Explainable Student Modeling

Explainable Student Modeling is a student modeling approach that, as a genus, constructs computational representations of learners' knowledge, skills, and cognitive processes, and, as its differentia, explicitly provides interpretable, transparent, and justifiable insights into the model's reasoning and decision-making mechanisms for stakeholders such as educators, learners, or developers.

8

Publications

352

Citations

20

Authors

12

Institutions

Publications per year

2017–2026

1

Authors

20

  1. HH
    Haym Hirsh

    Rutgers, The State University of New Jersey, United States

    2 publications · 52 citations

    2

    h-index

  2. IK
    In-Yung Kim

    Palo Alto University, United States

    2 publications · 52 citations

    2

    h-index

  3. IE
    Ian Ellery

    Palo Alto University, United States

    2 publications · 52 citations

    2

    h-index

  4. FB
    Fedor Bakalov

    University of Pittsburgh, United States

    1 publications · 21 citations

    1

    h-index

  5. LZ
    Laura Zangori

    University of Missouri, United States

    1 publications · 42 citations

    1

    h-index

1–5 of 20

Venues

  1. Machine Learning

    2 publications · 52 citations

    2

    h-index

  2. Science & Education

    1 publications · 42 citations

    1

    h-index

  3. 1

    h-index

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

    Repository · 1 publications · 21 citations

    1

    h-index

  5. National Conference on Artificial Intelligence

    Conference · 1 publications · 21 citations

    1

    h-index

1–5