Multimodal Learner Modeling

Multimodal Learner Modeling is a learner modeling approach that integrates multiple modalities of data—such as behavioral, physiological, linguistic, and interactional inputs—to construct a comprehensive, individualized representation of a learner’s cognitive, affective, and metacognitive states within personalized learning systems.

45

Publications

2.3K

Citations

158

Authors

78

Institutions

Publications per year

2017–2026

30

Authors

158

  1. MW
    Marcelo Worsley

    Stanford University, United States

    7 publications · 198 citations

    7

    h-index

  2. LM
    Louis‐Philippe Morency

    Carnegie Mellon University, United States

    3 publications · 124 citations

    3

    h-index

  3. SS
    Stefan Scherer

    University of Southern California, United States

    3 publications · 124 citations

    3

    h-index

  4. MC
    Mutlu Cukurova

    University College London, United Kingdom

    3 publications · 183 citations

    3

    h-index

  5. PB
    Paulo Blikstein

    Stanford University, United States

    2 publications · 87 citations

    2

    h-index

1–5 of 158

Venues

  1. Journal of Computer Assisted Learning

    5 publications · 365 citations

    5

    h-index

  2. British Journal of Educational Technology

    BJET · 3 publications · 329 citations

    3

    h-index

  3. IEEE Access

    2 publications · 57 citations

    2

    h-index

  4. Education and Information Technologies

    2 publications · 42 citations

    2

    h-index

  5. Learning and Instruction

    1 publications · 33 citations

    1

    h-index

1–5