All six predictor constructs correlate positively and significantly with ethical GenAI use, ranging from r = 0.370 to r = 0.507¶
Claim · All claims
Evidence · 1 study · associationalr2·q2·i3large
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 i3 Bivariate correlations between the six predictors and ethical GenAI use ranged from r = 0.370 (data protection) to r = 0.507 (academic integrity and transparency), all p < 0.001. → 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 · i3 · associational · r2
Pearson correlation analysis in the 980-student sample; the printed coefficients include r = 0.507 for academic integrity and transparency and r = 0.370 for data protection, privacy, and risk management, all p < 0.001. The strongest correlation r = 0.507 corresponds to a large effect (|r| ≥ .37), so impact is 3.
"All six predictor variables exhibited positive and statistically significant correlations with the ethical use of generative artificial intelligence (all p < 0.001): ethical and technical AI literacy (r = 0.449), academic integrity and transparency (r = 0.507), critical thinking and content verification (r = 0.477), self-regulation and academic responsibility (r = 0.437), data protection, privacy, and risk management (r = 0.370), and institutional guidance and ethics education (r = 0.396)."
Discussion¶
Related Claims¶
- Academic integrity and transparency is the strongest predictor of ethical GenAI use, followed by ethical and technical AI literacy and critical thinking — 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
- Ethical reasoning and reflective thinking are reported as the strongest predictors of sustainable and trustworthy AI use — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
bivariate-correlations-ethical-genai-predictors |
title |
All six predictor constructs correlate positively and significantly with ethical GenAI use, ranging from r = 0.370 to r = 0.507 |
description |
All six predictor constructs correlate positively and significantly with ethical GenAI use, ranging from r = 0.370 to r = 0.507 |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
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 |
Frontmatter is the page's machine-readable record — see the Schema & Guide.