Running head: AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION CONTEXTS:
A META-ANALYSIS
_______________________
A Dissertation
Presented to
The College of Graduate and Professional Studies
Department of Special Education
Slippery Rock University
Slippery Rock, Pennsylvania
______________________
In Partial Fulfillment
of the Requirements for the Degree
Doctorate of Special Education
_______________________
by
Toriel Chase Herman
December 2021
© Toriel Chase Herman, 2021

Keywords: augmented reality, community-based instruction, social skills, special education,
virtual reality

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COMMITTEE MEMBERS
Committee Chair: Dr. Matthew Erickson, Ed.D.
Chairman and Associate Professor of Special Education
Slippery Rock University
Committee Member: Dr. Karen Larwin, Ph.D.
Professor & YSU IRB Chair
Youngstown State University
Committee Member: Dr. Brian Danielson, Ed.D.
Director, Center for Teaching and Learning
Slippery Rock University

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ABSTRACT
The augmented and virtual reality applications literature base spans more than 30 years with one
of the first studies conducted by Meredith Bricken in 1991. With the advances in technology,
researchers are increasingly examining the use of augmented reality (AR) and virtual reality
(VR) within educational contexts, more specifically special education contexts. VR is one of the
fastest growing technologies (Nuguri, Calyam, Oruche, Gulhane, Valluripally, Stichter, & He,
2021) and AR is growing rapidly showing advances in interaction, navigation, and tracking
within education, entertainment, business, medicine, and other settings (Ablyaev, Abliakimova,
& Seidametova, 2020). Despite AR and VR demonstrating documented success with enriching
learning opportunities and task performances (Billingsley, Smith, Smith, & Meritt, 2019;
Bricken, 1991; Nuguri et al., 2021), there is limited research on applying these programs directly
within a school setting for students with disabilities. To understand the effectiveness of AR and
VR, a meta-analysis of six studies was conducted using hierarchical linear modeling focusing on
functional, transitional, and social skills. Participants included 18 students ages 6-15-years-old
all with a special education diagnosis (i.e., Intellectual Disability or Autism). Results suggest
that these interventions are effective in developing functional, transitional, and social skills with
students with disabilities. Most notably, participants aged 14-15 years old showed the greatest
effect estimates. There were no differences for sex. Limitations and potential future directions
in supporting students with disabilities are discussed.

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TABLE OF CONTENTS
ABSTRACT……………………………………………………………………………………...iv
LIST OF TABLES………………………………………………………………………………viii
CHAPTER 1: INTRODUCTION…………………………………………………………………1
Overview…………………………………………………………………………………..2
Significance of Study………...……………………………………………………….…...3
Definition of Terms…………………………………………………………………….….3
CHAPTER 2: LITERATURE REVIEW………………………………………………………..…5
Educational Disabilities…………………………..……………………………………….5
Intellectual Disability……………………………………………………………...6
Autism……………………………………………………………………………..7
Multiple Disabilities...……………………………………………………………..9
Community-based Instruction……………………………………………………………10
Functional Skills………………………………………………………………….12
Transitional Skills………………………………………………………………..12
Social Skills………………………………………………………………………13
COVID-19 Closure & Online Distance Learning………………………………………...14
Augmented Reality………………………………………………….……………………15
Virtual Reality……………………………………………………………………………18
Brain Impact……………………………………………………………………...20
Purpose of the Study……………………………………………………………………...22
Research Question………………………………………………………………..22
Need for the Study………………………………………………………………..22

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CHAPTER 3: METHODOLOGY………………………………………………………………..24
Restatement of the Purpose………………………………………………………………24
Procedure………………………………………………………………………………...24
Meta-analysis…………………………………………………………………….24
Sampling of Studies………………………………………………………………25
Search Process……………………………………………………………25
Criteria for Selecting Studies……………………………………………..27
Coding of Studies………………………………………………………………...27
Primary Moderators……………………………………………………………...31
Outcome Variable………………………………………………………………..31
Participant Characteristics………………………………………………………..31
Number…………………………………………………………………..31
Sex/Gender, Age, Race/Ethnicity………………………………………...31
Special Education Eligibility and Disability Labels……………………...32
Settings…………………………………………………………………...32
Data Analysis…………………………………………………………………………….32
CHAPTER 4: RESULTS………………………………………………………………………...35
Descriptive Analysis……………………………………………………………………..35
Model 1……………..…….………………………………………………..…….37
Model 2……………………………………………………………………..……38
Model 3…………………………………………………………………………..43
Test of Bias Estimates: Egger’s Test of the Intercept……………………………………..45
Summary of Findings…………………………………………………………………….46

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CHAPTER 5: DISCUSSION…………………………………………………………………….47
Inferences………………………………………………………………………………...47
Limitations……………………………………………………………………………….49
Recommendations………………………………………………………………………..50
Conclusion……………………………………………………………………………….51
REFERENCES…………………………………………………………………………………..53
APPENDIX A: DATA……………………………………...……………………………………65
APPENDIX B: CODING KEY..………………………………………………………………....67
APPENDIX C: PHASES…………………………………………………………………………69
APPENDIX D: MODERATORS………………………………………………………………...81
APPENDIX E: TAU OUTPUT…………………………………………………………………..82
APPENDIX F: IRB APPROVAL………………………………………………………………..84

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LIST OF TABLES
TABLE 1: DESCRIPTIVE INFORMATION FOR AUGMENTED AND VIRTUAL REALITY
STUDIES………………………...………………………………………………………28
TABLE 2: NUMBER OF EFFECT SIZES BY STUDY………………………………………..30
TABLE 3: DESCRIPTIVE DATA – PARTICIPANTS BY GENDER………………………...36
TABLE 4: DESCRIPTIVE DATA – PARTICPANTS BY AGE…...………………………….36
TABLE 5: DESCRIPTIVE DATA – PARTICIPANTS BY DISABILITY…………………….36
TABLE 6: HLM RESULTS FOR A TWO-LEVEL MODEL – STUDY, AR VS VR, AND
SKILL……………………………………………………………………………………40
TABLE 7: AVERAGE TAU-U BY STUDY……………………………………...….................42
TABLE 8: AVERAGE TAU-U BY AR OR VR………………..……………………………….42
TABLE 9: AVERAGE TAU-U BY SKILL…………………….……………………………….42
TABLE 10: HLM RESUTS FOR A TWO-LEVEL MODEL – AGE, SEX, AND AR VS VR...44

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CHAPTER 1: INTRODUCTION
In response to the global COVID-19 pandemic, Governor Tom Wolf closed
Pennsylvania’s public schools for in-person learning beginning March 16, 2020 for two weeks,
which eventually lasted through the remainder of the 2019-2020 school year. The Pennsylvania
Department of Education (PDE) required school districts to create a Continuity of Education
Plan and a Health and Safety Plan for approval. These plans sufficed in completing the 20192020 school term but failed to account for a true provision of a Free and Appropriate Public
Education (FAPE) under the Individuals with Disabilities Education Act (IDEA, 2004). For
students receiving special education services through their Individualized Education Programs
(IEPs), many of their supports and services were unimplemented or, at least, negatively impacted
by the global situation. More specifically, students with low-incidence disabilities, such as
Autism, Intellectual Disability (ID), or Multiple Disabilities (MD), require supports and services
to develop functional and transitional skills. At times, these skills occur via Community-based
Instruction (CBI), as this model lends itself to natural practice of these functional and transitional
skills (e.g., ordering from a menu, buying groceries, accessing public transportation, depositing
or withdrawing money from the bank, and so forth). Unfortunately, these instructional
experiences ceased March 16, 2020 and, in some instances, have yet to resume at particular
school districts.
However, both augmented reality (AR) and virtual reality (VR) programs, which already
exist, could have—should have—been utilized to continue a proper provision of a FAPE for
these students. It is from this perspective that the current study investigated the effectiveness of
augmented and/or virtual realities across various moderators as an instructional tool for students
with low-incidence disabilities to receive functional and transitional skills training (at times,

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through CBI).
Overview
The IDEA (2004) requires local educational agencies (LEA) to service the specific needs
of students with disabilities at school, to include academic instruction, related services,
community experiences, and so forth. Services are based around the student’s individual
strengths and needs. The needs of students are met through an IEP which is a legally binding
agreement between the IEP team which minimally includes parent, student (if 14 years of age or
older in Pennsylvania), LEA representative, regular education teacher, and special education
teacher. Other members could include related services (e.g., occupational therapist (OT),
physical therapist (PT), speech therapist), school counselor, school psychologist, special
education consultant, and/or specialist teachers. Within an IEP, a student must have targeted
goals to meet the individual needs of the student. Often students with low-incidence disabilities
require skill development in the areas of adaptive (functional) skills, transitional skills, and social
skills, which are offered through the IEP by way of CBI. Particularly, individuals with physical,
mental, cognitive, or sensory impairments face significant barriers that negatively affect their
inclusion and participation in typical community activities (Baragash, Al-Samarraie, Alzahrani,
& Alfarraj, 2020).
Virtual programs, originally developed for training task performance in the military
(Furness, 1978), have undergone sophisticated upgrades to now offer students opportunities to
see, hear, and touch virtual objects in real-life contexts without real-life limitations in order to
acquire the necessary skills within IEP’s. The innovation of technology applications can provide
enhanced educational experiences. More specifically, the potential of AR and VR programs
minimizes many obstacles students with disabilities face while maximizing their educational

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experience. As technology continues to advance and online learning environments continue, AR
and VR can change the course of 21 st Century learning and redefine how students with
disabilities receive their education.
Significance of Study
Prior research conducted on AR provides evidence that it is effective for students to make
academic gains (Baragash et al., 2020). The current study will research deeper into special
education needs and provide evidence that AR and VR can help with the specialized teaching
required to facilitate learning for specialized populations. Students with low-incidence
disabilities face unique challenges that require the LEA to not only provide structured,
consistent, and least restrictive environments but also naturalistic, creative, authentic,
challenging, and enriching learning environments that overcomes communicative, cognitive,
behavioral, physical, and developmental deficits. Special education populations require more
assistance in meeting their learning goals.
Definition of Terms
1. Augmented Reality (AR): AR is a form of virtual technology “interconnecting virtual objects
and integrating them into the real world” (p. 186, Gybas, Kostolányová, Klubal, 2019). Users see
and interact with virtual objects through visual overlay and audio speakers (Sahin, Keshav,
Salisbury, and Vahabzadeh, 2018). Furthermore, users look at a screen to experience the virtual
environment (Cumming, 2007; Smedley & Higgins, 2005).
2. Community-based Instruction (CBI): “CBI is the [direct] instruction of functional skills in
the place where they naturally occur” (p. 314, Rowe, Cease-Cook, & Test, 2011, as cited in
Barczak).
3. Least Restrictive Environment (LRE): LRE is “the most integrated setting appropriate” (p.

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523, Stone, 2018). As defined by IDEA (2004), LRE is when children with disabilities are
educated with non-disabled peers to the maximum extent appropriate and the removal from the
regular educational environment occurs only when the severity of the disability cannot be met in
regular classes with supplementary aids and services. Failure to implement LRE is a violation of
providing a free appropriate public education (FAPE).
4. Virtual Reality (VR): VR is an online three-dimensional environment where “generated
objects are displayed on an imaging device” (p. 186, Gybas, Kostolányová, Klubal, 2019). Users
are placed entirely in the virtual world (Sahin, Keshav, Salisbury, and Vahabzadeh, 2018). A
user wears specialized equipment (i.e., headset, gloves, headphones) to be transported/fully
immersed in the virtual environment and interacts through an avatar. The environment is seen by
the user through the equipment (Cumming, 2007). Some or all of the senses are used within the
environment (Eden & Bezer, 2011).

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CHAPTER 2: LITERATURE REVIEW
The IDEA (2004) is a federal legislation that mandates LEAs to provide a FAPE to
students with disabilities by meeting their individualized needs in the areas of academic
instruction, related services, community experiences, transition services, and so forth. This study
will focus on students with low-incidence disabilities, as defined by IDEA, 2004, including
visual and/or hearing impairment, significant cognitive impairment, or any impairment that
requires personnel with highly specialized skills to provide early intervention (EI) or FAPE.
More specifically, this study will highlight the educational disability categories of Intellectual
Disability (ID), Autism, and Multiple Disabilities (MD) and the need for academic instruction,
community experience, and transitional services for functional skill development.
Educational Disabilities
Under the IDEA (2004), students qualify for special education services under one of
thirteen disability categories (i.e., Autism, Deaf-Blindness, Deafness, Emotional Disturbance,
Hearing Impairment, Intellectual Disability, Multiple Disabilities, Orthopedic Impairment, Other
Health Impairment, Specific Learning Disability, Speech or Language Impairment, Traumatic
Brain Injury, Visual Impairment Including Blindness). For this study, the low-incidence
disabilities are the focus (i.e., ID, Autism, Multiple Disabilities), with the following definitions
from IDEA (2004):
•

Intellectual Disability (mental retardation) “means significantly subaverage general
intellectual functioning, existing concurrently with deficits in adaptive behavior and
manifested during the developmental period, that adversely affects a child’s educational
performance” (§300.8 (8));

•

“Autism means a developmental disability significantly affecting verbal and non-verbal

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communication and social interaction, generally evident before age three, that adversely
affects a child’s educational performance. Other characteristics often associated with
Autism are engagement in repetitive activities and stereotyped movements, resistance to
environmental change or change in daily routines, and unusual responses to sensory
experiences” (§300.8 (1)(i));
•

Multiple Disabilities means concomitant impairments (such as [ID]-blindness or [ID]orthopedic impairment), the combination of which causes such severe educational needs
that they cannot be accommodated in special education programs solely for one of the
impairments. Multiple disabilities does not include deaf blindness” (§300.8 (7)).

According to the Penndata Special Education Data Report School Year 2020-2021, 6.2%
(19,070), 12.1 % (37,218), and 1.0% (3,075) of students are identified as having ID, Autism, and
MD, respectively.
Intellectual Disability
The American Association on Intellectual and Developmental Disabilities (AAIDD)
asserts that students with ID require a FAPE that includes fair evaluation, challenging goals and
objectives, and the right to progress by receiving individualized supports, quality instruction, and
access to the general education curriculum in inclusive settings (Thompson, Walker, Snodgrass,
Nelson, Carpenter, Hagiwara, & Shogren, 2020). ID is a diverse disability that affects
individuals differently; however, it is commonly characterized by problems in adaptive skills
(Eden & Bezer, 2011; McNicholas, Floyd, Woods, Singh, Manguno, & Maki, 2018; Pan,
Totsika, Nicholls, & Paris, 2018; Smogorzewska, Szumski, & Grygiel, 2018). Adaptive skills,
which are comprised of conceptual skills, social skills, and practical skills (de Oliveira
Malaquias, Malaquias, Lamounier Jr., & Cardoso, 2013), are essential for daily living

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functioning, interacting with others, and working. More specifically, adaptive behavior includes
social functioning defined as deficits in understanding emotions, reduced communication skills,
speech and language difficulties, lack of reciprocal communication which can lead to further
difficulties in the educational environment and postsecondary transitioning (Smogorzewska et
al., 2018). Chang, Kang, and Huang (2013) cite that those individuals with cognitive
impairments are systematically excluded from working, as they are regarded as unemployable,
which reinforcers the notion that this population requires training in functional skills.
Due to the need for developing essential daily living skills, students with ID can benefit
from direct instruction and practice with independent and functional living skills. Online
environments appear to demonstrate a way for individuals to learn and transfer these required
skills in real-life situations. Computer-based technology and games are enjoyable for people
with disabilities and provide an option to promote skill development within mainstream
education settings (Standen, Brown, & Cromby, 2001).
Rubenstein, Daniels, Schieve, Christensen, Van Naarden Braun, Rice, and colleagues
(2017), as cited in Howard, Copeland, Gifford, Lawson, Bai, Heilbron, and Maslow (2021),
indicate that a decrease in prevalence of ID over time is linked to the increase of prevalence of
Autism, which leads to focusing on the growing needs of students with autism.
Autism
Prevalence rates of Autism has increased, thus requiring schools to provide appropriate
education services and raising the standards of a FAPE. Endrew F. v. Douglas County School
District ruled that a child with Autism must have an IEP that appropriately challenges the
student. Therefore, although goals may differ, each student will be given the chance to meet
challenging objectives (Wangsgard & Cardon, 2020). More specifically, students with Autism

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require training in skill development for daily life in the community, which is grouped into five
areas that include self-care, recreation, employment, and community participation (Clark, Field,
Patton, Brolin, & Sitlington, 1994, as cited in Chiang, Ni, & Lee, 2017).
Autism is a multifaceted disability that has varying degrees of symptoms, deficits,
impacts, and outcomes that influence the need for life skills training. One of the most common
symptoms are social communication and social interaction deficits in individuals with Autism
(American Psychiatric Association, 2013; Chen, Lee, & Lin, 2015; Ghanouni, Jarus, Zwicker,
Lucyshyn, Mow, & Ledingham, 2018; Hu & Han, 2019; Jeffs, 2009; Self, Scudder, Weheba, &
Crumrine, 2007). Social interaction can be defined as reciprocal communication where
individuals initiate and respond to social stimuli with others (Merrell & Gimpel, 1988; Shores,
1987, as cited in Wang, Laffey, Xing, Galyen, & Stichter, 2017). Individuals with autism lack
the ability to read verbal and nonverbal social cues (i.e., gestures, body movement, eye contact,
facial expressions, and perspective-taking), which can result in exhibiting socially inappropriate
behavior (Wang et al., 2017) and lead to fewer peer relationships, social networks, and
engagement in activities (Ghanouni et al., 2018). Additionally, social skill deficits can lead to
further difficulties in academic and occupational outcomes (Ke & Im, 2013).
When comparing students without disabilities and students with Autism, the latter have
poorer postsecondary outcomes. In other words, less than half pursue postsecondary education
and only about half find a paid job (Chiang, Cheung, Hickson, Xian, & Tsai, 2012; Chiang,
Cheung, Li, & Tsai, 2013, as cited in Chiang et al., 2017). Evidence-based practices (i.e., peer
reviewed educational interventions that are consistent and reliable) are most effective when
working with students with Autism (Garland, Vasquez III, & Pearl, 2012). Now regarded as an
evidence-based practice, life skills training can improve secondary transition for those with

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Autism. Life skills training should be implemented within both classroom and community
settings in order for students to develop and apply learned skills in daily living environments
(Chiang et al., 2017).
Sahin, Keshav, Salisbury, and Vahabzadeh (2018) propose that technology-based
interventions can be particularly suited for individuals with Autism due to a propensity to use
digital tools with an expressed interest in electronic media, preference for predictable
interactions, enjoyment in game-like tasks, and preference to computer-generated speech. Hu
and Han (2019) support the use of technology and electronics to provide a natural, predictable,
and less aversive environment for students with Autism. Moreover, Chia and Li (2012) suggest
technology is portable and flexible, thus allowing for various advantages for children with
difficulties. Self and colleagues (2007) propose virtual environments assist in generalization of
skills, specifically communication skills for children with Autism. Therefore, AR and VR
interventions may be particularly effective for students with Autism that require functional life
skill development.
Multiple Disabilities
Students with MD often require the most extensive supports compared to all the disability
categories under IDEA, exhibiting deficits in motor skills, cognitive skills, social skills, and selfcare (DÜZKANTAR, ATLIN, ÖĞÜLMÜŞ, & GÖRGÜN, 2020), with documented difficulties
achieving employment, postsecondary education, and independent community living outcomes
(Shattuck, Wagner, Narendorf, Sterzing, & Hensley, 2011; Shogren & Plotner, 2012, as cited in
Qian, Johnson, Wu, LaVelle, Thurlow, & Davenport, 2020). Consequently, their IEPs focus on
functional life skills that help students to be more independent across various settings (e.g.,
school, home, community).

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State legislation requires students with MD to progress in the general education
curriculum in addition to receiving a modified functional life skills curriculum (Bobzien, 2014).
Specifically, students with a concurrent visual impairment or blindness require skills to build
orientation skills, navigation of the environment, and community literacy skills. Students with a
concurrent orthopedic impairment require development in community literacy and navigation,
mobility, social skills, and safety skills. As seen in these examples, the combination of multiple
disabilities can manifest in complex needs and, consequently, necessitate creative or unique
supports. There are multiple challenges to providing opportunities for students with MD to
practice and acquire such skills in typical educational settings; however, the advantages to online
learning environments, in particular, include repetition of skills in a safe, interactive, and
engaging environment guided by an educator (Jeffs, 2009).
The unique challenges that students with disabilities (i.e., ID, Autism, and MD) face
require special educational programming to meet their individual needs. Often times, those
needs cannot be meet with typical general education curriculum or strictly within the structure of
a classroom setting; therefore, instruction must be adapted to provide an environment to acquire
and practice new skills. Community-based instruction provides students an opportunity to
develop real world skills.
Community-based instruction
Community-based instruction (CBI) is an integral part of educational programming for
students who have difficulties developing and applying daily living and other functional and/or
transitional skills in real-life contexts. CBI supports students with disabilities by preparing them
to transition into postsecondary life in a safe and natural setting. These students often struggle to
generalize the skills learned in the structured environment of a classroom into other settings (e.g.,

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community) since it does not emulate the real-world environment that is variable and
unpredictable (Barczak, 2019; Cromby, Standen, & Brown, 1996; Hopkins & Dymond, 2020).
For example, CBI provides instruction for students with ID, Autism, or MD the opportunity to
learn specific skills (e.g., use money, communicate needs, social interactions, and so forth) in
order to go grocery shopping, eat in a restaurant, go to a movie, and ride public transportation, all
of which enhances their acquisition of independency.
CBI allows adults, by way of the special education teacher and paraprofessionals, to
provide guidance and reinforcement of skills, which is important for learning of children with
disabilities (Ke & Im, 2013). CBI, combined with direct classroom instruction, has been found
to be more effective and allows students to acquire the necessary skills in less time than
classroom instruction alone (Bates, Cuvo, Miner, & Korabek, 2001; Branham, Collins, Schuster,
& Kleniert, 1999; Cihak, Alberto, Kessler, & Taber, 2004, as cited in Hopkins & Dymond,
2020). Instruction provided in the community decreases the need for repetitive instruction across
various settings and allows for focused instruction of the targeted skill within the applicable
environment, which decreases the need for students to generalize (Barczak, 2019). Other
benefits of CBI include providing students with disabilities opportunities to familiarize
themselves with the community organizations and build positive relationships with community
members, which can positively affect postsecondary opportunities for these students (Barczak,
2019).
Research on successful methods for teaching these skills has been declining even though
there is evidence supporting CBI as an evidence-based strategy to prepare students with lowincidence disabilities transitioning into adulthood (Hopkins & Dymond, 2020). Historically,
some students have been precluded from CBI, which has most notably been exacerbated during

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and after the COVID-19 pandemic. School districts are limited in providing CBI due to
transportation, funding, staffing, and administrative support, and it also reduces time in the
classroom. To that end, the advances in educational technology, such as AR and VR, must be
explored to enhance CBI instruction to promote the acquisition of functional, transitional, and
social skills.
Functional Skills
Functional skills as defined as daily living skills that can positively or negatively affect
the overall quality of life (Bobzien, 2014). In daily living, individuals with disabilities encounter
difficulties in acquiring the skills to develop self-determination, self-help, and happiness (e.g.,
personal well-being, pleasure, and satisfaction) which can often be overlooked within
educational contexts (Bobzien, 2014). Examples of functional skills important for students with
disabilities to develop include the practical skills of cooking, cleaning, sewing, time
management, and so on. Also included in functional skills development is physical skills, or
activities that allow an individual with a disability to physically navigate tasks (e.g., navigation
within a store or restaurant) and interactions which can reduce social isolation and promote
relationships (McMahon, Cihak, & Wright, 2015, as cited in Baragash et al., 2020). Simulated
learning environments provide an opportunity for students with disabilities to practice mobility,
navigation, and advocacy skills within real-life contexts (Jeffs, 2009). VR can enhance
functional performance in a flexible and ecologically valid way to improve specific skills in reallife simulations that are safe, interactive, and motivating for individuals with physical deficits
(Kirshner, Weiss, & Tirosh, 2011).
Transitional Skills
Transitional skills are defined as overall skills to transition to be more independent

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moving from school age to adulthood across settings (e.g., home, community, work). These
skills include community literacy (e.g., reading labels, maps, menus, bus schedules, and so
forth), financial skills (e.g., purchasing skills, buying groceries, ordering from a menu, using the
bank, and so forth.), occupational/vocational skills (e.g., applying for a job, time management,
and so forth), and safety skills (e.g., reading traffic signs, crossing a cross walk, and so forth;
Jeffs, 2009). Simulated environments allow individuals to explore, navigate, and manipulate the
environment in order to utilize the necessary skills to succeed in the real world. For example,
virtual environments were found to be new and effective ways for teaching skills for independent
living for individuals with ID (Standen, Brown, & Cromby, 2001).
Social Skills
Improving social skills, as defined as verbal and nonverbal communication, social
interaction (e.g., reciprocal conversation, taking another’s perspective, asking for assistance, and
so forth) and understanding and expressing emotions (e.g., speech, gestures, eye contact and
body posture; Ke & Im, 2013), is a common goal within an IEP for students with low-incidence
disabilities. Social skills training can facilitate understanding of social contexts that students
with social deficits find difficult to interpret (Ghanouni et al., 2018). Therefore, providing them
instruction and practice via innovative tools can improve their skills and promote positive
behavior (Baragash et al., 2020). Communication skills are essential for daily life, which can
impact an individual’s social, emotional, and learning foundation (Lan, Hsiao, & Shih, 2018).
Consequently, it is imperative to improve social communication skills, thereby improving a
student with a disability’s daily functioning.
Research suggests that using virtual environments demonstrates potential for teaching
social skills for individuals with social deficits, including disabilities such as ID, Autism, and

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MD (Cobb, 2007; Dieker, Hynes, Hughes, & Smith, 2008; Mitchell, Parsons, & Leonard, 2007).
More specifically, virtual environments provide students with Autism an innovative way to
challenge their typically rigid and inflexible language, behavior, and mental concepts (Jeffs,
2009).
Providing CBI to facilitate the development of functional, transitional, and social skills is
critical to positively impacting student achievement and success. Although many factors inhibit
school districts from providing CBI (i.e., staffing, budget, safety, and transportation), a major
impact on CBI occurred globally during the COVID-19 pandemic resulting in mass school
closures and prolonged online distance learning.
COVID-19 Closure & Online Distance Learning
During the 2020 global COVID-19 pandemic, mass school closures resulted in students
receiving educational instruction by way of online distance learning (ODL) defined as virtual or
remote learning, not face to face, via the internet (Eldokhny & Drwish, 2021). For example,
school districts used internet applications such as Zoom and Google Classroom. During the
2019-2020 school year, all schools in Pennsylvania were closed for about 13 weeks. Although
districts operated under state approved Continuity of Education Plans for the remainder of the
year, a FAPE could not be fully provided to students with disabilities. Despite educators’
utilization of ODL in new ways in attempts to be effective, CBI was significantly impacted and
essentially eliminated during this time. Consequently, COVID-19 Compensatory Services
(CCS) was offered to meet special education services missed due to the closures. A service to be
considered as part of special education programming for CCS is CBI.
As schools prepared for reopening for the 2020-2021 school year all districts had to
develop and implement a School Health and Safety Plan that followed all state policies and

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recommended state health and safety guidelines. Many school districts opted to remain closed,
thereby continuing ODL, while others provided hybrid models, and fewer yet opened
completely. Due to social distancing, mask mandates, and other health and mitigations efforts,
the provisions continued to inhibit CBI and districts did not creatively adapt to address this
problem. Specifically, one consideration overlooked by schools was the use of AR and VR to
provide CBI, especially for students with low-incidence disabilities.
Due to comorbidity issues, these students can, at times, be regarded as medically fragile
and, with this designation, many parents/guardians opted for their students to remain ODL longer
than the state or school district required. Although a vaccination was developed and approved
for adults and most teenagers, children elementary-aged cannot yet receive the vaccination and
other parents may opt not to have their child receive the vaccination regardless of the child’s age,
which could lead to continued ODL for the 2021-2022 school year. Therefore, CBI through AR
and VR continues to be a relevant topic of research and discussion. Some studies have shown
that incorporating AR with ODL stimulates learning (Lytridis, Tsinakos, & Kazanidis, 2018, as
cited in Eldokhny & Drwish, 2021). While virtual environment technology emerged in the
1970s with the latest advances in technology, there has been a dramatic rise in utilization
continuing to grow since the early 2010s (Howard, 2018 and Plunkett, 2014, as cited in Howard
& Gutworth, 2020).
Augmented Reality
An accepted definition of AR is defined as the “integration of three dimensional (3D)
virtual objects into a 3D real environment in real time” (Azuma, 1997, as cited in Gybas,
Kostolányová, Klubal, 2019, p. 185), and further understood as a simpler way to complete a task
in the real world by combining virtual and real environments ((Dubois, Nigay & Troccaz, 2001,

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
as cited in Gybas, Kostolányová, & Klubal, 2019; Eldokhyn & Drwish, 2021). Not only is AR a
form of virtual technology, but specific features enable an individual to see information at the
right time and place by linking realistic goals with 3D images and graphics that present facts,
time, and spatial obstacles more effectively (Eldokhny & Drwish, 2021). AR technology takes
virtual objects and audio guidance by way of a visual overlay and audio speakers allowing users
to see and interact with the virtual world around them (Sahin et al., 2018). From an educational
standpoint, AR is displaying text, video, and images (i.e., any computer-generated materials)
through technology into a real-world environment (Yuen, Yaoyuneyong, & Johnson, 2011, as
cited in Gybas, Kostolányová, & Klubal, 2019).
AR technology provides a realistic opportunity that enriches student engagement,
motivation, and performance by allowing students to repetitively practice skills that are more
difficult to repeat in reality. Moreover, AR equips educators to provide a learning environment
individualized to meet students’ creativity, imagination, learning style, and cognitive ability all
while providing an environment suitable for collaborative, cooperative, and effective learning
(Eldokhyn & Drwish, 2021). AR can also be commonly referred to as simulations or computer
displayed virtual worlds (Cumming, 2007). In a simulation, a student assumes a role and makes
choices while maneuvering through the environment (Smedley & Higgins, 2005).
Chen, Law, sand Chen (2018) as cited in Wang (2020) elaborate that AR, the
combination of visual information with physical objects, helps present and explain educational
content, more specifically abstract content. For example, Cheng and Tsai’s (2013) research
suggests that image-based AR benefits students’ learning of practical skills and conceptual
understanding. Research evidence not only supports the use of AR for educational learning but
suggests benefits of AR for students with disabilities (Baragash et al., 2020; Cobb, 2007; Gybas

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
et al., 2019; Jeffs, 2009; Lan et al., 2018; Wang, 2020). AR applications have been widely used
to facilitate skill acquisition for individuals with learning, communication, behavior, and
developmental disorders (Baragash et al., 2020). Sahin and colleagues (2018) highlight that
technology-based interventions can support improvement in social-emotional skills,
communication ability, academics, employment skills, and behavior for individuals with Autism.
Chen and colleagues (2015) found evidence in their research that an AR program can be used to
teach facial emotional expressions recognition and response. Skills acquired through AR
programs help individuals with disabilities access their community and leisure activities (Chang,
Chen, & Huang, 2011, as cited in Lin & Chang, 2015).
AR provides students with Autism a visual and auditory experience that promotes
generalization, decreases rigidity, and is well-suited to meet their needs to learn social-emotional
skills. AR applications on smartphones and tablets have shown improvement in identifying and
understanding social cues, emotions, and facial expressions in book characters (Sahin et al.,
2018). In terms of safety and sensory challenges, Sahin and collegues (2018) found in their
study that individuals with Autism were able to use AR technology (e.g., AR smart glasses)
without reporting any major negative effects (e.g., headache, eye strain, dizziness, and other
sensory and motor discomfort).
AR simulations are more affordable and available compared to full-immersion VR
programs (Cumming, 2007) making them more accessible within educational contexts. AR fills
in the gaps to complete educational learning (Eldokhny & Drwish, 2021) and, therefore, is not
considered to be a replacement but in addition to direct classroom instruction. Examples of AR
programs or applications include Aurasma application, Let’s go banking!, Augmented reality
role-playing game (AR-RPG), Augmented reality concept map (ARCM), Kinect Skeletal

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
Tracking (KST) system, Meal-Maker, and Heads Up Navigator. Until the beginning of the 21st
century, the terms AR and VR had similar definitions and were used interchangeably. However,
the introduction of mobile technology helped delineate the difference between the two terms
(Gybas et al., 2019).
Virtual Reality
In contrast to AR, VR can be defined as a representation of computer-generated, 3D, real
life environments (Cobb, 2007; Chia & Li, 2012; Cromby et al., 1996; Fitzgerald, Yap, Ashton,
Moore, Furlonger, Anderson, Kickbush, Donald, Busacca, & English, 2018; Howard &
Gutworth, 2020; Hu & Han, 2019; Ke & Im, 2013; Muscott & Gifford, 1994; Self et al., 2007;
Standen et al., 2001) that a user autonomously navigates with an avatar (i.e., graphical
representations) (Ke & Im, 2013). Wang, Laffey, Xing, Galyen, and Stichter (2017) define VR
as an online simulated environment where users have an opportunity to interact with others
locally or globally using avatars, also considered a collaborative virtual environment (CVE).
Zhang, Weitlauf, Amat, Swanson, Warren, & Sarkar (2020) define a CVE as a computer-based,
online space where multiple users collectively interact including across various distances.
VR environments typically require a user to wear a head mounted stereoscopic display
(e.g., Leap Motion, HTC Vive, Oculus Rift, Samsung Gear VR, and Google Cardboard) with
headphones that allow a user to transmit and receive data, thus creating a total immersive
experience (Cumming, 2007; Muscott et al., 1994; Newbutt, Bradley, Conley, 2020; Smedley &
Higgins, 2005; Standen et al., 2001). Movements by the user are fed into the computer which
generates a graphic display in real time based on the user’s activity (Cromby et al., 1996). In
contrast to AR, VR headsets allow the user to place themselves and their senses completely
within the virtual world, thus removing them from seeing and hearing in the real world (Cobb,

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
2007; Radianti, Majchrzak, Fromm, & Wohlgenannt; 2020; Sahin et al., 2018), which can create
a Cave Automatic Virtual Environment (CAVE). A CAVE uses surround vision projection
where two or more people can experience the environment simultaneously while others observe
(Cumming, 2007; Howard & Gutworth, 2020; Powers & Darrow, 1994; Smedley & Higgins,
2005). The CAVE environment can specifically benefit individuals with severe physical
disabilities (Powers & Darrow, 1994).
VR can be a useful tool for individuals with disabilities because it offers a safe,
structured, and controlled learning environment to acquire and practice the necessary
competencies (Fitzgerald et al., 2018; Howard & Gutworth, 2020; Kirshner et al., 2011; Ke &
Im, 2013; Self et al., 2007) to improve functional, transitional, and social skills. Collaborative
virtual learning environments (CVLE) deliver a distinct likeness to real-life social scenarios
(Bailenson, Yee, Merget, & Schroeder, 2006; Yee, Bailenson, Urbanek, Chang, & Merget, 2007,
as cited in Wang et al., 2017). Additional advantages to VR for individuals with disabilities
include creating a real-life practice environment where mistakes can be made without fear of
danger or embarrassment, individuals with mobility issues can more easily navigate situations,
and the experiences are not limited by caregivers who hinder the individual doing things on their
own. Lastly, but particularly important for individuals with disabilities, virtual environments can
be manipulated in ways the real world cannot. For example, scaffolding tasks so the user can
start with simple skills and move to more complex skills at their individualized pace (Cromby et
al., 1996; Standen et al., 2001).
Virtual learning environments (VLE) allow students to engage in interactive learning, but
also provide the learner control over the learning process (Jeffs, 2009). VR can be a useful tool
for individuals with disabilities because it supports generalization of social interactions into the

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
real world (Beaumont & Sofronoff, 2008; Parsons & Cobb, 2011; Parsons & Mitchell, 2002;
Schmidt & Schmidt, 2008; Strickland, McAllister, Coles, & Osborne, 2007, as cited in Ke & Im,
2013; Zhang et al., 2020) by providing role-play through flexible scenarios which helps develop
cognitive flexibility. More specifically, individuals with Autism can practice a variety of
responses to simulated but real-life scenarios with reduced anxiety yet increased cognitive
flexibility (Parsons & Mitchell, 2002, as cited in Ke & Im, 2013). Standen and colleagues
(2001) cite Sims (1994) who suggests individuals with ID, who typically display passive
behavior, can benefit from interactive online learning environments where learning is controlled
by the student, thus providing an environment that is self-paced with decreased peer irritation
and increased attention to task.
VR programs such as Second Life, iSocial, Virtual Café, and virtual reality job interview
training (VR-JIT) are examples of programs that can be infused into special education
classrooms to develop daily living skills (i.e., functional, transitional, and social) and have a
major impact on students with low-incidence disabilities by improving their overall ability to
navigate in society.
Brain Impact
Pugnetti, Mendozzi, Barberi, Rose and Attree (1996) state in numerous research papers
that VR profoundly affected the brain psychologically, neurophysiological, and emotionally.
More specifically, VR affects the brain in terms of learning, cognition, perception, affect, and
motivation. Pugnetti and colleagues (1996) examined brain functioning using
electroencephalography (EEG) and event-related potential (ERP) during VR sessions. Maps of
the brain showed distinct multi-channel changes in the brain before VR sessions compared to
during VR sessions. The authors’ findings suggest neurophysiological correlations. The specific

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
areas of the brain affected were the anterior regions and frontal lobes (Pugnetti et al., 1996).
Furthering the research on the brain and VR, Rodriguez Ortega, Rey, Clemente Bellido,
Wrzesien, and Alacañiz Raya (2015) found brain activation in the frontal lobe, limbic lobe, and
temporal lobe during a VR simulation which is associated with emotional processes (e.g.,
sadness and happiness). Specific areas of the brain activated included the limbic lobe (e.g.,
emotional regulation), occipital lobe (e.g., cognitive reappraisal), parietal lobe (e.g., spatial
processing and mental rotation tasks), and the temporal lobe and parietal lobe (e.g., sense of selfawareness, self-consciousness, presence, and navigation).
Zanier, Zoerle, Di Lernia and Riva (2018) and De Luca, Maggio, Maresca, Latella,
Cannavò, Sciarrone, Lo Voi, Accorinit, Bramanti, and Calabrò (2019) state that VR requires
cognitive involvement that may improve brain plasticity and regenerative processes. VR
programs have been used to detect visual-vestibular deficits in adults, evaluate executive
dysfunctions, and assess residual executive functions in individuals with traumatic brain injury
(TBI). Other uses were to assess subclinical cognitive abnormalities in individuals that suffered
a concussion but were asymptomatic. VR tools are demonstrated effective tools for
neurorehabilitation. VR has the potential to address cognition, behavior, attention, memory,
executive functioning, behavioral control, mood regulation, and many other areas individuals
with brain deficits exhibit (Zanier et al., 2018).
Previous studies on AR and VR have yielded positive results worth future exploration.
As technology continues to advance and the difficulties of students with disabilities require
innovative yet evidence-based strategies to address, a meta-analysis to compile results on AR
and VR programs with students with low-incidence disabilities (i.e., ID, Autism, and MD)
provides further evidence for education entities to implement.

21

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
Purpose of the Study
Through an investigation of the research literature, the current study hopes to understand
the effectiveness of AR and/or VR across various moderators as an instructional tool for students
with low-incidence disabilities to receive functional and transitional skills training. With
increasing numbers of students pursuing remote or online education settings, schools face
challenges of meeting the IDEA (2004) mandates to ensure students with disabilities receive a
FAPE, which is individualized to meet the students’ specific needs through an IEP. More
specifically, students who need CBI for development and implementation of functional and
transitional skills training, the state mandates schools to develop goals, provide instruction, and
monitor progress in relation to these aforementioned skills. A consequence of virtual schooling
is the lack of opportunity to provide students with CBI opportunities. AR and/or VR programs
offer students with disabilities receiving remote instruction opportunities to continue receiving
direct instruction and implementation of functional and transitional skills.
Research Question
More specifically, the research question guiding this study is:
How effective are augmented and virtual realities across various moderators (i.e., school
level, sex, and AR or VR)?
By investigating and answering this research question, the current study hopes to add to the
literature on augmented and virtual realities in special education contexts and provide teachers
with an evidence-based intervention to use with students with low-incidence disabilities to
receive functional and transitional skills training.
Need for the Study
Although AR and VR have been shown effective in educational contexts (Baragash et al.,

22

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
2020; Cobb, 2007; Cromby et al., 1996; Cumming, 2007; de Oliveira Malaquias et al., 2013;
Eldokhny & Drwish, 2021; Gybas et al., 2019; Hu & Han, 2019; Jeffs, 2009; Lan et al., 2018;
Muscott et al., 1994; Powers & Darrow, 1994; Sahin et al., 2018; Smedley & Higgins, 2005;
Standen et al., 2001; Wang, 2020; Wu, Lee, Chang, & Liang, 2013), AR and VR utilized for a
FAPE for students with low-incidence disabilities to meet CBI goals (functional, transitional, and
social skills) has only recently been explored. At least six studies have investigated AR and/or
VR for students with ID, Autism, and/or MD for CBI. With Bricken (1991) publishing the first
known study using VR, she has influenced, and is cited in, subsequent studies on the topic.
However, additional research is needed on both AR and VR as the prevalence of technology in
special education classrooms, specifically with low-incidence populations, increases. After all,
70 percent of school-aged students own a device (Bedesem, 2012) and 90 percent of children in
the United States between the ages of 5 and 17 use a computer daily (DeBell & Chapman, 2003,
as cited in Cumming, 2007). Furthermore, increasingly schools are now implementing 1:1
device programs that can be used for AR/VR to improve functional, transitional, and social
skills. For example, iPads can be used to utilize an AR program iSocial for a student with
Autism to practice social skills. To that end, this study investigated the effectiveness of AR and
VR across various moderators.

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
CHAPTER 3: METHODOLOGY
Restatement of the Purpose
The current study is a meta-analysis of six studies in order to understand the effectiveness
of AR and VR as an instructional method for students with low-incidence disabilities to receive a
FAPE through CBI in order to learn functional, transitional, and social skills. More specifically,
this meta-analysis employed a hierarchical linear modeling as the quantitative method to answer
the following research question:
How effective are augmented and virtual realities across various moderators (i.e., school
level, sex, and AR or VR)?
Procedure
Meta-analysis
The meta-analysis method was chosen to investigate the overall effect of AR and VR on
transitional, functional, and social skills of students with low-incidence disabilities. This method
was chosen because it combines data from multiple studies to determine the effect size estimates
of multiple moderators (e.g., school level, sex, and AR or VR) on outcome variables. A smaller
meta-analysis (i.e., less than 200 events) is useful for summarizing information and producing
recommendations for future research (Flather, Farkough, Pogue, & Yusuf, 1997). Regardless of
the breadth of the meta-analysis, combining multiple studies with smaller sample sizes into one
larger sample size increases reliability and validity (Flather, Farkough, Pogue, & Yusuf, 1997;
Glass, McGaw, & Smith, 1981).
A comprehensive search was conducted for studies utilizing AR and VR to analyze
dependent variables of transitional, functional, and social skills. Continuing along the
framework, as outlined by Glass, McGraw, and Smith (1981), the six identified studies were then

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
reviewed and coded. Finally, the individual and overall effect size estimates for each moderator
were calculated using hierarchical linear modeling, as described by Shadish (2014). Specifically,
data points will be extracted from the sample study graphs using WebPlotDigitizer and coded for
the total number of effect size estimates to be analyzed through hierarchical linear modeling.
Sampling of Studies
Search process. In order to complete the comprehensive search for existing data on AR
and VR studies, the following chosen search terms were entered into EBSCOhost:
•

Augment* reality or AR OR Virtual reality or VR AND Special Education,

•

Augment* reality or AR AND Virtual reality or VR AND Special Education,

•

Augment* reality or AR AND Virtual reality or VR AND Autism

•

Augment* reality or AR AND Virtual reality or VR AND Multiple Disabilit*

•

Augment* reality or AR AND Virtual reality or VR AND Intellectual Disabilit* or
Mental Retardation

•

Augment* reality or AR OR Virtual reality or VR AND Autism

•

Augment* reality or AR OR Virtual reality or VR AND Multiple Disabilit*

•

Augment* reality or AR OR Virtual reality or VR AND Intellectual Disabilit* or Mental
Retardation

•

Augment* reality or AR OR Virtual reality or VR AND Autism AND functional skills

•

Augment* reality or AR OR Virtual reality or VR AND Multiple Disabilit* AND
functional skills

•

Augment* reality or AR OR Virtual reality or VR AND Intellectual Disabilit* or Mental
Retardation AND functional skills

•

Augment* reality or AR OR Virtual reality or VR AND Autism AND Transition* skills

25

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
•

Augment* reality or AR OR Virtual reality or VR AND Multiple Disabilit* AND
Transition* skills

•

Augment* reality or AR OR Virtual reality or VR AND Intellectual Disabilit* or Mental
Retardation AND Transition* Skills

•

Augment* reality or AR OR Virtual reality or VR AND Autism AND Social skills

•

Augment* reality or AR OR Virtual reality or VR AND Multiple Disabilit* AND Social
skills

•

Augment* reality or AR OR Virtual reality or VR AND Intellectual Disabilit* or Mental
Retardation AND Social skills

•

Augment* reality or AR AND Special Education,

•

Augment* reality or AR AND Community Based Instruction or CBI,

•

Augment* reality or AR AND functional skills,

•

Augment* reality or AR AND transitional skills,

•

Augment* reality or AR AND social skills,

•

Virtual reality or VR AND Special Education,

•

Virtual reality or VR AND Community Based Instruction or CBI,

•

Virtual reality or VR AND functional skills,

•

Virtual reality or VR AND transitional skills, and

•

Virtual reality or VR AND social skills.

Finally, from the resulting studies from the aforementioned search terms, other studies were
identified through a review of their references and searched for in EBSCOhost. It should be
noted that the search was restricted to peer-reviewed articles with no limitations to publication
date and all studies were written in English.

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
Criteria for selecting studies. The following inclusion criteria to qualify research
studies for the current study were:
1. Study employed single-subject research design.
2. Study participants included at least one individual.
3. Study settings included at least one educational setting.
4. Study participants included at least one low-incidence disability (i.e., Autism, ID, MD).
5. Study intervention or independent variables included augmented and/or virtual realities.
6. Study dependent variables included quantitative measures of transitional, functional, and
social skills.
The aforementioned search process and criteria filtering yielded six studies.
Coding of Studies
Table 1 summarizes the information from the six participating studies based on these
categories: study, participant demographics, setting, type of disability, research design,
independent variable, and dependent variable. Table 2 summarizes data based on these
categories: study, number of participants, number of dependent variables, number of conditions,
and number of effect size estimates. Specific coding information can be found in the
corresponding Appendices A-D.

27

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
Table 1
Descriptive Information for Augmented and Virtual Reality Studies

Author(s),
Year

Participant
Characteristics

Independent
Variable

Setting

Dependent
Variable with
Measures

Research
Design

Cheng,
Huang, &
Yang, 2015

Three
participants
Male
Unknown
ethnicity
Ages 10-13
Autism
Special
education
eligible

Unknown
school level
Unknown
grade

VR

Oral exam
scores on
social
behavioral
scale (SBS)

Multiple
baseline
across
participants
AB plus
maintenance

Cihak,
Moore,
Wright,
McMahon,
Gibbons, &
Smith, 2016

Three
participants
Male
Unknown
race/ethnicity
Ages 6 & 7
Autism
Special
education
eligible

Elementary
school
Grades 1 & 2

AR

Number of
task-analyzed
steps
completed
independently
(out of 16)
Event
recording

Multiple
baseline
across
participants
AB plus
maintenance

Kang &
Chang,
2019

Three
participants
2 Male
1 Female
Unknown
race/ethnicity
Ages 14 & 15
Intellectual
Disability
Special
education
eligible

Junior high
School
Grade 9

AR

Percentage of
correct task
steps for cash
withdrawal
and money
transfer

Multiple
baseline
across
participants
AB plus
maintenance

Lee, Chen,
Wang, &

Three
participants
2 Male

Elementary
School

AR

Ability to
identify the
correct

Multiple
baseline

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
Chung,
2018a

1 Female
Ages 8-9
Autism
Special
education
eligible

Unknown
Grade

Lee, Lin,
Chen, &
Chung,
2018b

Three
participants
2 Males
1Female
Ages 7-9
Autism
Special
education
eligible

Elementary
School
Unknown
Grade

AR

Lee, 2021

Three
Elementary
AR
participants
School
2 Males
Unknown
1 Female
Grade
Ages 7-9
Autism
Special
education
eligible
Note: AR = Augmented Reality; VR = Virtual Reality

29

greeting
behavior

across
participants
AB plus
maintenance

Error rate

Multiple
baseline
across
participants
AB plus
maintenance

Ability to
accurately
identify body
gestures

Multiple
baseline
across
participants
AB plus
maintenance

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
Table 2
Number of Effect Sizes by Study

Number of
Participants

Number of
Dependent
Variables

Number of
Conditions

Number of
Effect Sizes

Cheng, Huang,
& Yang, 2015

3

1

1

3

Cihak, Moore,
Wright,
McMahon,
Gibbons, &
Smith, 2016

3

1

1

3

Kang & Chang,
2019

3

2

1

6

Lee, Chen,
Wang, & Chung,
2018a

3

1

1

3

Lee, Lin, Chen,
& Chung, 2018b

3

1

1

3

Lee, 2021

3

1

1

3

Author(s), Year

Total

30

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
Primary Moderators
This study focused on three primary moderators which included school level, sex, and
AR or VR. By determining the effect size estimates of AR or VR interventions on social,
transitional, and functional skills, it allows the generalization of each study’s results across
school settings. Similarly, comparing the effect size estimates among boys versus girls allows
the generalizability across all students. Finally, with AR being more researched than VR (Cihak,
Moore, Wright, McMahon, Gibbons, & Smith, 2016; Kang and Chang, 2019; Lee, Chen, Wang,
& Chung, 2018a; Lee, Lin, Chen, & Chung, 2018b; Lee, 2021), evaluating effect size estimates
for AR and VR adds to the literature about VR as a viable intervention for developing social,
transitional, and functional skills.
Outcome Variables
Social, transitional, and functional skills serve as the outcome variables of the current
study. All six studies evaluated one or more of these as their dependent variable(s) to determine
the efficacy of AR or VR as their intervention, or independent variable (Cihak, Moore, Wright,
McMahon, Gibbons, & Smith, 2016; Cheng, Huang, & Yang, 2015; Kang and Chang, 2019; Lee,
Chen, Wang, & Chung, 2018a; Lee, Lin, Chen, & Chung, 2018b; Lee, 2021). To that end, in
order to corroborate the reliability and validity of results from each individual study included in
this meta-analysis, the outcome variables of social, transitional, and functional skills is the
outcome variable of the current study.
Participant Characteristics
Number. The total number of participants included within the six studies was 18 (n =
18). In all six of the studies the number of participants was three (n = 3).
Sex/Gender, age and race/ethnicity. Fourteen of participants were male (n = 14) and

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
four of the participants were female (n = 4) in the corresponding studies. The ages of the
participants ranged from 6- to 15- years old, more specifically 6 (n = 2), 7 (n = 4), 8 (n = 5), 9 (n
= 1), 10 (n = 1), 11 ( n = 1), 12 (n = 1), 14 (n = 1), and 15 (n = 2). The race and ethnicity of the
participants was not included in any of the six studies; therefore, it is undetermined for all 18
participants.
Special education eligibility and disability labels. All the participants qualified under
one of the thirteen special education disability categories. Fifteen of the eighteen participants
had a special education eligibility diagnosis of Autism (n = 15), with the remaining participants
qualifying for special education under ID (n = 3).
Settings. All the studies included had varying information included for the setting.
Studies were conducted within a regular education classroom with the addition of a teacher’s
aide and occupational therapist substitute (n = 2), within a special education classroom (n = 3),
and within a special education class with an Occupational Therapist (n = 1). None of the studies
identified the region.
Data Analysis
Meta-analysis was created as a tool to extract pertinent information within the plethora of
available research in journals and other sources (Glass, 2000, as cited in Cooper & Patall, 2009).
Hauser (2007) claims meta-analysis as a valuable research tool that has impacted the field of
scientific research. According to Cooper and Patall (2009) meta-analysis takes two forms as a
technique to combine quantitative data from multiple different studies. Meta-analysis can be
conducted in two forms, aggregated data (AD) or individual participant-level data (IPD). AD
relies on summary results of studies creating a statistical synthesis of the data by collecting
published and unpublished works on a specific topic, extracting effect size estimates within the

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
reports, and combing effects to reveal an average effect size estimates (Cooper, 2009, as cited in
Cooper & Patall, 2009).
IPD relies on central collection, checking, and re-analysis of each studies raw data to
combine results. Similarly to AD, IPD collects data from both published and unpublished works.
When outcomes across the various selected studies are measured exactly, the raw data can be reanalyzed using traditional inferential statistics (Cooper & Patall, 2009).
Kavale (1984) highlights the benefits of using meta-analysis specifically for research in
special education. Due to the inconsistent and often contradictory nature of special education
research, meta-analysis is warranted to find valuable information across studies. Specifically,
when the literature is smaller it becomes more manageable, allowing for accumulating data that
is direct. Special education research findings are highly variable, creating gaps in past and future
research. However, synthesizing results creates comprehensive statistical summaries. Other
advantages include (a) using quantitative methods for organization and information extraction
from large databases, (b) eliminating selection bias, (c) transforming study information into
equal experimental effects, (d) detecting statistical interactions, and (e) generating practical
conclusions. In summary, a meta-analysis statistically accumulates data and findings from
multiple separate studies into one comprehensive review summary (Kavale, 1984). A popular
approach to analyze the data used in a meta-analysis is hierarchical linear modeling.
Hierarchical linear modeling (HLM) is used to analyze clustered data using regression
equations to describe variations of scores within the groups being analyzed. A summary of
findings of several cases are examined in a systematic and quantitative way. By aggregating the
results of several cases, the power for assessing effect size estimates is increased and the results
are not restricted to the specific studies cases, but instead allow for broader population inferences

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to be drawn. A major advantage to HLM is it can be easily adapted and is beneficial for
behavioral research and particularly single-case study designs (Van den Noortgate & Onghena,
2007). There are various tools to extract data in order to apply HLM. WebPlotDigitizer is a free
tool used to extract data points on an XY chart. Drevon, Fursa, and Malcolm (2017) found that
WebPlotDigitizer is a reliable and valid tool for extracting data with intercoder reliability of 90%
proportional agreement and over half in exact agreement.

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
CHAPTER 4: RESULTS
The purpose of the current investigation is to analyze existing research examining the
impact of AR and VR technology on the skills of children with disabilities. This study utilizes
meta-analytic techniques on a group of publicly available research studies that individually
examined the effectiveness of AR or VR to support the development of functional, social, and
transitional skills. The present hierarchical meta-analysis was guided by two research questions:
1. How effective are augmented reality (AR) and virtual reality (VR) technologies in
supporting functional, social, and transitional skills of children with disabilities?
2. What moderators or variables are associated with effectiveness AR and VR
interventions for students with disabilities?
Descriptive Analysis
A total of six studies with twenty-one effect size measures were analyzed. Outcome measures
for each study was centered around functional, social, and transitional skills. Based on the
individual participant data collected, the present study yielded twenty-one cases for a total
sample size of n = 391 data points. The number of data points is based on the multiple outcome
measures related to functional, social, and transitional skills development collected and analyzed
for the investigation. Tables 3-5 provide demographic data of the study’s participants, beginning
with participants by gender. As indicated in Table 3, there were three times more male children
diagnosed with a disability included as a part of the hierarchical meta-analysis compared to
females. In Table 4, data are organized by age of participants, showing a large majority of
participants’ ages fell between six and 12 years. Finally, Table 5 includes demographic data
organized by disability category. Autism is the identified disability for 71% of the participant
data collected.

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
Table 3
Descriptive Data – Participants by Gender
Gender

n

%

Male

16

76.2

Female

5

23.8

Table 4
Descriptive Data – Participants by Age
Age (years)

n

%

6-12

15

71.4

14-15

6

28.6

Table 5
Descriptive Data – Participants by Disability
Disability

n

%

Autism

15

71.4

ID

6

28.6

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
In order to determine the effectiveness of AR or VR to support the development of
functional, social, and transitional skills, including identified potential moderators or variables
related to the intervention’s efficacy, further examination of participant demographic data was
warranted. A total of three models using Hierarchical Linear Modeling (HLM) were conducted.
HLM was used to synthesize the available cases as a group in order to understand the degree of
impacts found across different student characteristics on the skills being measured. HLM is
considered to be the gold-standard approach in computing a synthesis of small sample studies
because it takes into consideration the number of measures at and after baseline. Therefore,
HLM accounts for any auto-correlations that may bias the data across the data collection
(Boedeker, 2017).
The first model analyzed the effect of all identified moderator variables (i.e., gender, age,
school level, study, disability, AR or VR, and skill) being measured against the outcomes across
the baselines and subsequent phases. The HLM analysis used a restricted maximum likelihood
(REML) estimation to reduce bias in comparison to a full maximum likelihood estimation. The
decision to conduct a REML was based on the small number of groups in the present
investigation (Boedeker, 2017). REML was used for each of the three models/runs. The results
generated after one hundred iterations and the following levels were evaluated:
Model 1
Level-1 Model
OUTCOMEij = β0j + β1j*(PHASEij) + rij
Level-2 Model
β0j = γ00 + γ01*(STUDYj) + γ02*(SCHOOLEVELj) + γ03*(AGEj) + γ04*(SEXj)
+ γ05*(DISABILIj) + γ06*(AR OR VRj) + γ07*(SKILL) + u0j
β1j = γ10

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
Mixed Model
OUTCOMEij = γ00 + γ01*STUDYj + γ02*SCHOOLEVELj + γ03*AGEj
+ γ04*SEXj + γ05*DISABILIj + γ06*AR or VRj + γ07*SKILLj
+ γ10*PHASEij + u0j+ rij
The OUTCOMEij noted for the Level-1 Model refers to the functional, social, or transitional
skills measure for participant “i” on level “j”. The intercept for the Level-1 Model is β0j, the
slope for PHASE, β1j, and rij accounts for the Level-1 error. In reference to Level-2, β0j, refers to
the results for the intercept. The intercept for the Level-2 Model is γ00, the slope for STUDY, γ01,
the slope for SCHOOL LEVEL, γ02, the slope for AGE, γ03, the slope for SEX, γ04, the slope for
DISABILITY, γ05, the slope for AR or VR, γ06, the slope for SKILL, γ07, and u0j accounts for Level2 error.
The results of this model did not converge as singularity exists between one moderator
variable and the outcomes (disability by outcomes) and between two moderators (school level
and age group). The model was reanalyzed after removing disability and school level, and the
model was determined not to have the power to support analysis with all remaining moderator
variables in a single model. Therefore, two additional models were conducted:
•

Model 2 including AR vs. VR, Skill Type, and Study

•

Model 3 including AR vs. VR, Age, and Gender

Model 2
Model 2 converged after 31 iterations, and is summarized:
Level-1 Model
OUTCOMEij = β0j + β1j*(PHASEij) + rij
Level-2 Model

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
β0j = γ00 + γ01*(STUDYj) + γ02*(AR OR VRj) + γ03*(SKILLj) + u0j
β1j = γ10
Mixed Model
OUTCOMEij = γ00 + γ01*STUDYj + γ02*AR or VRj + γ03*SKILLj
+ γ10*PHASEij + u0j+ rij
The results from Model 2 are presented in Table 6.

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
Table 6
HLM Results for a Two-Level Model – Study, AR vs VR, and Skill
Fixed Effect

Coefficient

SE

t-ratio

d.f.

p-value

INTRCPT2, γ00

66.716014

6.390030

10.441

17

<0.001

STUDY, γ01

-5.718786

0.795974

-7.185

17

<0.001

AR OR VR, γ02

-42.319585

3.888308

-10.884

17

<0.001

SKILL, γ03

22.384980

1.803440

12.412

17

<0.001

2.393329

0.137499

17.406

368

<0.001

For INTRCPT1, β0

For PHASE slope, β1
INTRCPT2, γ10

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
As shown in Table 6, all three potential moderators were revealed to be significant, with p-values
of < 0.001. Specifically, these results indicate that there were significant differences found
across the six investigations, the outcomes for AR relative to VR, and the outcomes based on the
type of skill measured. Table 7 presents the average Tau-U for each study and shows the largest
effect size estimates were reported in Lee (2021) and the smallest effect size estimates were
found in Lee (2018). Table 8 presents the average Tau-U by AR or VR and revealed VR
interventions resulted in the largest effect size estimates. Table 9 provides the average Tau-U by
skill measured and the results indicate that the greatest effect for AR or VR is found in
developing functional skills followed by transitional skills. Closer examination of the data
reveals that the VR intervention was used with studies measuring social skills.

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
Table 7
Average Tau-U by Study
Study

N

Tau-U Mean

SD

1

3

0.984

0.014

2

3

0.838

0.140

3

6

0.957

0.057

4

3

-0.333

1.154

5

3

-0.999

0.000

6

3

0.999

0.000

N

Mean

SD

AR

18

0.427

0.911

VR

3

0.838

0.140

N

Mean

SD

Functional

3

0.984

0.014

Social

12

0.126

0.997

Transitional

6

0.957

0.057

Table 8
Average Tau-U by AR or VR

Table 9
Average Tau-U by Skill
Skill

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
Model 3
Model 3 examined age, gender, AR, or VR, against the estimated effect size estimates.
The model is summarized:
Level-1 Model
OUTCOMEij = β0j + β1j*(PHASEij) + rij
Level-2 Model
β0j = γ00 + γ01*(AGEj) + γ02*(SEXj) + γ03*(AR or VRj) + u0j
β1j = γ10
Mixed Model
OUTCOMEij = γ00 + γ01*AGEj + γ02*SEXj + γ03*AR or VRj
+ γ10*PHASEij + u0j+ rij
The results of Model 3, after seven iterations, are presented in Table 10.

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
Table 10
HLM Results for a Two-Level Model – Age, SEX, and AR vs VR
Fixed Effect

Coefficient

SE

t-ratio

d.f.

p-value

For INTRCPT1, β0
INTRCPT2, γ00

30.064445

6.553158

4.588

17

<0.001

AGE, γ01

34.688616

2.408926

14.400

17

<0.001

SEX, γ02

0.535899

2.612815

0.205

17

0.840

AR or VR, γ03

-24.937530

3.540750

-7.043

17

<0.001

2.389349

0.135209

17.672

368

<0.001

For PHASE slope, β1
INTRCPT2, γ10

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As indicated in Table 10, the outcomes did not significantly differ based on the gender of the
student (p = 0.840), but significantly differed by AGE of the student and VR or AR, as indicated
in the previous model. Closer examination of the data indicates that the greatest effect size
estimates were found with 14–15-year-old students (Tau-U Mean = 0.957) relative to the 6–12year-old students (Tau-U Mean = 0.298). The available data indicates that only 6-12-year-old
students participated in the VR research (Tau-U Mean = 0.838), and that 14-15-year-old students
had greater outcomes for the AR research (Tau-U Mean = 0.957).
Finally, the data were manually analyzed in order to assess the overall estimate of the use
of AR and VR on students’ development of functional, social, and transitional skills. The details
of this analyses are presented in Appendix E. Overall, the use of AR and VR reveal a
significantly large effect size estimate of Tau-U = 0.6364, p < 0.001 when examining all twentyone students’ data from baseline to subsequent phases of data collection.
Test of Bias Estimates: Egger's Test of the Intercept
Egger’s Test of the Intercept suggests that bias is assessed by using precision (the inverse
of the standard error) to predict the standardized effect (effect size divided by the standard error).
In this equation, the size of the treatment effect is the slope of the regression line (B1) while bias
is captured by the intercept (B0). This approach is advantageous in that it is a more powerful
test, indicating that if an effect exists, it will more likely reveal that effect (Paige, Stern, Higgins,
& Egger, 2020). For the current investigation, Egger’s Test was computed in CMA®, a
dedicated meta-analysis software. Results indicate that for the current investigation, the intercept
(B0) is 0.04523, 95% confidence interval (-0.03749, 0.12795), with t = 1.14435, df = 19. The 1tailed p-value is 0.13335, indicating no significant bias exists is the twenty-one effect size
measures analyzed.

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
Summary
The current investigation utilized meta-analysis within an HLM platform to examine the
impact AR or VR to support the development of functional, social, and transitional skills. The
resulting analysis included three models:
1. A full model of all available moderators against the outcomes.
2. A second model examining for differences across the six studies, the skills being
measured, and whether AR or VR was utilized.
3. A third model examining for differences across the age of the student, the gender of
the student, and whether AR or VR was utilized.
Two moderators created singularity in the full model and were eliminated from the calculations.
These variables were disability and school level. The second model revealed that there were
differences in the reported effects for the six studies, as well as across the skills being measured,
and whether AR or VR was being utilized in the intervention. The third model revealed that
there were differences for age of the student, but no differences for sex. Further analysis
revealed that 14-15-year-old students revealed the greatest effect estimates, however they were
only included in the AR research studies. Overall, the use of AR and VR reveal a significantly
large effect size estimate when examining all twenty-one students’ data from baseline to
subsequent phases of data collection.
While there is a lack of research available on AR and/or VR, the result of this
investigation provides evidence that this technology can be effective in developing the
functional, social, and transitional skills of students with disabilities. Chapter five will discuss
these results in light of the available research and potential future directions in supporting
students with disabilities through the use of these technologies.

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
CHAPTER 5: DISCUSSION
Inferences
The purpose of this meta-analysis was to investigate the effectiveness of AR and VR for
developing functional, transitional, and social skills for students with low-incidence disabilities.
The research questions guiding this study:
1. How effective are augmented reality (AR) and virtual reality (VR) technologies in
supporting functional, social, and transitional skills of children with disabilities?
2. What moderators or variables are associated with effectiveness AR and VR
interventions for students with disabilities?
The results of the current study suggest that AR and VR are effective to develop transitional,
functional, and social skills for students with low-incidence disabilities (i.e., Autism and
Intellectual Disability), supporting the prior research (Baragash et al., 2000; Cobb, 2007; Gybas
et al., 2019; Jeffs, 2009; Ke & Im, 2013; Kirsher et al., 2011; Lan et al., 2018; Standen, 2001;
Standen et al., 2001; Wang, 2020). When examining what moderators or variables are associated
with effectiveness, AR and VR was shown effective across both age and gender. There was no
significant difference across gender which is surprising due to the majority of participants being
male (e.g., 76%). AR was shown specifically effective for participants ages 14-15-years-old
across all three skills (i.e., transitional, functional, and social). VR was shown specifically
effective for participants ages 6-12-years-old and particularly in teaching social skills. This is
due to the only skill examined using VR was social skills, however, it is still statistically
significant in effectiveness.
The population that had the largest effect size estimates was participants ages 6-12 and
diagnosed with Autism. This may be due to the majority of participants included in the meta-

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
analysis being between the ages of 6-12 years (e.g., 71%) old and with an Autism diagnosis (e.g.,
71%). VR had the largest effect size estimates in comparison with AR, determining VR
programs are more efficacious. This is noteworthy due to only one VR study was included in the
meta-analysis.
Overall, the use of AR and VR was affective across phases (e.g., baseline to subsequent
phases of data collection). AR or VR was found to be most effective in developing functional
skills followed by transitional skills. Considering the majority of the meta-analysis examined
social skills, the data suggests AR and VR are more suited to develop functional and transitional
skills as compared to social skills. This somewhat contradicts the research literature that shows
virtual environments are particularly suited for students to develop social skills due to their
propensity for technology in relation to their disability (Cobb, 2007; Dieker et al., 2008; Jeffs,
2009; Mitchell et al., 2007).
Lee (2021) showed the largest effect size estimates compared to all six studies included
in the meta-analysis. When considering the data collection method, participants were evaluated
based on a 5-point Likert scale (i.e., 1- absolutely inappropriate, 2- slightly inappropriate, 3neutral, 4- slightly appropriately, and 5- absolutely appropriate) after being asked to display the
appropriate social greeting behavior for specific scenarios, leaving a margin for rater bias.
Compared to the other studies which had a more methodical method for evaluation. Possible
rater bias could result in over-estimation of effect size estimates.
Lee (2018a) and Lee (2018b) showed the smallest effect size estimates compared to all
the studies. In both studies the data collection method was based on correct rate and error rate
respectively. Participants chose a social behavior to respond to a specific scenario and it was
either correct or incorrect, leaving no margin for interpretation. Therefore, the results can be

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
considered more accurate, and illustrate a truer depiction of the participants skill development
whether positive or negative in supporting the research hypothesis.
The existing research literature provided evidence that AR and/or VR was effective for
developing functional (Jeffs, 2009; Kirsher et al., 2011), transitional (Jeffs, 2009; Standen et al.,
2001), and social skills (Baragash et al., 2020; Sahin et al., 2018) for individuals with disabilities
(Baragash et al., 2000; Cobb, 2007; Gybas et al., 2019; Jeffs, 2009; Lan et al., 2018; Wang,
2020), specifically, Autism (Ke & Im, 2013) and ID (Standen, 2001). Although, the existing
research supports the results from this current meta-analysis, the current study adds further
evidence for the specific population of students with disabilities receiving intervention within an
educational context.
The current study included only six available studies on the topic of AR or VR as it is
implemented for the development of functional, transitional, and social skills with students with
low-incidence disabilities (e.g., Autism and ID) within an educational context resulting in 21
cases providing 391 extracted data points to run a HLM for examination. The majority of the
population was male, ages 6-12-years-old, and diagnosed with Autism. Although significant
effect size estimates resulted, the study is not without limitations which will be discussed in
further detail.
Limitations
The following limitations must be taken into consideration when examining the results
and conclusions. First, there is limited research literature on using AR and VR within an
educational setting to instruct students with low incidence disabilities functional, transitional,
and social skills, therefore yielding a small sample of studies to select to include within the metaanalysis. Specifically for VR, only one study was included as the rest were studies using AR.

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
All but one study was found using EBSCOhost excluding studies published in languages other
than English and any unpublished and/or peer reviewed articles which contributes to possible
sampling bias which leads to possible under- or over- estimation of the effect size estimates.
Due to the limited number of studies included, this resulted in convergence issues. More
specifically for Model 1, in HLM, it was deemed not to have enough statistical power to evaluate
the effectiveness across all moderators. Calculations were unable to determine efficacy across
school level because of the singularity between school level and age. That is, all 14-15-year-olds
were in the same school level (e.g., junior high) and 15 of 21 cases were 6-12 years old who
were also coded as in elementary school. Therefore, school level and age moderators were too
similar to distinguish and analyze through HLM. Likewise, 71% of participants had Autism.
Singularity existed between disability and some other moderators. Increased studies would
provide more accurate evidence of the effectiveness of AR and VR by alleviating the
convergence issue mentioned.
Due to the nature of the topic being examined, data collection of the studies was variable.
The variable nature of the collection methods used in each individual study can produce an
under- or over-estimation of effect size estimates. The current study relies on the accuracy and
reliability of the reporting of results for each individual study that was included in the metaanalysis. In response to these limitations, future recommendations will be discussed to further
the investigation of this worthy topic.
Recommendations
In future research, the aforementioned limitations should be accounted for to produce further
evidence of the effectiveness of AR and VR. During the study selection process only one other
study was found examining VR but was not included due to the lack of data and data analysis.

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AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
This deemed it unusable for the current meta-analysis. The results indicate AR and VR are
effective intervention tools to teach required skills to students with disabilities within educational
contexts, providing educators more evidence-based strategies that are useful across various
moderators (e.g., age and gender). Providing intervention directly in educational contexts
provides students affordable access to effective tools. However, the small sample of the current
study limited the generalizability of the results. Replication of results will increase the
generalizability of findings.
As continued research develops, technology advances, and more affordable AR and VR
options become available allowing for more schools to implement AR and VR within both
regular and special education contexts, an updated meta-analysis can be conducted to further the
research and provide more evidence of AR and VR’s efficacy. In addition, with more studies,
separating and examining more moderators and variables will account for singularity issues and
results in further evidence of which target populations can benefit the most from AR and VR
programs.
Conclusion
In conclusion, as COVID-19 continues to impact school districts and the education of
students, specifically students with disabilities, options to provide FAPE, CBI, and evidencebased interventions to address IEP goals, transition goals, and necessary life skills, AR and VR
programs were found effective across various moderators for the development of all three
functional, transitional, and social skills. Although the current research is limited, future
research can address the limitations of the current study to increase generalizability of results. In
the meantime, there are affordable and accessible AR and VR options for educators to use in
their classrooms to adhere to FAPE and LRE for students with disabilities requiring CBI per

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their IEPs. AR and VR provide a safe, controlled, naturalistic setting for students to learn and,
with the evidence the current meta-analysis discovered, AR and VR are shown to be effective
options.

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64

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
APPENDIX A
Data
Study
Chiak (2016)
Chiak (2016)
Chiak (2016)
Cheng (2015)
Cheng (2015)
Cheng (2015)
Kang (2019)
Kang (2019)
Kang (2019)
Kang (2019)
Kang (2019)
Kang (2019)
Lee (2018a)
Lee (2018a)
Lee (2018a)
Lee (2018b)
Lee (2018b)
Lee (2018b)
Lee (2021)
Lee (2021)
Lee (2021)

Study
1
1
1
2
2
2
3
3
3
3
3
3
4
4
4
5
5
5
6
6
6

Participant ID
101
102
103
201
202
203
301
302
303
304
305
306
401
402
403
501
502
503
601
602
603

65

Author
5,12,15,11,6,13
5,12,15,11,6,13
5,12,15,11,6,13
3,7,16
3,7,16
3,7,16
8, 1
8, 1
8, 1
8, 1
8, 1
8, 1
9, 2, 14, 4
9, 2, 14, 4
9, 2, 14, 4
9, 10, 2, 4
9, 10, 2, 4
9, 10, 2, 4
9
9
9

Year
2
2
2
1
1
1
4
4
4
4
4
4
3
3
3
3
3
3
5
5
5

Source
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
School Level
1
1
1
3
3
3
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1

Age Range
1
1
1
1
1
1
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1

Sex/Gender
1
1
1
1
1
1
1
1
1
1
2
2
1
1
2
1
1
2
1
1
2

Disability/Category
1
1
1
1
1
1
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1

66

AR or VR
1
1
1
2
2
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

Type of Skill
1
1
1
2
2
2
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
APPENDIX B
Coding Key
Author(s)
Chang
Chen
Cheng
Chung
Cihak
Gibbons
Huang
Kang
Lee
Lin
McMahon
Moore
Smith
Wang
Wright
Yang

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16

Year
2015
2016
2018
2019
2021

1
2
3
4
5

Source
journal article

67

1

School Level
elementary
junior high
unknown

1
2
3

Age Range
6-12
14-15

1
2

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
Sex/Gender
male
female

1
2

Disability/Category
Autism
ID
MD

1
2
3

68

AR or VR
AR
VR

1
2

Type of Skill
Functional
Social
Transitional

1
2
3

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
APPENDIX C
Phases
Participant ID
101
101
101
101
101
101
101
101
101
101
101
101
101
101
101
101
101
101
101
101
101
101
101
102
102
102
102
102
102
102
102
102
102
102

Study
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

Phase
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
0
0
0
0
0
0
0
0
0
0
0

Session
0.929296161
1.970107862
3.016057135
4.008213005
5.005808657
6.008541881
6.995106862
7.981671844
9.033212005
9.99303139
10.97385438
11.9495398
12.90346608
13.96074824
14.92011431
15.96092601
16.96909901
17.99933336
18.94781986
19.93997573
20.98078744
21.93471372
67.95255301
1.0391198
2.03667482
2.95110024
3.99022005
4.94621027
7.9804401
11.0562347
13.9657702
16.9584352
19.9511002
22.9437653

69

Outcome
18.47215
18.47748312
12.55949762
18.6621424
18.49303806
12.40061509
24.94922425
37.49783342
25.13388353
18.51859259
37.68738139
62.77948882
62.95859277
93.97446324
87.88181806
87.88715118
75.52297908
87.72337995
94.17423303
100.2768778
100.2822109
100.4613149
94.59954935
37.7224199
31.6725979
37.9003559
31.4946619
25.2669039
25.2669039
37.7224199
43.772242
37.544484
37.544484
37.7224199

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
102
102
102
102
102
102
102
102
102
102
102
102
102
102
102
102
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103

1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1

24.0244499
25.0635697
25.9779951
26.9755501
28.0146699
29.0537897
30.00978
31.0904645
31.9633252
32.9608802
33.9584352
35.0391198
36.0366748
37.0342298
37.9486553
68.0831296
0.89688249
1.95683453
3.01678657
3.91366906
8.03117506
11.0071942
13.942446
16.9592326
19.9760192
22.9928058
26.0095923
28.9448441
31.9616307
34.9784173
37.9952038
38.9736211
39.911271
40.971223
41.9088729
42.9688249
43.9472422
44.8848921
45.9448441

70

50.1779359
43.772242
56.405694
50.1779359
62.633452
62.633452
50
56.227758
56.405694
68.683274
81.316726
93.9501779
100.355872
100.355872
100.355872
100.177936
24.8120301
24.8120301
25
24.8120301
24.6240602
18.7969925
24.8120301
6.01503759
18.4210526
24.8120301
24.8120301
24.8120301
24.8120301
18.4210526
18.4210526
31.2030075
37.2180451
43.6090226
56.0150376
56.0150376
50
50
62.406015

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
103
201
201
201
201
201
201
201
201
201
201
201
202
202
202
202
202
202

1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2

1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
0
0
0
1
1
1
1
1
2
2
2
0
0
0
0
1
1

46.9640288
47.942446
49.0023981
49.940048
50.9592326
51.9376499
52.9160671
53.9760192
54.9544365
55.9328537
56.9520384
57.971223
58.9904077
59.9280576
60.9064748
61.9664269
62.9448441
63.9232614
64.9832134
65.9616307
66.940048
67.9184652
0.45844504
1.50268097
2.49597855
3.48927614
4.48257373
5.47587131
6.4691689
7.48793566
9.47453083
13.4731903
16.4530831
0.49850075
3.50374813
4.50074963
5.49775112
6.46626687
7.49175412

71

43.6090226
56.0150376
68.4210526
62.593985
74.8120301
75.1879699
68.7969925
62.406015
68.4210526
62.406015
62.2180451
81.2030075
87.593985
93.2330827
87.593985
93.2330827
100
93.2330827
100
100
100
100
7.94646013
11.9891173
9.98669447
17.9398272
19.9670341
22.942389
24.9695959
24.0341575
25.9552378
28.138457
28.175633
11.0871369
12.0829876
10.0248963
14.0746888
22.1742739
24.1659751

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
202
202
202
202
202
202
202
203
203
203
203
203
203
203
203
203
203
203
203
203
203
301
301
301
301
301
301
301
301
301
301
301
301
301
301
301
301
301
301

2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3

1
1
1
1
2
2
2
0
0
0
0
0
0
1
1
1
1
1
2
2
2
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2

8.48875562
9.47151424
10.4827586
11.494003
13.4737631
15.4962519
17.476012
0.50390016
3.49765991
4.47581903
5.49843994
6.46177847
7.49921997
9.48517941
10.4929797
11.50078
12.4641186
13.4867395
14.4945398
15.4875195
17.4586583
0.86363636
1.72727273
2.59090909
4.31818182
5.13636364
6
6.86363636
7.72727273
8.59090909
9.45454545
11.1818182
12
12.8636364
14.5909091
15.4545455
16.3181818
18
18.8636364

72

20.1161826
24.1659751
26.1576763
25.0954357
25.0954357
26.0912863
27.0871369
11.9631375
2.99943709
8.03885681
10.0271161
10.1179536
8.97232095
18.2266755
14.9364556
20.2235553
22.2113
24.1995593
24.2083085
25.289094
26.213423
27.176781
27.176781
27.176781
100
100
99.8680739
100
100
100
100
99.7361478
100
99.7361478
99.7361478
99.7361478
99.7361478
100
100

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
302
302
302
302
302
302
302
302
302
302
302
302
302
302
302
302
302
302
303
303
303
303
303
303
303
303
303
303
303
303
303
303
303
303
303
303
304
304
304

3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3

0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
2
2
0
0
0

0.86363636
1.72727273
2.59090909
4.31818182
5.13636364
6
6.86363636
7.72727273
8.59090909
9.45454545
11.1818182
12
12.8636364
14.5909091
15.4545455
16.3181818
18
18.8636364
0.88888889
1.73333333
2.57777778
3.46666667
4.31111111
6.02222222
6.88888889
8.57777778
9.44444444
10.3111111
11.1555556
12.0444444
12.8888889
14.5777778
15.4666667
16.3111111
18.0444444
18.8888889
0.88888889
1.75555556
2.57777778

73

27.176781
27.176781
27.176781
100
100
99.8680739
100
100
100
100
99.7361478
100
99.7361478
99.7361478
99.7361478
99.7361478
100
100
22.997416
22.997416
50.129199
50.129199
50.129199
100.129199
100.258398
100.258398
100.129199
100
100.258398
100.258398
100
100.258398
100.258398
100
100
100
19.6382429
39.5348837
39.5348837

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
304
304
304
304
304
304
304
304
304
304
304
304
304
304
304
305
305
305
305
305
305
305
305
305
305
305
305
305
305
305
305
305
306
306
306
306
306
306
306

3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3

0
0
1
1
1
1
1
1
1
1
1
1
1
2
2
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
2
2
0
0
0
0
0
0
0

3.42222222
4.33333333
6.02222222
6.88888889
8.57777778
9.44444444
10.3111111
11.1555556
12.0444444
12.8888889
14.5777778
15.4666667
16.3111111
18.0444444
18.8888889
0.99547511
1.99095023
2.98642534
3.98190045
6.96832579
7.9638009
8.95927602
10.9954751
12.9864253
13.9819005
15
15.9728507
16.9909502
17.9638009
19.0045249
20.9954751
21.9909502
0.99547511
1.99095023
2.98642534
3.95927602
6.96832579
7.98642534
8.95927602

74

39.5348837
49.6124031
100.129199
100.258398
100.258398
100.129199
100
100.258398
100.258398
100
100.258398
100.258398
100
100
100
50.1312336
50.2624672
50.1312336
50.1312336
50.1312336
50.1312336
50.3937008
100
100
100
100.131234
100
100
100
100
100
100
29.9212598
39.6325459
39.6325459
39.7637795
39.6325459
99.7375328
39.6325459

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
306
306
306
306
306
306
306
306
306
306
401
401
401
401
401
401
401
401
401
401
401
401
401
401
401
401
401
401
401
401
401
401
402
402
402
402
402
402
402

3
3
3
3
3
3
3
3
3
3
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4

1
1
1
1
1
1
1
1
2
2
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
0
0
0
0
0
0
0

10.9954751
12.9864253
13.9819005
15
15.9728507
16.9909502
17.9638009
19.0045249
20.9954751
21.9909502
0.49797023
1.61840325
2.67658999
3.64140731
4.69959405
5.72665765
6.72259811
7.78078484
8.80784844
9.91271989
10.8930988
11.9512855
12.947226
13.9431664
15.0013532
15.9972936
17.0554804
18.0514208
19.1096076
20.1366712
21.2259811
22.1596752
0.49132176
1.59679573
2.64085447
3.623498
4.69826435
5.71161549
6.70961282

75

100
100
100
100.131234
100
100
100
100
100
100
29.3103448
16.091954
29.3103448
14.9425287
21.2643678
25.862069
45.9770115
54.5977011
59.1954023
45.4022989
59.7701149
55.1724138
65.5172414
49.7126437
60.3448276
68.9655172
45.4022989
60.3448276
54.5977011
65.5172414
59.7701149
55.1724138
19.8992596
20.4947506
15.975088
25.0902719
30.2304588
14.9145831
30.2801463

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
402
402
402
402
402
402
402
402
402
402
402
402
402
402
402
403
403
403
403
403
403
403
403
403
403
403
403
403
403
403
403
403
403
403
403
403
403
501
501

4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
5
5

0
1
1
1
1
1
1
1
1
1
1
2
2
2
2
0
0
0
0
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
0
0

7.76902537
8.81308411
9.88785047
10.9012016
11.9452603
12.9586115
13.941255
14.9853138
15.9986649
17.0427236
18.0560748
19.1308411
20.1134846
21.2496662
22.1708945
0.50291545
1.60932945
2.68221574
3.65451895
4.69387755
5.73323615
6.70553936
7.77842566
8.81778426
9.89067055
10.8965015
11.9693878
12.9752187
13.9475219
15.0204082
15.9927114
17.03207
18.0379009
19.1107872
20.1166181
21.2565598
22.1618076
0.49713056
1.62697274

76

25.1926812
40.5593822
53.6541146
75.554148
65.0685763
70.207246
75.3451572
81.6209491
75.9641643
65.1945018
76.0149897
45.3597221
55.6112696
51.0938828
55.0939131
24.8447205
14.2857143
24.8447205
19.8757764
35.4037267
39.7515528
44.7204969
60.2484472
54.6583851
59.0062112
64.5962733
69.5652174
65.2173913
59.6273292
54.6583851
60.2484472
45.3416149
55.2795031
54.6583851
59.6273292
64.5962733
45.3416149
75.3058856
69.7483597

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
501
501
501
501
501
501
501
501
501
501
501
501
501
501
501
501
501
501
502
502
502
502
502
502
502
502
502
502
502
502
502
502
502
502
502
502
502
502
503

5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5

0
0
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
0
0
0
0
0
0
1
1
1
1
1
1
1
1
2
2
2
2
2
2
0

2.65136298
3.61549498
4.67001435
5.69440459
6.70373027
7.74318508
8.76757532
9.82209469
10.8163558
11.8708752
12.8651363
13.8292683
14.8837877
15.8780488
16.9325681
17.9268293
18.9813486
19.9756098
0.51289009
1.62415197
2.64993216
3.61872456
4.67299864
5.69877883
6.69606513
7.75033921
8.74762551
9.83039349
10.8276798
11.85346
12.8507463
13.8480326
14.8738128
15.8710991
16.8968792
17.8941655
18.9769335
19.9742198
0.5193068

77

65.0278884
70.4165525
59.7988168
45.8086825
30.9750455
26.2553802
26.3101897
15.692454
20.2400335
15.8020731
36.0799897
31.0753954
24.9520417
25.0052391
20.005481
26.2384537
20.1151
25.786275
70.212766
64.893617
59.0425532
68.6170213
73.9361702
68.6170213
55.8510638
45.7446809
25.5319149
26.0638298
20.7446809
16.4893617
20.7446809
10.106383
25.2659574
21.2765957
21.2765957
25.5319149
17.0212766
16.4893617
69.2004238

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
503
503
503
503
503
503
503
503
503
503
503
503
503
503
503
503
503
503
503
601
601
601
601
601
601
601
601
601
601
601
601
601
601
601
601
601
601
601
601

5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6

0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
2
2
2
2
0
0
0
0
0
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2

1.60675803
2.66146995
3.62899767
4.6882316
5.71635415
6.70902419
7.768439
8.75622529
9.82649291
10.8361657
11.8614846
12.8596715
13.8505327
14.8759421
15.8715062
16.9320063
17.9263043
18.9826441
19.9780274
0.47644231
1.60977564
2.65649038
3.63301282
4.69455128
5.73108974
6.73525641
7.81434295
8.83285256
9.92820513
10.930609
11.9613782
12.9961538
13.9666667
15.0294872
16.0291667
17.0629808
18.0653846
19.1564103
20.1559295

78

64.5793676
54.7248469
64.6353543
69.3158425
73.9954694
64.7206264
69.9825149
45.0098623
35.1557722
30.5325627
26.2004841
34.6583519
19.5695053
15.5281269
15.5556895
24.3059802
20.2637404
15.6418229
15.0879853
15.2173913
8.69565217
8.42391304
20.1086957
20.1086957
35.326087
40.7608696
50.2717391
54.3478261
69.0217391
68.4782609
64.1304348
73.3695652
64.673913
69.0217391
59.2391304
65.2173913
64.673913
64.673913
54.3478261

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
602
602
602
602
602
602
602
602
602
602
602
602
602
602
602
602
602
602
602
602
603
603
603
603
603
603
603
603
603
603
603
603
603
603
603
603
603
603
603

6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6

0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
2
2
2
2
0
0
0
0
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2

0.5117801
1.62565445
2.67931937
3.64267016
4.69633508
5.75
6.7434555
7.79712042
8.82068063
9.90445026
10.9280105
11.9816754
12.9751309
13.9685864
15.0222513
16.0157068
17.0693717
18.0628272
19.1465969
20.1400524
0.49263722
1.60107095
2.64792503
3.63319946
4.71084337
5.72690763
6.71218206
7.78982597
8.83668005
9.91432396
10.8995984
11.9464525
12.9625167
13.9477912
14.9330656
16.0107095
17.0267738
18.0890228
19.0589023

79

24.6851367
20.7155323
14.8058464
19.7360384
19.6596859
14.5833333
18.9557882
24.9905468
29.9163758
43.7267307
54.2081152
58.8539849
68.5042176
73.9877836
68.6336533
48.8394415
68.763089
68.1355439
63.3347877
68.2627981
19.8985335
25.607734
19.9517768
25.6579348
25.4004655
35.3687477
39.938542
50.1924364
51.0705702
70.6994645
65.0419861
70.7496653
65.6611294
60.003651
70.2552635
70.2818851
60.9319855
60.6741359
60.6980954

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
603

6

2

20.1365462

80

56.1792625

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
APPENDIX D
Moderators
Participant
ID
101
102
103
201
202
203
301
302
303
304
305
306
401
402
403
501
502
503
601
602
603

School
Level
1
1
1
3
3
3
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1

Age
Range
1
1
1
1
1
1
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1

Sex/Gend
er
1
1
1
1
1
1
1
1
1
1
2
2
1
1
2
1
1
2
1
1
2

81

Disability/Categ
ory
1
1
1
1
1
1
2
2
2
2
2
2
1
1
1
1
1
1
1
1
1

AR or
VR
1
1
1
2
2
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

Type of
Skill
1
1
1
2
2
2
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
APPENDIX E
Tau Output
Identificati
on
S
10
101
0
17
102
4
36
103
0
201

68

202

68

203

36

301

65

302

61

303

70

304

64

305

73

306

99

401

55

402

50

403

63

501

50

502

63

PAIR TA
S
U
0.9
102
8
0.9
180
7
1.0
360
0
0.8
80
5
0.9
70
7
0.6
56
4
1.0
65
0
0.8
72
5
1.0
70
0
0.8
72
9
0.9
77
5
1.0
99
0
1.0
55
0
1.0
50
0
1.0
63
0
1.0
50
0
1.0
63
0

TAU
U

VARIAN
CE

0.98

816.00

0.97

1680.00

1.00

4800.00

0.85

666.67

0.97

420.00

0.69

354.67

1.00

411.67

0.85

456.00

1.00

420.00

0.94

432.00

0.95

487.67

1.00

693.00

1.00

311.67

SD
28.5
7
40.9
9
69.2
8
25.8
2
20.4
9
18.8
3
20.2
9
21.3
5
20.4
9
20.7
8
22.0
8
26.3
2
17.6
5

-1.00

266.67

16.3
3

0.33

-1.00

357.00

18.8
9

0.30

266.67

16.3
3

357.00

18.8
9

-1.00

-1.00

82

SD
Tau
0.28
0.23
0.19
0.32
0.29
0.34
0.31
0.30
0.29
0.29
0.29
0.27
0.32

0.33

0.30

Z
3.5
0
4.2
5
5.2
0
2.6
3
3.3
2
1.9
1
3.2
0
2.8
6
3.4
2
3.0
8
3.3
1
3.7
6
3.1
2
3.0
6
3.3
3
3.0
6
3.3
3

P
Value

0.00

CI 90%
0.520<>
1
0.592<>
1
0.683<>
1
0.319<>
1
0.490<>
1
0.090<>
1
0.487<>
1
0.359<>
1
0.518<>
1
0.414<>
1
0.476<>
1
0.563<>
1
0.472<>
1

0.00

-1<>0.463

0.00

-1<>0.507

0.00

-1<>0.463

0.00

-1<>0.507

0.00
0.00
0.00
0.01
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.00

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION

503

81

81

601

60

60

602

81

81

603

45

45

1.0
0
1.0
0
1.0
0
1.0
0

-1.00

513.00

1.00

340.00

1.00

513.00

1.00

225.00

83

22.6
5
18.4
4
22.6
5
15.0
0

0.28
0.31
0.28
0.33

3.5
8
3.2
5
3.5
8
3.0
0

0.00
0.00
0.00
0.00

-1<>0.540
0.494<>
1
0.540<>
1
0.452<>
1

AUGMENTED AND VIRTUAL REALITIES IN SPECIAL EDUCATION
APPENDIX F
IRB Approval

TO:

Dr. Matthew Erickson
Special Education

FROM:

________________________________
Michael Holmstrup, Ph.D., Chairperson
Institutional Review Board (IRB)

DATE:

September 17, 2021

RE:

Protocol Title: Augemented and Virtual Realities in Special Education
Contexts: A Meta-Analysis

Your protocol submission has been reviewed and determined to not be research as
defined by the Federal Regulations that govern human research (45 CFR part 46).
Therefore, it does not require the review/approval of the IRB.
We appreciate you submitting the protocol for clarification, and hope that you will
continue to consult with the IRB in the future.
If you have any questions, please contact the IRB Office by phone at (724)738-4846 or
via e-mail at irb@sru.edu.

84