Learner Performance Prediction

Learner Performance Prediction is a computational modeling approach within educational data mining that distinguishes itself by forecasting individual students’ future academic outcomes based on historical and real-time learning interaction data.

1.6K

Publications

84.1K

Citations

3.9K

Authors

1.3K

Institutions

Publications per year

2017–2026

1K

Variants

Student Performance Prediction

Authors

3.9K

  1. SK
    Sotiris Kotsiantis

    University of Patras, Greece

    16 publications · 1.3K citations

    15

    h-index

  2. RS
    Ryan S. Baker

    Columbia University, United States

    9 publications · 650 citations

    10

    h-index

  3. CR
    Cristóbal Romero

    University of Córdoba, Spain

    9 publications · 4K citations

    9

    h-index

  4. KR
    Kenneth R. Koedinger

    Carnegie Mellon University, United States

    9 publications · 771 citations

    9

    h-index

  5. NT
    Neil T. Heffernan

    Worcester Polytechnic Institute, United States

    8 publications · 717 citations

    9

    h-index

1–5 of 3.9K

Venues

  1. Education and Information Technologies

    41 publications · 2.7K citations

    29

    h-index

  2. IEEE Access

    34 publications · 2.3K citations

    27

    h-index

  3. Applied Sciences

    25 publications · 1.7K citations

    21

    h-index

  4. arXiv (Cornell University)

    Repository · 22 publications · 1.8K citations

    18

    h-index

  5. International Journal of Computer Applications

    23 publications · 852 citations

    17

    h-index

1–5