Claims

Qualitative narratives reveal temporal guilt patterns, authenticity concerns, and skill-atrophy fears among academics using AI

Claim · All claims
Evidence · 1 study · associational r1 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q2 i? Thematic analysis of open-ended responses identified a temporal guilt trajectory in approximately 35% of responses, authenticity concerns in 25%, and skill atrophy anxiety in 30%. → 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 · i? · associational · r1

Reflexive thematic analysis of open-ended survey responses (90 participants, 82.6%, provided at least one substantive response) found "a temporal guilt trajectory appeared in approximately 35% of responses, where initial guilt diminished with continued use"; authenticity concerns appeared in 25% and skill atrophy anxiety in 30%.

"A temporal guilt trajectory appeared in approximately 35% of responses, where initial guilt diminished with continued use, directly supporting the quantitative guilt paradox finding."

Discussion

The same narratives describe five ways academics reconcile AI use with academic values: tool framing, critical-thinking emphasis, boundary setting, transparency, and denying that reconciliation is needed.

Page metadata
Field Value
type claim
id ai-guilt-qualitative-themes
title Qualitative narratives reveal temporal guilt patterns, authenticity concerns, and skill-atrophy fears among academics using AI
description Qualitative narratives reveal temporal guilt patterns, authenticity concerns, and skill-atrophy fears among academics using AI
status review
evidence_strength weak
newest_evidence 2026
generated by process:wiki-ingest on 2026-10-11
trust unverified — no one has confirmed this page's content
sources 1 — diane-vassallo-2026

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