GPA band remains a significant negative predictor of active AI engagement, positive affect, perceived learning impact, and AI-related disengagement when controlling for age, gender, and year category¶
Claim · All claims
Evidence · 1 study · associationalr1·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? In sensitivity-check regression models, student-reported GPA band remained a significant negative predictor of active AI engagement (B = −0.133), positive affect (B = −0.156), perceived positive learning impact (B = −0.192), and AI-related disengagement (B = −0.029), with a small positive relationship for negative affect (B = 0.032). → Jason Zagami 2026
Evidence¶
Jason Zagami 2026¶
Jason Zagami. (2026). Guarded adoption of generative AI in higher education: high-achieving students, successful-student identity, and epistemic agency in a single-university mixed-methods survey. International Journal of Educational Technology in Higher Education 23:47. https://doi.org/10.1186/s41239-026-00625-6
q2 · i? · associational · r1
Regression sensitivity checks (Table 3) controlling for age group, gender, and year category, with GPA band entered as an ordinal predictor coded 1–9. All printed B coefficients were significant (p < 0.001 for four outcomes; p = 0.026 for negative affect); no standardised effect sizes are printed.
"student-reported GPA band remained a significant negative predictor of active AI engagement, positive affect towards AI, perceived positive learning impact, and AI-related disengagement. A small positive relationship remained for negative affect."
Discussion¶
Related Claims¶
- Exploratory stage-of-study analyses: undergraduate year level is positively associated with AI-related disengagement, and the GPA-band pattern is stronger in postgraduate/research students for active engagement and perceived learning impact — related
- High-achieving students less often endorse AI-supported autonomy, effective learning, and active engagement, and more often agree that reliance on AI hinders critical thinking and independent problem solving — a narrower finding that bears on this claim
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
regression-gpa-predictor-controls |
title |
GPA band remains a significant negative predictor of active AI engagement, positive affect, perceived learning impact, and AI-related disengagement when controlling for age, gender, and year category |
description |
GPA band remains a significant negative predictor of active AI engagement, positive affect, perceived learning impact, and AI-related disengagement when controlling for age, gender, and year category |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
generated |
by process:wiki-ingest on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — jason-zagami-2026 |
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