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The evidence behind the series
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Browse the scientific research and professional literature used across all seven volumes of The Science of Learning for Educators.
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- Vol 5 RE: Chapter 15
intelligent tutoring systemslearning analyticsnatural language processinglarge language modelsgenerative aimultimodal learning analyticshuman–ai collaborationself-regulated learningPreprint Evidence summaryAt a glance
Feng, Zhang, and Gašević map changes in artificial intelligence in education by analysing 2,398 articles published from 2020 through 2024 across eight core AIED and learning-analytics venues. Their three-level keyword co-occurrence network analysis examines the field’s overall structure, major knowledge clusters, and emerging bridging topics.
Key ideas
Established technical themes—including intelligent tutoring systems, learning analytics, natural language processing, MOOCs, computer vision, and causal inference—remain prominent. Longitudinal patterns show the rapid rise of large language models and generative AI, alongside multimodal learning analytics and human–AI collaboration. Within generative-AI work, personalisation, self-regulated learning, feedback, assessment, motivation, and ethics are central interests. The authors interpret these developments as movement toward more co-adaptive and human-centred educational AI, while the field remains strongly technology focused.
Why it matters
Because results depend on selected venues, author keywords, preprocessing, and network thresholds, the map describes publication patterns rather than establishing instructional effectiveness or forecasting which technologies will endure.
A transparent research trail
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What it contributes
Evidence summaries explain the central idea and why the source matters to educators.
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Edition abbreviations
- TE
- Teacher Edition
- PE
- Practice Edition
- RE
- Research Edition
Citation checks
References are checked against publisher records, scholarly indexes, DOI or ISBN metadata, repositories and author records where available. An entry marked [Citation not verified] preserves the wording found in the relevant volume without attributing findings to an unconfirmed work.
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