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Personalized learning with educational recommender systems, ontology networks, and educator-in-the-loop

Primary research

#520

T1new
Topic
unassigned (set during synthesis)
First seen
2026-07-21 07:15:56
Last seen
2026-07-21 07:15:56

Source raw items (1)

  • Semantic Scholar2026-07-21 07:15:19
    Personalized learning with educational recommender systems, ontology networks, and educator-in-the-loop

    This paper examines the role of Information and Communication Technologies (ICT) in education, focusing on challenges like the digital divide and the rise of generative AI. While these technologies expand learning opportunities, they also deepen inequalities, underscoring the need for inclusive strategies. Personalized teaching, supported by Educational Recommender Systems (ERS), tailors’ instruction to student needs, yet many ERS prioritize efficiency over pedagogy. The Teacher-in-the-Loop (TITL) approach addresses this by integrating educators’ expertise, ensuring context-aware recommendations. This study proposes a Framework for Personalized Teaching that combines Ontology-driven networks with ERS and TITL to enhance adaptability and inclusivity. Through a case study and literature review, it explores how teacher involvement in ERS can better address student diversity. By advancing ethical and pedagogically sound recommender systems, this research contributes to the global discourse on equitable, high-quality education that balances technological advancements with human-centered teaching.