Academic AI Use Ethics
EducationReliability: alpha 0.893 sample items
About this scale
A multi-item measure of student attitudes toward ethical use of AI in academic work — disclosure, original thought, plagiarism boundaries, and instructor permission.
Sample item(s)
“Using AI to write a paper without disclosure is a form of plagiarism”
“I should ask my instructor before using AI on assignments”
“Submitting AI-generated work as my own is wrong”
Reliability
Reported internal consistency: alpha 0.89. As a rule of thumb, Cronbach’s α ≥ .70 is considered acceptable, ≥ .80 good, and ≥ .90 excellent for established measures.
Notes
Highly relevant for higher-education academic-integrity research post-2022.
Source & citation
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024): Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, Vol. 61, No. 2, pp. 228–239.
Cotton, Cotton & Shipway (2024): Chatting and cheating. IETI, 61(2), 228–239.
Source. Scale details are summarised from the publication cited above. Always consult the original source for the full item set, scoring, and permission to use.
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