Adaptive Learner Models
Adaptive Learner Models is a computational framework within learner profiling that dynamically captures and updates individual learners' knowledge states, cognitive traits, and learning behaviors over time by integrating real-time interaction data, thereby distinguishing itself from static learner models through its capacity for ongoing personalization and responsiveness to evolving learner needs.
162
Publications
8K
Citations
478
Authors
189
Institutions
Publications per year
2017–2026
72
Parents
162
PROST: Parallel robust online simple tracking
Jakob Santner, Christian Leistner, Amir Saffari et al. · 2010 · 383 citations
Khalid Colchester, Hani Hagras, Daniyal Alghazzawi et al. · Journal of Artificial Intelligence and Soft Computing Research · 2016 · 320 citations · Full text
Education, Educational Technology, Artificial Intelligence In Education +16
Kinshuk Kinshuk, Nian‐Shing Chen, I-Ling Cheng et al. · International Journal of Artificial Intelligence in Education · 2016 · 305 citations · Full text
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189

University of Birmingham
Birmingham, United Kingdom
8 h-index
14 publications
531 citations

Vanderbilt University
Nashville, United States
6 h-index
10 publications
1.1K citations
University of Michigan
Ann Arbor, United States
5 h-index
7 publications
946 citations
Athabasca University
Athabasca, Canada
4 h-index
7 publications
788 citations
New York University
New York, United States
4 h-index
4 publications
532 citations
Abdelmalek Essaâdi University
Tétouan, Morocco
4 h-index
8 publications
238 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
8 publications
1.5K citations
American Medical Association
Chicago, United States
3 h-index
9 publications
2.9K citations
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5 publications · 441 citations
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Repository · 5 publications · 101 citations
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6 publications · 552 citations
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4 publications · 72 citations
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4 publications · 151 citations
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