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Utilization of Artificial Intelligence and Assistive Technology in Autism: Diagnosis, Treatment, and Education Applications--A Systematic Literature Review

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Title: Utilization of Artificial Intelligence and Assistive Technology in Autism: Diagnosis, Treatment, and Education Applications--A Systematic Literature Review
Language: English
Authors: Mohammad A. Beirat (ORCID 0000-0001-8730-6405), Ahmad Algolaylat (ORCID 0000-0001-6261-4428), Hussein Al Njadat (ORCID 0000-0001-8545-1983), Bassam AlAbdallat (ORCID 0000-0002-2704-7576), Alaa K. Al-Makhzoomy (ORCID 0000-0001-6660-1018)
Source: Educational Process: International Journal. Article e2025350 2025 17.
Availability: UNIVERSITEPARK Limited. iTOWER Plaza (No61, 9th floor) Merkez Mh Akar Cd No3, Sisli, Istanbul, Turkey 34382. e-mail: editor@edupij.com; Web site: http://www.edupij.com/
Peer Reviewed: Y
Page Count: 27
Publication Date: 2025
Document Type: Journal Articles
Information Analyses
Descriptors: Artificial Intelligence, Assistive Technology, Autism Spectrum Disorders, Clinical Diagnosis, Intervention, Technology Uses in Education, Disability Identification, Affordances, Barriers, Robotics, Computer Mediated Communication, Computer Simulation, Ethics, Privacy
ISSN: 2147-0901
2564-8020
Abstract: Background/purpose: This paper systematically reviews current advancements in AI-based diagnostic tools and assistive technologies, analyzing their influence on the early detection, treatment, and educational support of autism spectrum disorders (ASDs). The review aims to identify both the benefits and challenges of incorporating these technologies into autism care and to highlight future opportunities, especially in enhancing learning and communication outcomes for individuals with autism. Materials/methods: A systematic literature review was conducted based on 27 peer-reviewed articles published between 2010 and 2023. The search strategy involved major databases, including Scopus, ScienceDirect, PubMed, JSTOR, and Google Scholar. The analysis follows the PRISMA approach, with specific inclusion criteria and quality assessment procedures in place. The study focuses on four key subthemes: AI-driven diagnostic systems, therapeutic and assistive robotics, educational and communication applications, including augmented reality applications, and ethical and implementation challenges associated with autism-related technologies. Results: The reviewed studies demonstrate that AI tools offer significant potential for early and precise autism diagnosis, particularly through the application of machine learning algorithms to behavioral and physiological data. Assistive technologies, particularly social robots and AR platforms, show positive outcomes in therapeutic engagement. Supporting educational development and skill acquisition. However, issues such as limited accessibility, ethical concerns regarding data privacy, and integration barriers persist. Conclusion: AI and assistive technologies are transformative in autism care, offering innovative solutions for diagnosis and treatment. However, their successful implementation requires addressing ethical, infrastructural, and cultural challenges. This study provides evidence-based insights and practical recommendations for researchers, clinicians, educators, and policymakers to enhance the equity and impact of these emerging technologies in autism intervention and inclusive learning environments.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1483560
Database: ERIC
FullText Text:
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  Data: Utilization of Artificial Intelligence and Assistive Technology in Autism: Diagnosis, Treatment, and Education Applications--A Systematic Literature Review
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  Data: <searchLink fieldCode="AR" term="%22Mohammad+A%2E+Beirat%22">Mohammad A. Beirat</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-8730-6405">0000-0001-8730-6405</externalLink>)<br /><searchLink fieldCode="AR" term="%22Ahmad+Algolaylat%22">Ahmad Algolaylat</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6261-4428">0000-0001-6261-4428</externalLink>)<br /><searchLink fieldCode="AR" term="%22Hussein+Al+Njadat%22">Hussein Al Njadat</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-8545-1983">0000-0001-8545-1983</externalLink>)<br /><searchLink fieldCode="AR" term="%22Bassam+AlAbdallat%22">Bassam AlAbdallat</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-2704-7576">0000-0002-2704-7576</externalLink>)<br /><searchLink fieldCode="AR" term="%22Alaa+K%2E+Al-Makhzoomy%22">Alaa K. Al-Makhzoomy</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6660-1018">0000-0001-6660-1018</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Educational+Process%3A+International+Journal%22"><i>Educational Process: International Journal</i></searchLink>. Article e2025350 2025 17.
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  Data: UNIVERSITEPARK Limited. iTOWER Plaza (No61, 9th floor) Merkez Mh Akar Cd No3, Sisli, Istanbul, Turkey 34382. e-mail: editor@edupij.com; Web site: http://www.edupij.com/
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  Data: 27
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  Data: Journal Articles<br />Information Analyses
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  Data: <searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Assistive+Technology%22">Assistive Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Autism+Spectrum+Disorders%22">Autism Spectrum Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Clinical+Diagnosis%22">Clinical Diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Intervention%22">Intervention</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Disability+Identification%22">Disability Identification</searchLink><br /><searchLink fieldCode="DE" term="%22Affordances%22">Affordances</searchLink><br /><searchLink fieldCode="DE" term="%22Barriers%22">Barriers</searchLink><br /><searchLink fieldCode="DE" term="%22Robotics%22">Robotics</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Mediated+Communication%22">Computer Mediated Communication</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Simulation%22">Computer Simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Ethics%22">Ethics</searchLink><br /><searchLink fieldCode="DE" term="%22Privacy%22">Privacy</searchLink>
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  Data: 2147-0901<br />2564-8020
– Name: Abstract
  Label: Abstract
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  Data: Background/purpose: This paper systematically reviews current advancements in AI-based diagnostic tools and assistive technologies, analyzing their influence on the early detection, treatment, and educational support of autism spectrum disorders (ASDs). The review aims to identify both the benefits and challenges of incorporating these technologies into autism care and to highlight future opportunities, especially in enhancing learning and communication outcomes for individuals with autism. Materials/methods: A systematic literature review was conducted based on 27 peer-reviewed articles published between 2010 and 2023. The search strategy involved major databases, including Scopus, ScienceDirect, PubMed, JSTOR, and Google Scholar. The analysis follows the PRISMA approach, with specific inclusion criteria and quality assessment procedures in place. The study focuses on four key subthemes: AI-driven diagnostic systems, therapeutic and assistive robotics, educational and communication applications, including augmented reality applications, and ethical and implementation challenges associated with autism-related technologies. Results: The reviewed studies demonstrate that AI tools offer significant potential for early and precise autism diagnosis, particularly through the application of machine learning algorithms to behavioral and physiological data. Assistive technologies, particularly social robots and AR platforms, show positive outcomes in therapeutic engagement. Supporting educational development and skill acquisition. However, issues such as limited accessibility, ethical concerns regarding data privacy, and integration barriers persist. Conclusion: AI and assistive technologies are transformative in autism care, offering innovative solutions for diagnosis and treatment. However, their successful implementation requires addressing ethical, infrastructural, and cultural challenges. This study provides evidence-based insights and practical recommendations for researchers, clinicians, educators, and policymakers to enhance the equity and impact of these emerging technologies in autism intervention and inclusive learning environments.
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    Languages:
      – Text: English
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        PageCount: 27
    Subjects:
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Assistive Technology
        Type: general
      – SubjectFull: Autism Spectrum Disorders
        Type: general
      – SubjectFull: Clinical Diagnosis
        Type: general
      – SubjectFull: Intervention
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      – SubjectFull: Technology Uses in Education
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      – SubjectFull: Disability Identification
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      – SubjectFull: Affordances
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      – SubjectFull: Barriers
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      – SubjectFull: Robotics
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      – SubjectFull: Computer Mediated Communication
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      – SubjectFull: Computer Simulation
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      – SubjectFull: Ethics
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      – SubjectFull: Privacy
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      – TitleFull: Utilization of Artificial Intelligence and Assistive Technology in Autism: Diagnosis, Treatment, and Education Applications--A Systematic Literature Review
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