Neural Knowledge Tracing

Neural Knowledge Tracing is a machine learning framework within knowledge tracing that employs neural networks to model student knowledge states by capturing complex, nonlinear relationships between past interactions and future performance.

43

Publications

3.2K

Citations

170

Authors

56

Institutions

Publications per year

2017–2026

41

Variants

Nkt

Authors

170

  1. QL
    Qi Liu

    University of Science and Technology of China, China

    3 publications · 263 citations

    3

    h-index

  2. ZH
    Zhenya Huang

    University of Science and Technology of China, China

    3 publications · 263 citations

    3

    h-index

  3. EC
    Enhong Chen

    University of Science and Technology of China, China

    3 publications · 263 citations

    3

    h-index

  4. SW
    Shijin Wang

    Tongji University, China

    3 publications · 263 citations

    3

    h-index

  5. ZL
    Zitao Liu

    Michigan State University, United States

    2 publications · 90 citations

    2

    h-index

1–5 of 170

Venues

  1. Expert Systems with Applications

    6 publications · 218 citations

    6

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 213 citations

    3

    h-index

  3. Applied Sciences

    2 publications · 59 citations

    2

    h-index

  4. Information Sciences

    2 publications · 239 citations

    2

    h-index

  5. Educational Data Mining

    Conference · 2 publications · 69 citations

    2

    h-index

1–5