Computer-based Aptitude Testing

Computer-Based Aptitude Testing is a form of aptitude assessment that utilizes computerized platforms to administer, score, and interpret standardized tests designed to measure an individual's cognitive abilities, skills, or potential for learning, distinguishing it from traditional paper-and-pencil methods through its reliance on digital technology for adaptive testing, automated scoring, and immediate feedback.

47

Publications

1.9K

Citations

92

Authors

47

Institutions

Publications per year

2017–2026

4

Authors

92

  1. JK
    John Konvalina

    University of Nebraska at Omaha, United States

    3 publications · 161 citations

    3

    h-index

  2. LJ
    Larry J. Stephens

    University of Nebraska at Omaha, United States

    3 publications · 161 citations

    3

    h-index

  3. SW
    Stanley Wileman

    University of Nebraska at Omaha, United States

    3 publications · 161 citations

    3

    h-index

  4. JA
    Jo Ann Lee

    George Mason University, United States

    3 publications · 140 citations

    3

    h-index

  5. JB
    Jens Bennedsen

    Aarhus University, Denmark

    2 publications · 95 citations

    2

    h-index

1–5 of 92

Venues

  1. Educational and Psychological Measurement

    4 publications · 193 citations

    4

    h-index

  2. Communications of the ACM

    3 publications · 382 citations

    3

    h-index

  3. AEDS Journal

    3 publications · 106 citations

    3

    h-index

  4. ACM SIGCSE Bulletin

    3 publications · 162 citations

    3

    h-index

  5. Journal of Educational Computing Research

    2 publications · 28 citations

    2

    h-index

1–5