
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/">
  <dc:language>eng</dc:language>
  <dc:rights>http://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:description xml:lang="eng">Artificial Intelligence (AI) is redefining the landscape of personalized education by enabling adaptive systems
that respond dynamically to individual learning needs. This paper explores how AI technologies-including machine learning,
big data analytics, and intelligent tutoring systems-support the transformation of pedagogical models. Key opportunities
discussed include real-time personalization of content delivery, increased student motivation, and inclusive learning environments.
At the same time, the study critically examines potential risks, such as data privacy concerns, algorithmic bias, and the
erosion of human-centered pedagogy. Policy implications are addressed with recommendations for regulatory frameworks to
ensure ethical and responsible AI integration into education. The paper emphasizes the need for empirical research to validate
AI-driven models in diverse educational settings. By aligning technological innovation with humanistic values, the paper contributes
to ongoing discourse on how AI can support-not supplant-the role of educators. The findings provide a foundation for
future research and policy design aimed at creating equitable, transparent, and effective personalized learning ecosystems.</dc:description>
  <dc:subject xml:lang="eng">artificial intelligence, personalized learning, educational policy, algorithmic ethics, adaptive learning systems.</dc:subject>
  <dc:format>application/pdf</dc:format>
  <dc:format>247193 bytes</dc:format>
  <dc:identifier>https://unilib.phaidrabg.rs/o:8322</dc:identifier>
  <dc:identifier>doi:10.23947/2334-8496-2025-13-2-541-549</dc:identifier>
  <dc:source>International Journal of Cognitive Research in Science, Engineering and Education (IJCRSEE)</dc:source>
  <dc:source>volume: 13</dc:source>
  <dc:source>number: 2</dc:source>
  <dc:source>startpage: 541</dc:source>
  <dc:source>endpage: 549</dc:source>
  <dc:creator id="https://orcid.org/0000-0003-0039-7370">Stošić, Lazar</dc:creator>
  <dc:creator id="https://orcid.org/0000-0003-3715-468X">Radonjić, Aleksandar</dc:creator>
  <dc:creator id="https://orcid.org/0000-0002-6299-371X">Krčadinac, Olja</dc:creator>
  <dc:creator id="https://orcid.org/0000-0002-6798-6981">Baltezarević, Borivoje</dc:creator>
  <dc:creator>Mikhailova, Olga</dc:creator>
  <dc:date>2025</dc:date>
  <dc:type>info:eu-repo/semantics/article</dc:type>
  <dc:title xml:lang="eng">Personalized Learning through Artificial Intelligence: Opportunities, Risks, and Policy Perspectives</dc:title>
</oai_dc:dc>
