Artificial intelligence in special education: a systematic review


Interactive Learning Environments, vol.31, no.10, pp.7335-7353, 2023 (SSCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 31 Issue: 10
  • Publication Date: 2023
  • Doi Number: 10.1080/10494820.2022.2067186
  • Journal Name: Interactive Learning Environments
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, Applied Science & Technology Source, Communication Abstracts, Computer & Applied Sciences, EBSCO Education Source, Educational research abstracts (ERA), ERIC (Education Resources Information Center), INSPEC, Psycinfo
  • Page Numbers: pp.7335-7353
  • Keywords: Artificial intelligence, special education, artificial intelligence in education, artificial intelligence in special education, autism spectrum disorders, educational technology in special education, RESEARCH TRENDS, STUDENTS, INTELLIGENCE, CHILDREN, DISABILITIES, DIAGNOSIS, SKILLS, TOOL
  • Kayseri University Affiliated: No


© 2022 Informa UK Limited, trading as Taylor & Francis Group.The role of techniques involving Artificial Intelligence (AI) has been becoming increasingly important in educational settings. This study aims to reveal the recent trends in research into artificial intelligence in special education by using the systematic review method. Across the 29 studies published between 2008 and 2020 that are reviewed here, the majority are articles on quantitative research carried out in the United States. In terms of learning content, most of the studies are about skill development, focusing on cognitive and affective factors. Moreover, the research was carried out in school settings with learners from various backgrounds. The purposes for and methods of using AI were examined and it was found that software-based methods are more common. The primary disability type examined in the articles covered in this review were disorders on the autism spectrum. There is a tendency toward technical models rather than educational models. ANN and SVM are the most used technical theoretical infrastructures. This study yielded interesting results both on the evolution of AI in special education over the years and on its future development. This paper ends with suggestions developed in light of these studies for the use of artificial intelligence in special education.