Cluster analysis identifies four tentative moral response profiles: Comfortable Adopters, Guilty Non-Users, Cautious Users, and Morally Distressed Avoiders¶

Claim · All claims
Evidence · 1 study · associational r1 · q2 · i3 large
Currency · newest study 2026 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person · recheck by 2031: baselines and conditions change

Subclaims¶

q2 i3 Exploratory k-means clustering of guilt and usage variables yielded a four-cluster solution differing significantly on AI Guilt Index (F(3,105) = 22.13, p < .001, η² = 0.39), research use (η² = 0.57) and teaching use (η² = 0.56). → Diane Vassallo 2026

Evidence¶

Diane Vassallo 2026¶

Diane Vassallo. (2026). The AI Guilt Complex: Moral Emotions and Ethical Dilemmas in Academic Technology Adoption. Journal of Academic Ethics (2026) 24:53. https://doi.org/10.1007/s10805-026-09726-3

q2 · i3 · associational · r1

Exploratory k-means cluster analysis in the 109-respondent survey produced four profiles: Comfortable Adopters (26.6%, lowest guilt, highest use), Guilty Non-Users (29.4%), Cautious Users (28.4%), and Morally Distressed Avoiders (15.6%, highest guilt, minimal use), with the ANOVA showing "significant differences between clusters on all variables" (η² = 0.39 on guilt).

"One-way ANOVA confirmed significant differences between clusters on all variables: AI Guilt Index ( F(3,10 5 ) = 2 2 .13, p <.001, η² = 0.39), Research Use (F(3,105) = 47.23, p <.001, η² = 0.57), and Teaching Use ( F(3,10 5 ) = 45. 2 0 , p <.001, η² = 0.56)."

Discussion¶

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