Six predictor constructs jointly explain 44.0% of the variance in ethical GenAI use among university students, with all structural paths positive and significant¶
Claim · All claims
Evidence · 1 study · associationalr2·q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person
Subclaims¶
Reading the evidence codes
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q2 i? The six predictor constructs jointly explained 44.0% of the variance in ethical GenAI use (R2 = 0.440) in a confirmatory SEM model with excellent fit. → 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
Cross-sectional CB-SEM analysis of survey data from 980 students at the State University of Milagro. The confirmatory model showed "excellent fit (CFI = 0.998; SRMR = 0.021; RMSEA = 0.008)" and R2 = 0.440; no effect size per predictor was printed, so impact is null.
"The proposed model demonstrated an excellent fit (CFI = 0.998; SRMR = 0.021; RMSEA = 0.008). The six predictor constructs jointly explained 44.0% of the variance in ethical GenAI use (R2 = 0.440), and all structural paths were positive and statistically significant."
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
- All six predictor constructs correlate positively and significantly with ethical GenAI use, ranging from r = 0.370 to r = 0.507 — related
- Ethical reasoning and reflective thinking are reported as the strongest predictors of sustainable and trustworthy AI use — related
- In SEM, all three self-efficacy dimensions are positively associated with AI use, with Excellence strongest (β = .47), followed by Communication (β = .31) and Attention (β = .22); the model explains 43% of variance — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
six-predictors-explain-44-percent-ethical-genai-use |
title |
Six predictor constructs jointly explain 44.0% of the variance in ethical GenAI use among university students, with all structural paths positive and significant |
description |
Six predictor constructs jointly explain 44.0% of the variance in ethical GenAI use among university students, with all structural paths positive and significant |
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 |
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