Bayesian Learning Analytics

Bayesian Learning Analytics is a computational framework within learning analytics that uses Bayesian inference to model and update the probability of learners' knowledge states based on observed data, distinguishing itself through its probabilistic reasoning and sequential evidence integration.

17

Publications

1K

Citations

57

Authors

27

Institutions

Publications per year

2017–2026

9

Authors

57

  1. RS
    Ryan S. Baker

    Columbia University, United States

    2 publications · 58 citations

    2

    h-index

  2. OS
    Ofer Shai

    University of Toronto, Canada

    1 publications · 61 citations

    1

    h-index

  3. NV
    N.A.W. van Riel

    Eindhoven University of Technology, Netherlands

    1 publications · 17 citations

    1

    h-index

  4. BJ
    Benjamin J. Blencowe

    University of Toronto, Canada

    1 publications · 61 citations

    1

    h-index

  5. JJ
    J. J. Martin

    University of Pittsburgh, United States

    1 publications · 152 citations

    1

    h-index

1–5 of 57

Venues

  1. Computers & Education

    2 publications · 158 citations

    2

    h-index

  2. User Modeling and User-Adapted Interaction

    1 publications · 233 citations

    1

    h-index

  3. American Behavioral Scientist

    ABS · 1 publications · 44 citations

    1

    h-index

  4. Sustainability

    1 publications · 18 citations

    1

    h-index

  5. Reaction Chemistry & Engineering

    1 publications · 22 citations

    1

    h-index

1–5