Adaptive Content Generation

Adaptive Content Generation is a computational method in personalized learning systems that dynamically produces instructional materials tailored to individual learners' needs, preferences, and performance by leveraging real-time data and pedagogical models.

137

Publications

5.7K

Citations

390

Authors

151

Institutions

Publications per year

2017–2026

33

Authors

390

  1. GN
    Georgios N. Yannakakis

    IT University of Copenhagen, Denmark

    5 publications · 477 citations

    5

    h-index

  2. JT
    Julian Togelius

    New York University, United States

    5 publications · 477 citations

    5

    h-index

  3. DG
    Demetrios G. Sampson

    University of Piraeus, Greece

    4 publications · 193 citations

    4

    h-index

  4. JV
    Julita Vassileva

    University of Saskatchewan, Canada

    3 publications · 376 citations

    3

    h-index

  5. NS
    Noor Shaker

    IT University of Copenhagen, Denmark

    3 publications · 286 citations

    3

    h-index

1–5 of 390

Venues

  1. TU/e Research Portal

    Repository · 4 publications · 176 citations

    4

    h-index

  2. Expert Systems with Applications

    3 publications · 91 citations

    3

    h-index

  3. arXiv (Cornell University)

    Repository · 3 publications · 85 citations

    3

    h-index

  4. 3

    h-index

  5. 2019 IEEE Conference on Games (CoG)

    Conference · 2 publications · 171 citations

    2

    h-index

1–5