Knowledge Tracing Evaluation

Knowledge Tracing Evaluation is a scholarly methodological framework within educational data mining that systematically assesses the accuracy and efficacy of knowledge tracing models in predicting students' evolving cognitive states over time.

25

Publications

718

Citations

100

Authors

29

Institutions

Publications per year

2017–2026

14

Authors

100

  1. ZA
    Zachary A. Pardos

    University of California, Berkeley, United States

    4 publications · 69 citations

    4

    h-index

  2. YH
    Yun Huang

    University of Pittsburgh, United States

    3 publications · 88 citations

    3

    h-index

  3. NT
    Neil T. Heffernan

    Worcester Polytechnic Institute, United States

    3 publications · 112 citations

    3

    h-index

  4. JK
    Jussi Kasurinen

    Lappeenranta-Lahti University of Technology, Finland

    2 publications · 74 citations

    2

    h-index

  5. UN
    Uolevi Nikula

    Lappeenranta-Lahti University of Technology, Finland

    2 publications · 74 citations

    2

    h-index

1–5 of 100

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 154 citations

    5

    h-index

  2. Educational Data Mining

    Conference · 3 publications · 86 citations

    3

    h-index

  3. IEEE Transactions on Learning Technologies

    3 publications · 79 citations

    3

    h-index

  4. D-Scholarship@Pitt (University of Pittsburgh)

    Repository · 2 publications · 77 citations

    2

    h-index

  5. Infoscience (Ecole Polytechnique Fédérale de Lausanne)

    Repository · 1 publications · 11 citations

    1

    h-index

1–5