Automated Exercise Generation

Automated Exercise Generation is a computational method that systematically produces pedagogical exercises or practice tasks without manual human authoring, distinguished by its reliance on algorithmic rules, templates, or artificial intelligence models to generate contextually relevant and instructionally valid problems within a specific domain.

30

Publications

1K

Citations

94

Authors

41

Institutions

Publications per year

2017–2026

14

Authors

94

  1. MM
    Muhammad Mudassar Yamin

    Norwegian University of Science and Technology, Norway

    2 publications · 75 citations

    2

    h-index

  2. MU
    Mohib Ullah

    Norwegian University of Science and Technology, Norway

    2 publications · 75 citations

    2

    h-index

  3. EH
    Ehtesham Hashmi

    Norwegian University of Science and Technology, Norway

    2 publications · 75 citations

    2

    h-index

  4. BK
    Basel Katt

    Norwegian University of Science and Technology, Norway

    2 publications · 75 citations

    2

    h-index

  5. DR
    Danijel Radošević

    University of Zagreb, Croatia

    1 publications · 19 citations

    1

    h-index

1–5 of 94

Venues

  1. Computer Assisted Language Learning

    2 publications · 34 citations

    2

    h-index

  2. IEEE Transactions on Education

    1 publications · 27 citations

    1

    h-index

  3. Informatics in Education

    1 publications · 203 citations

    1

    h-index

  4. arXiv (Cornell University)

    Repository · 1 publications · 20 citations

    1

    h-index

  5. Computer Languages Systems & Structures

    1 publications · 21 citations

    1

    h-index

1–5