Computer Adaptive Classification Testing

Computer Adaptive Classification Testing is a type of computerized adaptive testing that dynamically selects items to classify examinees into predefined categories based on their estimated proficiency, using item response theory to optimize measurement precision and decision accuracy.

9

Publications

201

Citations

26

Authors

14

Institutions

Publications per year

2017–2026

2

Variants

Cact

Authors

26

  1. TJ
    Theo J. H. M. Eggen

    University of Twente, Netherlands

    1 publications · 12 citations

    1

    h-index

  2. TJ
    Theodorus Johannes Hendrikus Maria Eggen

    University of Twente, Netherlands

    1 publications · 12 citations

    1

    h-index

  3. JK
    Jiseon Kim

    Korea Advanced Institute of Science and Technology, South Korea

    1 publications · 10 citations

    1

    h-index

  4. BP
    Bernard P. Veldkamp

    University of Twente, Netherlands

    1 publications · 12 citations

    1

    h-index

  5. HC
    Hyewon Chung

    Chungnam National University, South Korea

    1 publications · 10 citations

    1

    h-index

1–5 of 26

Venues

  1. Educational and Psychological Measurement

    2 publications · 20 citations

    2

    h-index

  2. Applied Psychological Measurement

    1 publications · 12 citations

    1

    h-index

  3. Health Services Research

    HSR · 1 publications · 22 citations

    1

    h-index

  4. University of Twente Research Information

    Repository · 1 publications · 12 citations

    1

    h-index

  5. Journal of Pain and Symptom Management

    1 publications · 14 citations

    1

    h-index

1–5