Multimodal Learning Analytics

Multimodal Learning Analytics is a learning analytics approach that integrates and analyzes multiple streams of data—such as visual, auditory, gestural, and physiological signals—derived from learners’ interactions, thereby extending beyond unimodal analysis to capture complex, context-rich representations of cognitive and affective states in educational settings.

148

Publications

7.2K

Citations

375

Authors

171

Institutions

Publications per year

2017–2026

111

Authors

375

  1. MW
    Marcelo Worsley

    Stanford University, United States

    19 publications · 1K citations

    17

    h-index

  2. RM
    Roberto Martínez‐Maldonado

    Monash University, Australia

    16 publications · 892 citations

    16

    h-index

  3. DG
    Dragan Gašević

    Monash University, Australia

    12 publications · 768 citations

    12

    h-index

  4. MC
    Mutlu Cukurova

    University College London, United Kingdom

    11 publications · 620 citations

    11

    h-index

  5. PB
    Paulo Blikstein

    Stanford University, United States

    11 publications · 1.1K citations

    10

    h-index

1–5 of 375

Venues

  1. Journal of Learning Analytics

    9 publications · 727 citations

    9

    h-index

  2. British Journal of Educational Technology

    BJET · 8 publications · 732 citations

    8

    h-index

  3. IEEE Access

    6 publications · 177 citations

    6

    h-index

  4. Computers in Human Behavior

    6 publications · 620 citations

    6

    h-index

  5. Journal of Computer Assisted Learning

    6 publications · 545 citations

    6

    h-index

1–5