Adaptive Learning Resource Recommendation

Adaptive Learning Resource Recommendation is a type of personalized recommendation system that dynamically adjusts the selection and presentation of learning resources based on continuous analysis of individual learners’ interactions, preferences, and performance to optimize educational outcomes.

58

Publications

2.2K

Citations

196

Authors

108

Institutions

Publications per year

2017–2026

42

Authors

196

  1. JP
    José Palazzo Moreira de Oliveira

    Universidade Federal do Rio Grande do Sul, Brazil

    2 publications · 36 citations

    2

    h-index

  2. EP
    Eric Poitras

    McGill University, Canada

    2 publications · 32 citations

    2

    h-index

  3. NM
    Nikos Manouselis

    Agricultural University of Athens, Greece

    2 publications · 50 citations

    2

    h-index

  4. GM
    Guilherme Medeiros Machado

    Universidade Federal do Rio Grande do Sul, Brazil

    2 publications · 36 citations

    2

    h-index

  5. FD
    Fang Dong

    Southeast University, China

    2 publications · 73 citations

    2

    h-index

1–5 of 196

Venues

  1. Scientific Programming

    2 publications · 29 citations

    2

    h-index

  2. Interactive Learning Environments

    ILE · 2 publications · 63 citations

    2

    h-index

  3. Procedia Computer Science

    2 publications · 108 citations

    2

    h-index

  4. 2

    h-index

  5. Complexity

    2 publications · 46 citations

    2

    h-index

1–5