Machine-assisted Scoring

Machine-Assisted Scoring is a computational methodology in educational assessment that integrates automated systems with human judgment to enhance the accuracy, consistency, and efficiency of scoring processes by leveraging algorithmic support for decision-making while retaining human oversight.

112

Publications

5.2K

Citations

346

Authors

152

Institutions

Publications per year

2017–2026

49

Authors

346

  1. AC
    Aoife Cahill

    Educational Testing Service, United States

    4 publications · 97 citations

    4

    h-index

  2. NM
    Nitin Madnani

    Educational Testing Service, United States

    3 publications · 83 citations

    3

    h-index

  3. AL
    Anastassia Loukina

    Educational Testing Service, United States

    3 publications · 65 citations

    3

    h-index

  4. DM
    David M. Williamson

    University of Cambridge, United Kingdom

    3 publications · 418 citations

    3

    h-index

  5. SG
    Stephen G. Clyman

    National Board of Medical Examiners, United States

    3 publications · 141 citations

    3

    h-index

1–5 of 346

Venues

  1. Applied Measurement in Education

    6 publications · 256 citations

    6

    h-index

  2. arXiv (Cornell University)

    Repository · 5 publications · 84 citations

    5

    h-index

  3. Journal of Science Education and Technology

    3 publications · 168 citations

    3

    h-index

  4. ETS Research Report Series

    3 publications · 75 citations

    3

    h-index

  5. Journal of Educational Measurement

    3 publications · 149 citations

    3

    h-index

1–5