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    <journal-meta>
      <journal-id journal-id-type="nlm-ta">Rea Press</journal-id>
      <journal-id journal-id-type="publisher-id">null</journal-id>
      <journal-title>Rea Press</journal-title><issn pub-type="ppub">3009-3732</issn><issn pub-type="epub">3009-3732</issn><publisher>
      	<publisher-name>Rea Press</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">https://doi.org/10.31181/sa22202424</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group><subject>Artificial intelligence, Assistive technology, Special educational needs, LLMs</subject></subj-group>
      </article-categories>
      <title-group>
        <article-title>Artificial Intelligence in Special Education: A Literature Review</article-title><subtitle>Artificial Intelligence in Special Education: A Literature Review</subtitle></title-group>
      <contrib-group><contrib contrib-type="author">
	<name name-style="western">
	<surname> Aliu</surname>
		<given-names>Toluwani Victor</given-names>
	</name>
	<aff>University of Chester</aff>
	</contrib></contrib-group>		
      <pub-date pub-type="ppub">
        <month>09</month>
        <year>2024</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>01</day>
        <month>09</month>
        <year>2024</year>
      </pub-date>
      <volume>2</volume>
      <issue>2</issue>
      <permissions>
        <copyright-statement>© 2024 Rea Press</copyright-statement>
        <copyright-year>2024</copyright-year>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.5/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p></license>
      </permissions>
      <related-article related-article-type="companion" vol="2" page="e235" id="RA1" ext-link-type="pmc">
			<article-title>Artificial Intelligence in Special Education: A Literature Review</article-title>
      </related-article>
	  <abstract abstract-type="toc">
		<p>
			New avenues for communication with students who have Special Educational Needs (SEN) have begun to open up because of innovative educational technology. The most successful strategies over the past 20 years (2001–2020) have been those that utilize Artificial Intelligence (AI) techniques. The quality of life for SEN students is thought to be improved by the efficient use of AI techniques. Therefore, it becomes necessary to implement A.I. approaches to design procedures for both diagnosis and intervention. In addition, the study focuses on  Assistive Technology (AT) and provides information on the most pertinent research conducted over the previous 20 years for the earlier objectives. This paper also discusses the limitations of current AI use in special education, including the scarcity of intervention tools and the lack of standardized diagnostic methods. Furthermore, the review explores the unique challenges in developing countries in implementing AI-based solutions for special education. This review study advances the available research by reviewing the role of Large Language Models (LLMs) as an AT while building on existing research that has acknowledged the much earlier potential of AI technologies to empower special education.
		</p>
		</abstract>
    </article-meta>
  </front>
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