Academic integrity and transparency is the strongest predictor of ethical GenAI use, followed by ethical and technical AI literacy and critical thinking¶
Claim · All claims
Evidence · 1 study · associationalr2·q2
Currency · newest study 2026 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · 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? Academic integrity and transparency exhibited the strongest standardized effect on ethical GenAI use (β = 0.231), with all six paths positive and significant. → Tabares-Cruz YB 2026
Evidence¶
Tabares-Cruz YB 2026¶
Tabares-Cruz YB, Cevallos-Sánchez HA, Arteaga-Pita IG, Rodriguez-Alava LA, Carreño-Mendoza AL, Cedeño-Barreto MdlÁ, Castro-Castillo GJ, Cobacango-Villavicencio JG and Moreira-Choez JS (2026) Predictors of the ethical use of generative artificial intelligence in higher education. Front. Educ. 11:1942426. https://doi.org/10.3389/feduc.2026.1942426
q2 · i? · associational · r2
Structural path estimates from the CB-SEM of 980 students; the article reports standardized β coefficients and states none of the 95% confidence intervals included zero. All six paths are positive and significant, with standardized β from 0.114 to 0.231; these are path coefficients in a cross-sectional survey model, not d-scale effects, so impact is coded i? rather than converted.
"Academic integrity and transparency exhibited the strongest effect (β = 0.231), followed by ethical and technical literacy (β = 0.181), critical thinking and content verification (β = 0.177), institutional guidance and ethical education (β = 0.159), self- regulation and academic responsibility (β = 0.119), and data protection, privacy, and risk management (β = 0.114)."
Discussion¶
Learner Variables¶
- Academic and Critical Literacy — predictor: learners who differ on it differ in outcomes
Related Claims¶
- All six predictor constructs correlate positively and significantly with ethical GenAI use, ranging from r = 0.370 to r = 0.507 — related
- GenAI literacy dimensions predict critical monitoring beyond traits, use frequency, and perceptions, with critical-ethical awareness the strongest predictor — related
- AI task scaffolding is positively associated with critical thinking and technical problem-solving among AI-using university students — related
- Critical-ethical awareness plays a dual role: it negatively predicts general GenAI reliance but positively predicts shortcut reliance — related
- Six predictor constructs jointly explain 44.0% of the variance in ethical GenAI use among university students, with all structural paths positive and significant — related
- AI literacy is strongly associated with students' critical AI evaluation in generative-AI-supported learning — related
- Ethical reasoning and reflective thinking are reported as the strongest predictors of sustainable and trustworthy AI use — reports the opposite
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
academic-integrity-strongest-predictor-ethical-genai |
title |
Academic integrity and transparency is the strongest predictor of ethical GenAI use, followed by ethical and technical AI literacy and critical thinking |
description |
Academic integrity and transparency is the strongest predictor of ethical GenAI use, followed by ethical and technical AI literacy and critical thinking |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
source_checked |
2026-10-20 |
generated |
by process:wiki-ingest on 2026-10-11 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — tabares-cruz-yb-2026 |
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