Bayesian Student Modeling

Bayesian Student Modeling is a computational approach to learner profiling that uses Bayesian inference to dynamically update probabilistic representations of student knowledge and skills based on observed performance and prior evidence.

137

Publications

5.8K

Citations

325

Authors

150

Institutions

Publications per year

2017–2026

25

Authors

325

  1. RS
    Ryan S. Baker

    Columbia University, United States

    6 publications · 182 citations

    6

    h-index

  2. ZA
    Zachary A. Pardos

    University of California, Berkeley, United States

    6 publications · 138 citations

    6

    h-index

  3. CC
    Cristina Conati

    University of British Columbia, Canada

    5 publications · 268 citations

    5

    h-index

  4. KV
    Kurt VanLehn

    University of Pittsburgh, United States

    5 publications · 414 citations

    5

    h-index

  5. EM
    Eva Millán

    Universidad de Málaga, Spain

    4 publications · 229 citations

    4

    h-index

1–5 of 325

Venues

  1. Educational Data Mining

    Conference · 8 publications · 250 citations

    8

    h-index

  2. Computers & Education

    4 publications · 727 citations

    4

    h-index

  3. arXiv (Cornell University)

    Repository · 3 publications · 116 citations

    3

    h-index

  4. 3

    h-index

  5. 3

    h-index

1–5