Misconception Detection

Misconception Detection is a diagnostic process in Educational Data Mining that identifies persistent, context-specific student misunderstandings by analyzing patterns in learning behaviors and performance data to distinguish them from temporary errors or lack of knowledge.

649

Publications

31K

Citations

1.6K

Authors

545

Institutions

Publications per year

2017–2026

224

Authors

1.6K

  1. KF
    Kathleen F. McCoy

    University of Delaware, United States

    7 publications · 209 citations

    7

    h-index

  2. ES
    Elliot Soloway

    University of Michigan, United States

    6 publications · 470 citations

    6

    h-index

  3. FM
    Fatni Mufit

    State University of Padang, Indonesia

    6 publications · 188 citations

    6

    h-index

  4. AS
    Achmad Samsudin

    Indonesia University of Education, Indonesia

    4 publications · 150 citations

    5

    h-index

  5. DY
    Der‐Ching Yang

    National Chiayi University, Taiwan

    5 publications · 107 citations

    5

    h-index

1–5 of 1.6K

Venues

  1. Journal of Physics Conference Series

    21 publications · 532 citations

    16

    h-index

  2. Procedia - Social and Behavioral Sciences

    12 publications · 251 citations

    11

    h-index

  3. International Journal of Science Education

    IJSE · 10 publications · 1.6K citations

    10

    h-index

  4. 7

    h-index

  5. ACM SIGCSE Bulletin

    6 publications · 391 citations

    6

    h-index

1–5