Concepedia

Explainable Item Modeling

Explainable Item Modeling is an item modeling approach that, as a genus, belongs to the class of methods for designing and structuring test or assessment items, and, as its differentia, specifically incorporates transparency and interpretability mechanisms to make the item generation, selection, and scoring processes humanly understandable and justifiable.

2

Publications

48

Citations

6

Authors

6

Institutions

Publications per year

2017–2026

0

Parents

Publications

2

1–2 of 2

Authors

6

  1. MJ
    Mark J. Gierl

    University of Alberta, Canada

    1 publications · 10 citations

    1

    h-index

  2. TM
    Thomas M. Haladyna

    Arizona State University, United States

    1 publications · 10 citations

    1

    h-index

  3. SR
    Sophia Rabe‐Hesketh

    University of California, Berkeley, United States

    1 publications · 38 citations

    1

    h-index

  4. SE
    Susan E. Embretson

    University of Kansas, United States

    1 publications · 38 citations

    1

    h-index

  5. SC
    Sun‐Joo Cho

    Vanderbilt University, United States

    1 publications · 38 citations

    1

    h-index

1–5 of 6

Institutions

6

  1. KU Leuven

    Leuven, Belgium

    1 h-index

    1 publications

    38 citations

  2. University of California, Berkeley

    Berkeley, United States

    1 h-index

    1 publications

    38 citations

  3. The Ohio State University

    Columbus, United States

    1 h-index

    1 publications

    38 citations

  4. Georgia Institute of Technology

    Atlanta, United States

    1 h-index

    1 publications

    38 citations

  5. University of London

    London, United Kingdom

    1 h-index

    1 publications

    38 citations

  6. Vanderbilt University

    Nashville, United States

    1 h-index

    1 publications

    38 citations

1–6 of 6

Venues

  1. Psychometrika

    1 publications · 38 citations

    1

    h-index

1–1