Technology-Aided Interventions for Individuals With Autism: Implications for Policy and Practice

Abstract

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by pervasive difficulties in reciprocal social-communication skills and restricted, repetitive interests and behaviors. Advances in assistive technology can potentially improve the functional capabilities of individuals with ASD. This article reviews current legislation and professional standards related to educating students with ASD with an emphasis on technology and evidence-based practices. In particular, the article summarizes technology-aided interventions (e.g., speech-generating devices, computer-assisted instruction, video-based instruction, virtual reality, and robot-mediated interventions) that focused on social-communication skills among individuals with ASD. Implications and future directions of technology-aided interventions are discussed.

Keywords

autism spectrum disorder technology social-communication

Advances in assistive technology show promise and some effectiveness in improving social-communication skills among children with autism.

Key Points

Speech-generating devices and video-based instruction improve requesting skills of young children with autism, but there is limited research with other communicative skills and with older populations.

Newer technologies, including virtual reality and robot-mediated interventions, show emerging evidence, but require additional research.

Discrepancies divide legal requirements and professional standards on what is evidence-based.

Technology development outpaces educational law, policy, and research on technology use with students with disabilities.

Researchers must establish partnerships with policy makers and practitioners to define and implement evidence-based practices in natural settings and to bridge the research-practice–policy gap.

Introduction

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by pervasive difficulties in reciprocal social-communication skills and restricted, repetitive interests and behaviors (Diagnostic and Statistical Manual of Mental Disorders [5th ed.; DSM-5; American Psychiatric Association [APA], 2013]). These challenges impede academic, social, occupational, or daily functioning, where many of the affected individuals require lifelong intervention and support. Even though individuals with ASD are characterized by core deficits in social and language skills, symptoms manifest differently across individuals and in any degree of severity (APA, 2013), which can lead to withdrawal and isolation, making integration into school and society difficult.

Despite these social difficulties, individuals with ASD process visual information more easily than auditory information (Quill, 1997). They also demonstrate unusually strong systemizing, or analyzing and constructing rule-based systems (Baron-Cohen, Ashwin, Ashwin, Tavassoli, & Chakrabarti, 2009). Given these strengths, individuals within this population of learners are likely to gravitate toward, or benefit from, technology-aided interventions. During learning and instruction, computer monitors (whether on desktop, laptop, or tablet computers) provide ample use of visual cues, when presenting explicitly defined tasks, while also reducing extraneous sensory stimuli, all of which can benefit students with ASD (Grynszpan, Weiss, Perez-Diaz, & Gal, 2014).

Because technology has great promise to improve the lives of individuals with disabilities, this article presents current research on the use of technology-aided interventions to improve the social-communication skills of individuals with ASD. In particular, we will (a) describe the legislation and professional standards related to the use of assistive technology (AT), (b) delineate the requirements of the legal and professional standards for implementing evidence-based practices, (c) present the evidence base of high-tech AT aimed at improving the social-communication skills of individuals with ASD, and (d) provide an analysis of legislation and professional standards to guide educators and related service providers when selecting and implementing high-tech AT with students with ASD.

Legislation and Professional Standards

Federal legislation that addresses technology-related supports for individuals with disabilities are emphasized in both civil rights law (e.g., the Americans with Disabilities Act [ADA] of 1990) and education law (e.g., the Individuals with Disabilities Education Improvement Act [IDEIA] of 2004). Professional standards of education-related organizations (e.g., Council for Exceptional Children [CEC], 2009) also highlight the importance of technology-related supports for individuals with disabilities. Typically, when technology addresses the learning needs of children with disabilities, it is often described as AT. The Technology-Related Assistance for Individuals with Disabilities Act of 1988 was the first piece of federal legislation to secure funding for AT-related supports for individuals with disabilities, followed by the IDEIA of 2004; the ADA of 1990 and the amended Assistive Technology Act (AT Act) of 2004 provide a broad definition of AT as “any item, piece of equipment or product system, whether acquired commercially off the shelf, modified, or customized, that is used to increase, maintain, or improve the functional capabilities of children with disabilities.” Although IDEIA (2004) applies to school-age children with disabilities in educational settings, the AT Act (2004) supports provisions of AT to individuals with disabilities of all ages.

AT services—also part of the AT Act of 2004 and the IDEIA of 2004—directly aid educational teams with the “selection, acquisition, or use of an assistive technology device,” and thus are integral in the implementation and success of AT use. Examples of such services include assessing the needs of the person requiring AT devices, procuring the devices, customizing or adapting the devices to fit each person’s needs, maintaining the devices, training for the individual to use the devices, and training for professionals and caregivers to use the devices, to name a few (AT Act, 2004; IDEIA, 2004). Most recently, Title IV of the Every Student Succeeds Act (ESSA) of 2015 explicitly references the use of technology to personalize learning, which can support students with ASD who need AT to access the general education curriculum.

Federal legislation also requires that practitioners make curricular decisions and implement instructional strategies based on research. The IDEIA of 2004 stipulates that educators are to use practices that are based on peer-reviewed research to the extent that such practices are practical (Zirkel, 2013). Furthermore, the ESSA of 2015 requires educators to use evidence-based practices when instructing students. Under the ESSA, different levels of evidence are based on methodological rigor as well as the amount of available research on a given practice (Russo-Campisi, 2017). Professional organizations, such as the CEC, also highlight the importance of using evidence-based practices when educating students with disabilities (CEC, 2009). However, as will be discussed, the meaning and interpretation of research- or evidence-based practices are inconsistent among legal requirements, professional standards, and consumer expectations (Russo-Campisi, 2017; Zirkel, 2013).

High-Tech AT Use for Students With ASD

The heterogeneity of symptoms and severity among people with ASD prompt the need for AT to support some individuals to function as independently as possible. AT is broad in scope and includes low-tech devices (e.g., using picture cards to communicate) and high-tech devices (e.g., using a speech-generating device [SGD] to communicate). This article focuses on high-tech AT, given the proliferation of mobile computing devices, advances in technological hardware (e.g., head-mounted displays and social robots), and advances in software development (e.g., communication applications). Specifically, we analyzed the extant research on the use of SGDs, computer-assisted instruction (CAI), video-based instruction (VBI), virtual reality (VR), and robot-mediated interventions (RMI) to improve the social-communication skills of individuals with ASD.

SGDs

Children with ASD often struggle with developing communication skills (Muharib & Alzrayer, 2018). Consequently, professionals aim to create and optimize AT to improve such skills (Ganz et al., 2017). In particular, augmentative and alternative communication (AAC) encompasses various modalities that can support or replace a person’s speech and other communication skills (Sigafoos & Drasgow, 2001). These modalities are either unaided (e.g., the use of sign language) or aided (e.g., the use of devices that emit spoken language when activated; Ganz et al., 2012; Muharib & Alzrayer, 2018).

The use of high-tech AAC—and in particular, SGDs—to supplement or supplant the existing communication skills among people with ASD has gained popularity. SGDs are computerized devices that produce recorded or synthesized speech as a result of an individual interacting with the device (e.g., touching a symbol or gazing at a word displayed on the device; Muharib & Alzrayer, 2018). These devices can range from a simple one-button communication system that produces a message when activated to highly sophisticated systems that have displays featuring multiple communication messages with various submenus to refine a person’s communicative intent.

SGDs have several advantages that educators and professionals should consider. First, the displays on SGDs are visual, and individuals with ASD purportedly have strengths in visual learning (Quill, 1997). Second, SGDs require less complex fine motor demands, compared with other AAC methods, such as manual sign language and hand gestures (Muharib & Alzrayer, 2018). Third, peers and teachers can understand the child’s communicative intent when using an SGD because they do not have to interpret signs, gestures, or pictures (Lorah, Parnell, Whitby, & Hantula, 2015; Muharib & Alzrayer, 2018). Fourth, consumer, off-the-shelf devices (e.g., tablet computers and smartphones) can be adapted and optimized via software applications to function as SGDs. In particular, iPads are gaining popularity due to their increased accessibility and affordability compared with other forms of SGDs. Moreover, iPads are socially acceptable in academic and social settings, making users feel more comfortable about using such technology and less stigmatized by its presence (Kagohara et al., 2013).

Considering the positive attributes of SGDs, several studies have evaluated their efficacy for individuals with ASD. According to a meta-analysis on the effects of aided AAC interventions among 58 children and adults with ASD, 83% of the included studies focused on some type of communication skill (e.g., requests, number of communication acts per minute, pronoun use; Ganz et al., 2012). A majority of the studies were conducted in school environments, followed by families’ homes. Interventions using SGD were highly effective for individuals with ASD. Moreover, the 24 studies in the review met the majority of research design indicators set forth by Horner et al. (2005). Despite these positive findings, participants used SGDs to emit a limited number of communicative behaviors across the studies. Because the majority of the participants were preschool- or elementary-aged children, relatively few participants were at, or beyond, the secondary level of education.

The efficacy of tablet-based SGDs or portable multimedia devices on the communicative behaviors of individuals with ASD appears in other meta-analyses. In a review of 15 studies that used iPad or iPod Touch devices for 52 individuals with developmental disabilities and autism, participants’ ages ranged from 3 to 23 years, with most participants being preschool- and elementary-aged children (Alzrayer, Banda, & Koul, 2014). The studies reportedly used quality experimental procedures and were conducted across settings, including homes, schools, therapy centers, and universities. All the studies focused on communicative behaviors such as requesting, labeling, answering questions, and receptive identification, with the majority focusing on requesting skills. Findings suggested that SGDs were moderately to highly effective.

Similarly, a review of the effectiveness of tablet-based SGDs, including the iPad and iPod Touch, from 17 studies, found that the tablet-based SGDs were effective in helping children and adults with ASD acquire and develop communication skills (Lorah et al., 2015). However, in the majority of the studies, the specific communicative behavior targeted by researchers was requesting, which is similar to the aforementioned review studies on this topic.

A more recent meta-analysis (Muharib & Alzrayer, 2018) reviewed the effects of high-tech SGDs on developing communication skills among 54 children with ASD between the ages of 3 and 8 years. The majority of the 20 studies were conducted in schools and childcare centers, whereas others were carried out in participants’ homes or clinic-based environments. The intervention agents in most of the studies consisted of researchers rather than caregivers found in natural settings. The majority of the studies reportedly met an acceptable level of quality indicators for experimental research. The use of SGDs was effective when teaching communication skills to this population. Similar to the reviews by Ganz et al. (2012), Alzrayer et al. (2014), and Lorah et al. (2015), results of the meta-analysis by Muharib and Alzrayer (2018) revealed that most of the studies on high-tech SGDs focused on developing participants’ requesting skills, whereas limited studies focused on improving other communicative behaviors, such as labeling, commenting, and answering questions.

This body of work shows that technology-aided interventions, such as SGDs, have much potential. The extant research has demonstrated that the use of SGDs paired with systematic teaching procedures is effective in developing requesting skills among this population of students (e.g., Lorah et al., 2015; Muharib & Alzrayer, 2018). Requesting is a pivotal skill for individuals with ASD to acquire, as this repertoire allows individuals to communicate their wants or needs to others. Moreover, a requesting repertoire, in part, can prevent or ameliorate problem behaviors that serve communicative functions (Cooper, Heron, & Heward, 2007).

Notwithstanding this positive finding from the research, several substantial considerations require attention from researchers and practitioners when considering whether the use of SGDs constitutes an evidence-based practice in all, or the majority, of the situations. First, only limited research evaluates the effects of SGDs on acquiring other functions of communicative behaviors (e.g., labeling, answering questions, conversation). In addition, less research on the effects of SGDs examines older students and adults compared with younger students with ASD. As reported by Muharib and Alzrayer (2018), more studies are needed in natural settings using intervention agents typically found in those settings. Thus, while evidence supports the use of SGDs to develop the requesting skills of individuals with ASD, additional research is needed to understand the effects of these devices (a) on other communicative behaviors, (b) with older populations, and (c) when implemented in natural settings using natural intervention agents.

CAI

Another category of technology-aided interventions, CAI, has been used to teach academic, social, and behavioral skills to students with disabilities (Barton, Pustejovsky, Maggin, & Reichow, 2017; Grynszpan et al., 2014; Sansosti, Doolan, Remaklus, Krupko, & Sansosti, 2015). This type of instruction has the potential to be effective for individuals with ASD. However, as revealed in recent meta-analyses, there is limited research on this type of instruction when it comes to social skills development.

A meta-analysis on technology’s effects on a variety of behaviors among individuals with ASD (Grynszpan et al., 2014) included 10 studies centered on facial and emotional recognition and four studies focused on social problem solving. In 18 of the 21 included studies, researchers made use of desktop computers to, at least in part, facilitate instruction or intervention. Overall, the results of the meta-analysis showed meaningful improvements in participants’ skills; however, the authors noted that additional studies are needed, particularly replication studies.

Another meta-analytic review on CAI (Sansosti et al., 2015) reported that out of the 28 selected studies, only seven examined CAI on targeted social skills. Similar to the research on SGDs, participants were primarily preschool- or elementary-aged children with ASD; few adolescents and no adults participated in the studies targeting social skills. Moreover, the majority of the studies focusing on social skills development were conducted in school settings. The specific skills targeted by the researchers included resolving social problems, developing social competence, commenting spontaneously, greeting others, and sharing. In addition to there being too few studies on CAI addressing social skills development, the researchers of the included studies reported small effects.

Another meta-analysis (Barton et al., 2017) examined the effects of technology-aided interventions, inclusive of CAI, on a variety of skills among individuals with ASD. Included in their meta-analysis were studies on social skills development and emotional recognition. Although findings indicated that the overall data supported the use of CAI to improve the skills of individuals with ASD, few studies addressed social skills development, inclusive of those studies whereby researchers focused on emotional recognition. Given the limited number of studies directly on social skills interventions reported by each of the aforementioned research teams, as well as the marginal effects reported by Sansosti et al. (2015), additional research is needed on the effects of CAI on the social skills development among individuals with ASD.

VBI

A high-tech strategy to develop various skills among individuals with ASD is VBI, which consists, in part, of video modeling (VM) and video-self modeling (VSM). When using VM, a practitioner plays a recording of an actor engaged in behavior. Once the video ends, the practitioner asks the student to imitate what they observed on the video. Using VSM is nearly identical to VM except that the actor on the video is the actual student who will then be asked to imitate what was observed (Bellini & Akullian, 2007).

Among the first meta-analyses that explored the effects of VM and VSM on the skill development among individuals with ASD, Bellini and Akullian (2007) identified 23 studies meeting their inclusion criteria. The age of the participants ranged from 3 to 20 years; however, the majority of the 73 participants were younger children with very few adolescents and adult participants. The studies were conducted in various environments, with school settings being the most frequently cited. The researchers indicated that the body of work on VM and VSM met the criteria for an evidence-based practice as defined by Horner et al. (2005). Moreover, 17 of the included studies were conducted where social-communication skills were the targeted behaviors. Specific skills in this area included social interactions, giving compliments, conversation skills, greetings, play skills, social responses, social initiations, gaze, and sharing. VM and VSM were effective in developing social-communication skills among this population of learners.

A more recent meta-analysis (Qi, Barton, Collier, & Lin, 2018) examined the effects of VM on the development of social-communication skills among people with ASD; 18 studies met the inclusion criteria. Again, the majority of participants were preschool- and elementary-aged children. The most common research settings were in schools, with others being various clinical settings. Specific social-communication skills targeted for interventions included social skills, verbal and nonverbal communication skills, pragmatic skills, and play skills. The researchers found that VM was moderately effective to effective for improving social skills and concluded the intervention was an evidence-based practice.

In sum, the data on VM and VSM suggest that this technology has a solid evidence base. However, researchers and practitioners should approach these findings with some caution because adolescents and adults are underrepresented in this line of research related to development of social-communication skills. Additional research will help elucidate the effects of VM and VSM to improve such skills among older populations of individuals with ASD.

VR

Along with other high-tech devices and interventions, VR is emerging to improve the social-communication skills of individuals with ASD (Thai & Nathan-Roberts, 2018). VR technology incorporates the use of computer-generated simulations that have the potential to provide a safe environment for children to acquire social skills (Ip et al., 2018; Thai & Nathan-Roberts, 2018). VR environments can be two-dimensional (e.g., use of a computer screen) or three-dimensional (e.g., use of head-mounted displays or projection-based systems in a room), with the latter providing an immersive experience for the user (e.g., Didehbani, Allen, Kandalaft, Krawczyk, & Chapman, 2016; Ip et al., 2018).

According to one review (Thai & Nathan-Roberts, 2018), 12 VR studies targeted various social skills that included emotional recognition, responses to social situations, initiating social interactions, responding to a bullying situation, and joint attention, to name a few. Their findings indicated that the variety of skills targeted, often in isolation, suggests that VR systems focusing on social skills are in the initial phases of development. Others concur that insufficient evidence so far supports using VR systems to improve the skills of individuals with ASD (Barton et al., 2017; Grynszpan et al., 2014).

In addition to understanding the effectiveness of VR systems with this population, thorough investigation into pragmatic issues and side effects is warranted. VR systems are expensive and challenging from a technical point of view (Fitzgerald et al., 2018). Moreover, certain immersive VR systems (e.g., head-mounted displays) could cause side effects such as disorientation and safety concerns because the participant, while engaged in the virtual environment, is isolated from potential obstacles in the real environment (Ip et al., 2018). Thus, although the use of VR to improve the social-communication skills of individuals with ASD is promising, it requires considerable research to understand its potential in helping this population.

RMI and Social Robots

Among the newer technology-aided interventions to assist the learning of individuals with ASD are RMI. RMI can involve practitioners conducting therapeutic or instructional sessions with the aid of a social robot (e.g., Chung, 2018; Marino et al., 2019), which tend to have humanoid qualities (Kumazaki et al., 2019). Recently, researchers investigating the effects of RMI have reported promising results. For instance, the use of RMI improved social-emotional skills among children with ASD (Marino et al., 2019). Similarly, the inclusion of a social robot in an intervention protocol improved social-communication skills such as eye contact and verbal initiations (Chung, 2018). Notwithstanding these recent research findings, a meta-analysis found limited adequately controlled studies on the use of robots to improve the skills of people with ASD (Grynszpan et al., 2014). RMI are not yet an evidence-based practice, primarily because the literature base lacks enough well-designed studies with quality data analysis (Begum, Serna, & Yanco, 2016). Thus, while the inclusion of social robots in instructional or intervention sessions may benefit learners with ASD, additional research is needed to ascertain their effectiveness in skill development as well as understanding the parameters of their use in real-world educational and therapeutic environments.

Summary of High-Tech AT and Social-Communication Skills

Researchers have investigated multiple high-tech AT devices to improving social-communication skills among individuals with ASD. Much of this research is promising, and some of it could be classified as evidence-based. Notwithstanding these findings, additional research will be necessary to fully understand the effects of various high-tech AT devices on the skill development of this population, given the expense, technical demands, and fast-paced development of technology. Such work will also be helpful to educators and caregivers given the uncertainty, and seemingly disagreement, among legislation, professional standards, and consumer expectations related to intervention selection and implementation (Russo-Campisi, 2017).

Policy and Practice Implications

According to federal legislation such as the IDEIA of 2004 and the AT Act of 2004, students with disabilities have a right to access AT, including AT devices and services, as part of their educational program and based on need. Federal legislation also requires educators and related service providers to use practices based on research. However, among the federal laws mandating research- or evidence-based practices, there is equivocality as to the definitions of these, and related terms, on the use of research to guide instruction (Russo-Campisi, 2017).

The IDEIA of 2004 requires educators to use practices based on peer-reviewed research when practical (Zirkel, 2013). The ESSA of 2015 requires educators to use evidence-based practices, and this law includes broad guidelines as to what constitutes an evidence-based practice (Russo-Campisi, 2017). Both pieces of legislation have caveats when it comes to selecting and implementing practices based on research, and recent court decisions have tended to rule in favor of schools citing a more minimal interpretation of the meaning of research-based practices, particularly in relation to the IDEIA of 2004 (Russo-Campisi, 2017). Moreover, scientific guidelines as to the type and amount of research needed to claim a practice as evidence-based differ from the legal requirements stipulated in the aforementioned legislation, and such guidelines clearly favor more exhaustive research before professionals claim a practice is evidence-based (Russo-Campisi, 2017). Thus, discrepancies exist in the interpretation of terms suggestive of evidence-based practices from legislation, case law, and professional standards, and these discrepancies can lead to confusion among educators, related service providers, and consumers.

The issues of what constitutes an evidence-based practice and when to implement such a practice in special education classrooms are of concern, given the rapid pace of technology development and the proliferation of technology use in society. Social-communication skills are a key area of delay among this population (APA, 2013), and difficulty in this broad area of skills can lead to more substantive issues in life (e.g., struggling at school, difficulty forming relationships, and living independently). The use of AT can assist school-based professionals in facilitating skill development in this area of functioning.

However, given differences between legal and professional standards and the state of the evidence base on the use of high-tech AT to develop social-communication skills among this population, what are educators and related service providers to do? From which end of the research-based practices continuum (i.e., minimum standards by the law or stricter standards based on professional practices) should these professionals look for guidance on intervention selection and implementation? The answers to such questions can be complicated.

For instance, as presented on the use of SGDs to improve the communication skills of individuals with ASD, the evidence supports the use of these devices to increase the requesting repertoire of younger children with ASD. However, there is a lack of evidence on the use of SGDs to teach other communicative functions of behavior (e.g., labeling, answering questions, or engaging in conversation) and among older populations of individuals with ASD (Alzrayer et al., 2014; Ganz et al., 2012; Muharib & Alzrayer, 2018). According to the IDEIA of 2004 and recent case law (see Russo-Campisi, 2017), professionals could be justified in selecting SGDs to develop communicative behaviors with populations of learners who are not well studied. However, according to standards of evidence-based practices among researchers (e.g., Kratochwill et al., 2013) and professional organizations (e.g., CEC, 2014), such decisions could be premature.

A similar case can be made with the use of VM or VSM in improving social-communication skills of younger children with ASD; ample evidence supports the use of these strategies to improve this area of functioning among this subpopulation of learners with ASD. However, such claims cannot be made when considering the development of social-communication skills using VM or VSM with older students and adults (Bellini & Akullian, 2007; Qi et al., 2018).

When it comes to using CAI, VR, and RMI, some studies exist, and these demonstrated promising results. Nevertheless, much more research is needed to explicate the effectiveness, as well as limitations and side effects of using such technology (e.g., VR). In sum, the general framework of research-based practices in federal education law provides options for schools when developing and implementing educational programming for students with ASD and other disabilities. However, when contrasted with the research communities’ stricter guidelines of what constitutes an evidence-based practice, disagreement among professionals and families in school settings is possible (Russo-Campisi, 2017).

Conclusion

Legislative mandates, public policy, and professional standards related to technology in supporting individuals with ASD should continue to evolve as technological advances become more mainstream in education. Technology-aided interventions have shown great promise in improving the social lives of individuals with ASD; however, the literature still has known gaps. Differences remain between what is legally required, professionally recommended, and expected by consumers of education when it comes to what constitutes an evidence-based practice; such differences can leave members of educational teams (inclusive of family members) at odds with each other (Russo-Campisi, 2017; Zirkel, 2013). It is our hope that this article illustrates—through the analysis of one set of practices to develop a broad, albeit limited, group of skills among individuals with ASD—some of the challenges that educators, related service providers, and families experience as they develop educational programming for students in need. Moreover, it is our aim that such an analysis—when paired with others (Russo-Campisi, 2017; Zirkel, 2013)—will motivate legislators, policy developers, and researchers to define more clearly the breadth and quality of research needed for an intervention to be worthy of being implemented in school settings with students with ASD and other disabilities.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Alzrayer

Banda

D. R.

Koul

R. K.

(2014). Use of iPad/iPods with individuals with autism and other developmental disabilities: A meta-analysis of communication interventions. Review Journal of Autism and Developmental Disorders, 1, 179-191. doi:10.1007/s40489-014-0018-5

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.

Americans with Disabilities Act of 1990, Pub. L. No. 101-336, 104 Stat. 328 (1990).

Assistive Technology Act of 2004, Pub. L. No. 108-364, 118 Stat. 1707 (2004).

Baron-Cohen

Ashwin

Tavassoli

Chakrabarti

(2009). Talent in autism: Hyper-systemizing, hyper-attention to detail and sensory hypersensitivity. Philosophical Transactions of the Royal Society B: Biological Sciences, 364, 1377-1383.

Barton

E. E.

Pustejovsky

J. E.

Maggin

D. M.

Reichow

(2017). Technology-aided instruction and intervention for students with ASD: A meta-analysis using novel methods of estimating effect sizes for single-case research. Remedial and Special Education, 38, 371-386. doi:10.1177/0741932517729508

Begum

Serna

R. W.

Yanco

H. A.

(2016). Are robots ready to deliver autism interventions? A comprehensive review. International Journal of Social Robotics, 8, 157-181. doi:10.1007/s12369-016-0346-y

Bellini

Akullian

(2007). A meta-analysis of video modeling and video self-modeling interventions for children and adolescents with autism spectrum disorders. Exceptional Children, 73, 264-287. doi:10.1177/001440290707300301

Chung

E. Y. H.

(2018). Robotic intervention program for enhancement of social engagement among children with autism spectrum disorder. Journal of Developmental and Physical Disabilities. Advance online publication. doi:10.1007/s10882-018-9651-8

10.

Cooper

J. O.

Heron

T. E.

Heward

W. L.

(2007). Applied behavior analysis (2nd ed.). Upper Saddle River, NJ: Pearson.

11.

Council for Exceptional Children. (2009). What every special educator should know: Ethics, standards, and guidelines (6th ed.). Arlington, VA: Author. Retrieved from https://www.cec.sped.org/~/media/Files/Standards/News%20and%20Reports/Redbook%202009.pdf

12.

Council for Exceptional Children. (2014). Standards for evidence-based practices in special education Arlington, VA: Author. Retrieved from https://www.cec.sped.org/~/media/Files/Standards/Evidence%20based%20Practices%20and%20Practice/EBP%20FINAL.pdf

13.

Didehbani

Allen

Kandalaft

Krawczyk

Chapman

(2016). Virtual reality social cognition training for children with high functioning autism. Computers in Human Behavior, 62, 703-711. doi:10.1016/j.chb.2016.04.033

14.

Every Student Succeeds Act of 2015, Pub. L. No. 114-95, 129 Stat. 1802 (2015).

15.

Fitzgerald

Yap

H. K.

Ashton

Moore

D. W.

Furlonger

Anderson

…English

D. L.

(2018). Comparing the effectiveness of virtual reality and video modelling as an intervention strategy for individuals with autism spectrum disorder: Brief report. Developmental Neurorehabilitation, 21, 197-201. doi:10.1080/17518423.2018.1432713

16.

Ganz

J. B.

Earles-Vollrath

T. L.

Heath

A. K.

Parker

R. I.

Rispoli

M. J.

Duran

J. B.

(2012). A meta-analysis of single case research studies on aided augmentative and alternative communication systems with individuals with autism spectrum disorders. Journal of Autism and Developmental Disorders, 42, 60-74. doi:10.1007/s10803-011-1212-2

17.

Ganz

J. B.

Morin

K. L.

Foster

M. J.

Vannest

K. J.

Genç Tosun

Gregori

E. V.

Gerow

S. L.

(2017). High-technology augmentative and alternative communication for individuals with intellectual and developmental disabilities and complex communication needs: A meta-analysis. Augmentative and Alternative Communication, 33, 224-238. doi:10.1080/07434618.2017.1373855

18.

Grynszpan

Weiss

P. L. T.

Perez-Diaz

Gal

(2014). Innovative technology-based interventions for autism spectrum disorders: A meta-analysis. Autism, 18, 346-361. doi:10.1177/1362361313476767

19.

Horner

R. H.

Carr

E. G.

Halle

McGee

Odom

Wolery

(2005). The use of single-subject research to identify evidence-based practice in special education. Exceptional Children, 71, 165-179. doi:10.1177/001440290507100203

20.

Individuals with Disabilities Education Improvement Act of 2004, Pub. L. No. 108-446, 118 Stat. 2647 (2004).

21.

H. H.

Wong

S. W.

Chan

D. F.

Byrne

Yuan

V. S.

…Wong

J. Y.

(2018). Enhance emotional and social adaptation skills for children with autism spectrum disorder: A virtual reality enabled approach. Computers & Education, 117, 1-15. doi:10.1016/j.compedu.2017.09.010

22.

Kagohara

D. M.

van der Meer

Ramdoss

O’Reilly

M. F.

Lancioni

G. E.

Davis

T. N.

…Sigafoos

(2013). Using iPods and iPads in teaching programs for individuals with developmental disabilities: A systematic review. Research in Developmental Disabilities, 34, 147-156. doi:10.1016/j.ridd.2012.07.027

23.

Kratochwill

T. R.

Hitchcock

Horner

R. H.

Levin

J. R.

Odom

S. L.

Rindskopf

D. M.

Shadish

W. R.

(2013). Single-case intervention research design standards. Remedial and Special Education, 34, 26-38. doi:10.1177/0741932512452794

24.

Kumazaki

Warren

Swanson

Yoshikawa

Matsumoto

Yoshimura

…Kikuchi

(2019). Brief report: Evaluating the utility of varied technological agents to elicit social attention from children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 49, 1700-1708. doi:10.1007/s10803-018-3841-1

25.

Lorah

E. R.

Parnell

Whitby

P. S.

Hantula

(2015). A systematic review of tablet computers and portable media players as speech generating devices for individuals with autism spectrum disorder. Journal of Autism and Developmental Disorders, 45, 3792-3804. doi:10.1007/s10803-014-2314-4

26.

Marino

Chilà

Sfrazzetto

S. T.

Carrozza

Crimi

Failla

…Pioggia

(2019). Outcomes of a robot-assisted social-emotional understanding intervention for young children with autism spectrum disorders. Journal of Autism and Developmental Disorders. Advance online publication. doi:10.1007/s10803-019-03953-x

27.

Muharib

Alzrayer

N. M.

(2018). The use of high-tech speech-generating devices as an evidence-based practice for children with autism spectrum disorders: A meta-analysis. Review Journal of Autism and Developmental Disorders, 5, 43-57. doi:10.1007/s40489-017-0122-4

28.

C. H.

Barton

E. E.

Collier

Lin

Y. L.

(2018). A systematic review of single-case research studies on using video modeling interventions to improve social communication skills for individuals with autism spectrum disorder. Focus on Autism and Other Developmental Disabilities, 33, 249-257. doi:10.1177/1088357617741282

29.

Quill

K. A.

(1997). Instructional considerations for young children with autism: The rationale for visually cued instruction. Journal of Autism and Developmental Disorders, 27, 697-714. doi:10.1023/A:1025806900162

30.

Russo-Campisi

(2017). Evidence-based practices in special education: Current assumptions and future considerations. Child & Youth Care Forum, 46, 193-205. doi:10.1007/s10566-017-9390-5

31.

Sansosti

F. J.

Doolan

M. L.

Remaklus

Krupko

Sansosti

J. M.

(2015). Computer-assisted interventions for students with autism spectrum disorders within school-based contexts: A quantitative meta-analysis of single-subject research. Review Journal of Autism and Developmental Disorders, 2, 128-140. doi:10.1007/s40489-014-0042-5

32.

Sigafoos

Drasgow

(2001). Conditional use of aided and unaided AAC: A review and clinical case demonstration. Focus on Autism and Other Developmental Disabilities, 16, 152-161. doi:10.1177/108835760101600303

33.

Thai

Nathan-Roberts

(2018). Social skill focuses of virtual reality systems for individuals diagnosed with autism spectrum disorder; A systematic review. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 62, 1469-1473. doi:10.1177/1541931218621333

34.

Zirkel

P. A.

(2013). Is it time for elevating the standard for FAPE under IDEA? Exceptional Children, 79, 497-508. doi:10.1177/001440291307900407

Technology-Aided Interventions for Individuals With Autism: Implications for Policy and Practice

Abstract

Keywords

Tweet

Key Points

Introduction

Legislation and Professional Standards

High-Tech AT Use for Students With ASD

SGDs

CAI

VBI

VR

RMI and Social Robots

Summary of High-Tech AT and Social-Communication Skills

Policy and Practice Implications

Conclusion

Footnotes

Declaration of Conflicting Interests

Funding

References