Ai-generated Assignment Detection

AI-Generated Assignment Detection is a scholarly methodological framework designed to identify academic submissions produced substantially by artificial intelligence systems, distinguishing it from general plagiarism detection by focusing specifically on outputs generated through large language models and similar generative AI technologies.

9

Publications

755

Citations

40

Authors

11

Institutions

Publications per year

2017–2026

9

Authors

40

  1. TP
    Travis P. Holt

    Auburn University, United States

    2 publications · 65 citations

    2

    h-index

  2. TM
    Tina M. Loraas

    Auburn University, United States

    2 publications · 65 citations

    2

    h-index

  3. JG
    J. Gregory Jenkins

    Virginia Tech, United States

    2 publications · 65 citations

    2

    h-index

  4. JP
    Jefferson P. Jones

    Auburn University, United States

    2 publications · 65 citations

    2

    h-index

  5. ME
    Mollie E. Mathis

    Auburn University, United States

    2 publications · 65 citations

    2

    h-index

1–5 of 40

Venues

  1. Journal of Applied Learning & Teaching

    JALT · 1 publications · 81 citations

    1

    h-index

  2. Cogent Education

    1 publications · 231 citations

    1

    h-index

  3. 1

    h-index

  4. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 1 publications · 37 citations

    1

    h-index

  5. Issues in Accounting Education

    1 publications · 48 citations

    1

    h-index

1–5