Personalized Learning Recommendation

Personalized Learning Recommendation is an adaptive instructional strategy within intelligent tutoring system analytics that generates individualized learning pathways by analyzing learner-specific data to recommend tailored content, activities, or resources according to the learner’s cognitive, behavioral, and affective characteristics.

400

Publications

17.6K

Citations

1.1K

Authors

456

Institutions

Publications per year

2017–2026

234

Authors

1.1K

  1. HD
    Hendrik Drachsler

    Open University of the Netherlands, Netherlands

    7 publications · 506 citations

    7

    h-index

  2. HH
    Hans Hummel

    Open University of the Netherlands, Netherlands

    6 publications · 475 citations

    6

    h-index

  3. HO
    Hiroaki Ogata

    Tokushima University, Japan

    5 publications · 154 citations

    5

    h-index

  4. AK
    Aleksandra Klašnja‐Milićević

    University of Novi Sad, Serbia

    5 publications · 398 citations

    5

    h-index

  5. MS
    Mojtaba Salehi

    Tarbiat Modares University, Iran

    5 publications · 292 citations

    5

    h-index

1–5 of 1.1K

Venues

  1. 11

    h-index

  2. Procedia Computer Science

    10 publications · 497 citations

    10

    h-index

  3. Computers in Human Behavior

    8 publications · 970 citations

    8

    h-index

  4. IEEE Access

    8 publications · 467 citations

    8

    h-index

  5. IEEE Transactions on Learning Technologies

    7 publications · 239 citations

    7

    h-index

1–5