Adaptive Learning Recommendation

Adaptive Learning Recommendation is a systematic method within educational recommender systems that dynamically personalizes learning resources and pathways for individual learners by iteratively analyzing their real-time interactions, performance, and contextual needs to optimize knowledge acquisition and skill development.

142

Publications

6K

Citations

445

Authors

213

Institutions

Publications per year

2017–2026

81

Authors

445

  1. BV
    Boban Vesin

    Norwegian University of Science and Technology, Norway

    3 publications · 106 citations

    3

    h-index

  2. AK
    Aleksandra Klašnja‐Milićević

    University of Novi Sad, Serbia

    3 publications · 252 citations

    3

    h-index

  3. JG
    Jesús G. Boticario

    Universidad Nacional de Educación a Distancia, Spain

    3 publications · 103 citations

    3

    h-index

  4. IL
    Igor Labutov

    Cornell University, United States

    3 publications · 63 citations

    3

    h-index

  5. OC
    Olga C. Santos

    Universidad Nacional de Educación a Distancia, Spain

    3 publications · 103 citations

    3

    h-index

1–5 of 445

Venues

  1. Expert Systems with Applications

    5 publications · 292 citations

    5

    h-index

  2. 4

    h-index

  3. Procedia Computer Science

    3 publications · 95 citations

    3

    h-index

  4. IEEE Access

    3 publications · 183 citations

    3

    h-index

  5. 3

    h-index

1–5