistics of Reading Informational Text scores for Group A

Count

Mean

Standard
Deviation

Minimum

Maximum

Median

Mode

Reading
Informati
onal Texts
MOY

17

214.06

9.68

200

230

213

203

Reading
Informati
onal Texts
EOY

17

214

7.26

198

224

216

216

In the Reading Literature domain, students started with a MOY mean of 215.12 and a
median of 217, but this dropped to a mean of 213.18 and a median of 214 by EOY. The standard
deviation increased from 7.02 to 8.53, indicating growing disparities in student achievement. The
mode also shifted from 205 (MOY) to 209 (EOY), suggesting changes in the distribution of
scores over time (see Table 3).

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READING INTERVENTIONS
Table 3
Descriptive Statistics of Reading Literature scores for Group A

Count

Mean

Standard
Deviation

Minimum

Maximum

Median

Mode

Reading
Literature
MOY

17

215.12

7.02

202

228

217

205

Reading
Literature
EOY

17

213.18

8.53

196

234

214

209

In the Vocabulary Acquisition and Use category, the MOY mean was 216.41, with a
median of 214 and a mode of 218. By EOY, the mean slightly increased to 217.06, and the
median rose to 218, with the same mode of 218. The standard deviation decreased from 12.07 to
11.31, suggesting more consistent performance across the class by the end of the year. The mode
remained the same at 218 for both MOY and EOY scores (see Table 4).
Table 4
Descriptive Statistics of Vocabulary Acquisition and Use scores for Group A

Count

Mean

Standard
Deviation

Minimum

Maximum

Median

Mode

Vocabulary
Acquisition and
Use MOY

17

216.41

12.073

195

237

214

218

Vocabulary
Acquisition and
Use EOY

17

217.06

11.305

189

233

218

218

In conclusion, Group A saw an overall slight decrease in scores from the middle to end of
year in all areas, except in the domain of Vocabulary Acquisition and Use. While overall scores
decreased, it should be noted that the standard deviation also decreased in all domains except

61
READING INTERVENTIONS
Reading Literature, suggesting that student scores became more similar by the end of the year-a
sign that lower-performing students may have caught up or that performance across the group
became more consistent.
Group B Descriptive Statistics
The descriptive statistics for Group B’s Measures of Academic Progress (MAP) scores
provide a clear snapshot of student performance across four key domains: overall RIT scores,
Reading Literature, Reading Informational Texts, and Vocabulary Acquisition and Use. Twentyfive students were analyzed in Group B, which received adaptive online program interventions.
The MAP assessment was given in the middle of the year (MOY) and end of the year (EOY).
The data from this assessment are described in the following paragraphs.
The RIT MOY (middle of year) mean was 214.36, with a median of 214.0 and a standard
deviation of 8.24, indicating moderate variability in student performance. By the EOY (end of
year), the mean increased slightly to 216.64, with a higher median of 219 and a slightly increased
standard deviation of 8.45, suggesting slightly more variation in scores. The most frequent scores
(modes) were 207 for MOY and 219 for EOY, showing a shift in the most achieved score over
time (see Table 5).
Table 5
Descriptive Statistics of MAPs scores for Group B

Count

Mean

Standard
Deviation

Minimum

Maximum

Median

Mode

RIT MOY

25

214.36

8.24

199

229

214

207

RIT EOY

25

216.64

8.45

202

236

219

219

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READING INTERVENTIONS
For the Reading Informational Texts domain at MOY, the mean score was 214.84, and
the standard deviation was 11.37, suggesting a moderate degree of variability in scores. The
minimum score recorded was 191, while the maximum reached 232, showing a widespread in
performance. The median was 215, aligning closely with the mean, and the mode was 202. By
EOY, the mean slightly increased to 215.04, and the standard deviation decreased to 9.61,
reflecting less variability and more consistency in student scores. The range narrowed somewhat,
with scores spanning from 194 to 230. The median increased to 218, while the mode also rose to
208, signaling a shift in the typical score achieved by students (see Table 6).
Table 6
Descriptive Statistics of Reading Informational Text scores for Group B

Count

Mean

Standard
Deviation

Minimum

Maximum

Median

Mode

Reading
Informational
Texts MOY

25

214.84

11.37

191

232

215

202

Reading
Informational
Texts EOY

25

215.04

9.61

194

230

218

208

In the Reading Literature domain, students began with a MOY mean of 213.68 and a
median of 217, which slightly increased to a mean of 215.20 and a median of 215 by EOY.
However, the standard deviation rose from 9.49 to 11.75, indicating an increase in score
variability. The mode also shifted from 211 at MOY to 210 at EOY, suggesting some changes in
score distribution across the group (see Table 7).
Table 7
Descriptive Statistics of Reading Literature scores for Group B

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READING INTERVENTIONS
Count

Mean

Standard
Deviation

Minimum

Maximum

Median

Mode

Reading
Literature
MOY

25

213.68

9.49

197

230

217

211

Reading
Literature
EOY

25

215.2

11.75

186

235

215

210

For the Vocabulary Use and Acquisition domain, at MOY, the mean score was 214.84,
and the standard deviation was 7.65, indicating a relatively moderate spread of scores. The scores
ranged from a minimum of 201 to a maximum of 229, reflecting some variation across students.
The median was 215, aligning closely with the mean, while the mode was 218, indicating the
most frequently occurring score in this group. By EOY, the mean increased significantly to
220.16, suggesting notable improvement in vocabulary performance. The standard deviation rose
to 11, indicating a wider spread of scores by the end of the year. The range expanded, with scores
spanning from a minimum of 198 to a maximum of 250, showing greater variability among
students. The median also increased to 222, and the mode shifted to 216, suggesting both central
tendency and typical performance improved (see Table 8).
Table 8
Descriptive Statistics of Vocabulary Acquisition and Use scores for Group B

Vocabulary
Acquisition
and Use
MOY

Count

Mean

Standard
Deviation

Minimum

Maximum

Median

Mode

25

214.84

7.65

201

229

215

218

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READING INTERVENTIONS
Vocabulary
Acquisition
and Use
EOY

25

220.16

11

198

250

222

216

In conclusion, Group B showed modest increases in mean scores from MOY to EOY in
all domains, with the highest increase being in the Vocabulary Use and Acquisition domain.
Although the standard deviations rose slightly in these areas, the overall upward trend in medians
and modes suggests that several students made academic progress during the intervention period.
While the descriptive statistics provide a snapshot of student performance patterns, inferential
statistical analysis was conducted to determine whether the differences observed between the two
groups were statistically significant. The following section reports the results for the hypothesis
testing on each assessment domain.
Results
Hypothesis 1
Ho1: Students receiving small group interventions will not demonstrate significantly
greater gains in reading informational texts compared to students using the online intervention
program, based on the MAPs assessment data.
Table 9
Summary of t-Test Results for Reading Informational Texts

Reading
Informati
onal Texts

Small
Group
Mean
Gain

Online
Mean
Gain

t

df

p

Cohen's d

Effect Size
Interpretation

Statistical
Significance

-0.06

+0.20

0.60

40

0.56

-0.03

Negligible

Not
significant

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READING INTERVENTIONS
An independent samples t-test was conducted to evaluate whether students receiving
small group instruction demonstrated greater gains in Reading Informational Texts compared to
those using an online intervention. The analysis revealed no statistically significant difference
between the two groups, t(40) = 0.60, p = .56. The effect size was negligible (d = -0.03),
indicating no practical difference (see Table 9). Therefore, the null hypothesis was not rejected,
suggesting that small group instruction did not result in significantly greater gains than the online
program in this domain.
Hypothesis 2
Ho2: Students receiving small group interventions will not demonstrate significantly
greater gains in reading literature compared to students using the online intervention program,
based on the MAPs assessment data.
Table 10
Summary of t-Test Results Reading Literature

Reading
Literature

Small
Group
Mean
Gain

Online
Mean
Gain

t

df

p

Cohen's
d

Effect Size
Interpretation

Statistical
Significance

-1.94

+1.52

-1.71

40

0.095

-0.37

Small

Not
significant

An independent samples t-test was conducted to evaluate whether students receiving
small group instruction demonstrated greater gains in Reading Literature compared to those
using an online intervention. The results showed no statistically significant difference between

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groups, t(40) = -1.71, p = .095. However, the effect size (d = -0.37) indicates a small practical
difference, favoring the online intervention (see Table 10). Despite the numerical advantage for
the online group, this difference was not large enough to reach statistical significance. The null
hypothesis was not rejected.
Hypothesis 3
Ho3: Students receiving small group interventions will not demonstrate significantly
greater gains in vocabulary acquisition and use compared to students using the online
intervention program, based on the MAPs assessment data.
Table 11
Summary of t-Test Results for Vocabulary Acquisition and Use
Small
Group
Mean
Gain

Online
Mean
Gain

t

df

p

Cohen's
d

Effect Size
Interpretation

Statistical
Significance

Vocabulary
Small to
Acquisition +0.65 +5.32 -2.93 40 0.006
-0.44
approaching
Significant
and Use
medium
An independent samples t-test was conducted to evaluate whether students receiving
small group instruction demonstrated greater gains in Vocabulary Acquisition and Use compared
to those using an online intervention. A statistically significant difference was found, t(40) = 2.93, p = .006 (see Table 11). Students in the online intervention group demonstrated
significantly greater gains than those in the small group. The effect size was d = -0.44, which
represents a small to approaching medium practical difference. The null hypothesis was rejected
for this outcome, suggesting the online program was more effective in improving vocabulary
skills.

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CHAPTER FIVE: CONCLUSIONS
Overview
The purpose of this quantitative quasi-experimental case study was to analyze and
compare reading intervention outcomes among two classes of 6th grade students in a rural school.
This chapter will explore the interpretation of the study's findings and their implications for
policy and practice. It will conclude with discussions of implications and limitations, along with
recommendations for future research.
Discussion
The purpose of this quantitative quasi-experimental case study was to analyze and
compare reading intervention outcomes among sixth-grade students in a rural school who
received either small group instruction or an adaptive computer-based program. This chapter
discusses the findings of the study broken down by research questions, relevant literature, and
theoretical frameworks. Each research question is examined with comparisons to prior studies,
highlighting how the present results align with or diverge from existing knowledge in the field.
The chapter also interprets findings through the lenses of Self-Determination Theory (SDT) and
the Zone of Proximal Development (ZPD), which served as the theoretical underpinnings of the
research.
Research Question 1 (RQ1):
Which intervention showed the most significant growth in reading informational texts on the
MAPs assessment?
The results for RQ1 indicated that there was no statistically significant difference in gains
in reading informational texts between students receiving small group interventions and those

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using the adaptive online program Waggle (Cohen’s d = -0.03). This outcome suggests that
neither intervention type provided a distinct advantage in improving students’ informational text
comprehension, concluding that neither intervention proved to be effective in the domain of
reading informational texts.
These findings differ with Stein et al. (2022), who found that while online programs like
Lexia and iStation were effective in supporting reading skills, they did not necessarily
outperform traditional teacher-led instruction in every area. In this case, neither intervention was
successful during this study. Similarly, Donegan and Wanzek (2021) emphasized that the
effectiveness of small group interventions depends heavily on implementation fidelity and
alignment with Tier 1 instruction—both of which can vary significantly in rural settings. Smallgroup instruction allows educators to personalize learning experiences, addressing students’
specific academic needs while fostering deeper engagement. This approach is especially
beneficial in rural schools, where teachers often manage diverse student needs with limited
instructional resources (Batista, 2019).
Vygotsky’s Zone of Proximal Development (ZPD) framework underscores the
importance of tailored scaffolding that targets the student’s potential developmental zone
(Doolittle, 1995; Clapper, 2015). If instruction, whether online or in-person, does not sufficiently
challenge or support the learner within that optimal range, growth may stagnate. The flat
outcome in this domain could also suggest that both groups needed more robust or differentiated
support specifically tailored to the cognitive demands of informational texts.
Moreover, Self-Determination Theory (Deci & Ryan, 2000) posits that competence,
autonomy, and relatedness must be present for optimal motivation. If neither intervention
fostered intrinsic motivation around informational reading—which is often perceived as less

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engaging than narrative texts—students may not have experienced the persistence necessary to
achieve substantial gains. This is particularly relevant given that 64.5% of the students in the
rural district are economically disadvantaged and may lack foundational support at home (PA
Ready Index, 2024), making motivational components of instruction even more critical.
Research Question 2 (RQ2):
Which intervention showed the most significant growth in reading literature on the MAPs
assessment?
Results from RQ2 showed a small but not statistically significant difference in favor of
the online intervention group in reading literature (Cohen’s d = -0.37, p = 0.095). Although the
online program slightly outperformed small group instruction, the results do not suggest a
conclusive advantage.
This finding partially supports Alqahtani (2020), who noted that adaptive platforms can
enhance reading motivation and comprehension when they provide interactive feedback and
context-sensitive questioning. However, other studies, including those by Donegan and Wanzek
(2021) and Solari et al. (2018), reinforce the idea that face-to-face small group instruction
enables real-time feedback and deeper engagement—benefits that are particularly valuable for
literature, which often requires interpretation and discussion.
The role of SDT is again relevant here. While the online group may have experienced
enhanced autonomy and competence due to adaptive scaffolding and gamified features (Stone,
Deci, & Ryan, 2009), the lack of relatedness—one of SDT’s core tenets—may have limited
engagement. In contrast, small group sessions allow for the development of student-teacher
relationships and peer discussion, which support motivation and learning (Capin et al., 2024).

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This result also echoes findings by Robinson (2013) and Capin et al. (2024), who
emphasized the importance of balancing instructional quality with contextual constraints in rural
schools. While online programs can reduce teacher workload (Stein et al., 2022), they may not
always foster the same depth of literary engagement as teacher-facilitated discussions.
Research Question 3 (RQ3):
Which intervention showed the most significant growth in vocabulary acquisition and use on the
MAPs assessment?
The most notable finding from this study emerged in RQ3. Students in the online
intervention group made significantly greater gains in vocabulary acquisition and use compared
to those in the small group intervention (p = 0.006, Cohen’s d = -0.44).
This supports the findings of Campbell et al. (2022), who reported that adaptive learning
systems significantly improve vocabulary skills, especially when instruction is tailored to
students’ performance. Additionally, Pindiprolu and Forbush (2021) found that computer-based
programs like Funnix and Headsprout are effective in promoting vocabulary and phonemic
awareness, especially for at-risk learners.
The success of the Waggle platform in this area may be explained through the lens of
ZPD: its ability to continuously adjust based on student performance mirrors the scaffolding
process Vygotsky advocated (Silalahi, 2019). Students were likely able to operate within their
optimal learning zone more consistently than in a small group setting, where instructional time
and personalization may have been constrained by staffing challenges typical of rural schools
(Goldhaber et al., 2020).

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This result also aligns with the SDT framework. Waggle’s interactive and self-paced
format likely enhanced students’ sense of autonomy and competence, both of which are essential
for sustained intrinsic motivation (Deci & Ryan, 2000). As emphasized by Syal and Nietfeld
(2024), gamified digital interventions foster engagement and vocabulary retention, especially
when integrated with real-time feedback.
The comparatively lower gains in the small group setting could reflect findings by
Stevens et al. (2020), who noted that while teacher-led interventions improve comprehension and
vocabulary, their success often depends on how well they are aligned with Tier 1 instruction and
implemented consistently—factors that can be difficult to manage in resource-strapped rural
schools.
Implications
The findings of this study offer meaningful implications for both instructional practice
and educational leadership in rural schools. The results suggest that adaptive online interventions
can contribute to student growth more than small group teacher led interventions, though neither
emerged as definitively superior across all reading domains. Notably, the adaptive computerbased intervention produced statistically significant gains in Vocabulary Acquisition and Use,
suggesting that such platforms may be particularly effective for reinforcing discrete literacy
skills. Additionally, small group teacher led interventions did not prove to be effective in student
growth.
For classroom teachers, this indicates that integrating adaptive programs into existing
reading instruction may help bridge vocabulary gaps, especially in environments where one-onone instruction is difficult to sustain. At the same time, the lack of significant difference in

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reading informational text and literature performance underscores the importance of ensuring
that both types of interventions are implemented with fidelity and aligned to core instructional
goals.
School administrators and district leaders may view these findings as justification for
adopting a hybrid intervention model—blending teacher-led small group instruction with
adaptive digital platforms. This approach offers the flexibility to address individual learning
needs while maximizing limited staffing and resources. In rural schools, where teacher shortages
and funding constraints are often acute, a combination model may offer the most sustainable and
effective solution.
Theoretically, the results support the application of differentiated instruction principles
and intervention strategies that respond to the unique needs of rural learners. Interventions that
are carefully structured and supported—whether digital or teacher-directed—can foster
meaningful literacy growth when they account for student motivation, developmental readiness,
and consistent progress monitoring.
Limitations
Several limitations must be acknowledged when interpreting the findings of this study.
First, the study employed a quasi-experimental design using intact classroom groups. As such,
random assignment was not possible, which limited the ability to fully control preexisting
differences between the groups. Although groups were predetermined, the study controlled initial
differences by measuring gains across each domain of reading proficiency.

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Second, the sample size was relatively small and drawn from a single rural school
district. While the findings provide valuable insight into reading intervention practices in similar
contexts, they may not be generalizable to more diverse or urban populations. The sample size
was chosen to maintain consistency among instruction with the researcher being the only teacher.
Third, the intervention period spanned only 18 weeks. It is possible that a longer
implementation window would have yielded different results, particularly in more complex areas
like reading comprehension of literature and informational texts.
Additionally, both intervention types were delivered by the same classroom teacher,
which may have introduced bias. Although consistent instruction is a strength of the design, the
teacher’s familiarity with the small group students may have influenced the quality or focus of
instruction. One limitation of having a single classroom teacher deliver the small-group
instruction was the potential for inconsistency if the teacher was absent. Although this occurred
only once during the study, a substitute teacher—who was not trained in implementing the HMH
Into Reading interventions—conducted the instruction on that occasion. This introduced a minor
inconsistency in intervention delivery, as the substitute may have implemented the program
differently than the researcher intended.
Finally, the study relied solely on the MAPs assessment to measure growth. While this
assessment provides valid and reliable data on reading skills, it may not fully capture qualitative
differences in engagement, strategy use, or reading motivation. If students were given an
assessment on paper/pencil, it could have resulted differently than the MAPs assessment that is
administered on the computer.
Recommendations for Future Research

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Based on the results and limitations of this study, several directions for future research are
recommended. The first recommendation would be to broaden the scope of the sample. Future
studies should include a larger and more diverse sample of schools to improve generalizability.
Including schools from urban and suburban areas would allow for comparisons across
geographic and socioeconomic contexts. The HMH Curriculum is a nationally recognized
curriculum, so schools could be included using a similar research model.
The next recommendation would be to examine hybrid models. Given the potential benefits
of both teacher-led and online interventions, future research should explore hybrid approaches
that strategically combine both methods to maximize student outcomes. The hybrid model is
something that could be utilized in the target district, due to them having access to both small
group interventions and online program interventions through the curriculum they are currently
implementing. Hybrid models could be used across grade levels, and not only in 6th grade.
The third recommendation would be to investigate subgroup differences. Research could also
explore how interventions affect students with specific characteristics, such as English language
learners, students with disabilities, or students who are significantly below grade level. The
target school district has a large population of students with disabilities and students who are
significantly below grade level. Research could be conducted to explore which method leads to a
higher level of achievement among these subgroups.
Additionally, future studies should consider investigating qualitative factors not captured by
the MAPs assessment, such as student engagement, strategy use, and motivation. Although
MAPs provide reliable quantitative data on academic gains, it does not measure how students
interact with the material or how motivated they are during the intervention. During the study,

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the researcher noted that students seemed more engaged during small group intervention. They
were more willing to participate in small groups than the students who used Waggle. Researchers
could gather observational data, conduct interviews, or administer engagement surveys to
determine how different interventions impact student motivation and preferences. These insights
would add depth to our understanding of why certain approaches may be more effective or
sustainable over time.
The last recommendation would be to analyze the cost-effectiveness of both programs. Given
the resource constraints of many rural schools, studies examining the cost-effectiveness of each
intervention model would help decision-makers allocate funding more efficiently. Since the
results of online programs and small group interventions were similar, rural districts could
choose the intervention that would be most cost-effective for their district.

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Appendix A
SRU IRB Approval

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Appendix B
MAPs Assessment Sample Questions
Vocabulary Use and Acquisition

Reading Literature

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Reading Informational Texts