Learning Analytics For Affect

Learning Analytics for Affect is a learning analytics approach that specifically integrates affective data—such as emotions, engagement, and motivation—to interpret and enhance educational experiences by systematically analyzing learners' emotional and cognitive states within digital learning environments.

5

Publications

332

Citations

23

Authors

12

Institutions

Publications per year

2017–2026

2

Authors

23

  1. DD
    Devansh Desai

    University of North Carolina at Charlotte, United States

    1 publications · 18 citations

    1

    h-index

  2. NB
    Nigel Bosch

    University of Illinois Urbana-Champaign, United States

    1 publications · 61 citations

    1

    h-index

  3. WZ
    Weinan Zhao

    Florida State University, United States

    1 publications · 61 citations

    1

    h-index

  4. PB
    Paulo Blikstein

    Stanford University, United States

    1 publications · 23 citations

    1

    h-index

  5. RS
    Ryan S. Baker

    Columbia University, United States

    1 publications · 61 citations

    1

    h-index

1–5 of 23

Venues

  1. International Joint Conference on Artificial Intelligence

    Conference · 1 publications · 61 citations

    1

    h-index

  2. 1

    h-index

  3. AI Magazine

    1 publications · 213 citations

    1

    h-index

  4. International Journal of Mobile and Blended Learning

    JMBL · 1 publications · 13 citations

1–4