Adaptive Feedback Generation

Adaptive Feedback Generation is a feedback generation approach that dynamically tailors feedback content, timing, and delivery based on individual learner characteristics, performance, and contextual factors to optimize learning outcomes.

48

Publications

1.9K

Citations

172

Authors

81

Institutions

Publications per year

2017–2026

21

Authors

172

  1. AA
    Anastasios A. Economides

    University of Macedonia, Greece

    2 publications · 40 citations

    2

    h-index

  2. SA
    Sohail Agha

    Tulane University, United States

    2 publications · 53 citations

    2

    h-index

  3. KV
    Kasisomayajula Viswanath

    Dana-Farber Cancer Institute, United States

    2 publications · 53 citations

    2

    h-index

  4. KK
    Kiros Karamanidis

    German Sport University Cologne, Germany

    2 publications · 130 citations

    2

    h-index

  5. CS
    Christina Synowiec

    Results for Development Institute, United States

    2 publications · 53 citations

    2

    h-index

1–5 of 172

Venues

  1. IEEE Transactions on Learning Technologies

    4 publications · 126 citations

    4

    h-index

  2. Gates Open Research

    2 publications · 53 citations

    2

    h-index

  3. Bulletin of Marine Science

    1 publications · 11 citations

    1

    h-index

  4. Chaos Solitons & Fractals

    1 publications · 38 citations

    1

    h-index

  5. Computers in Human Behavior

    1 publications · 74 citations

    1

    h-index

1–5