AI dependency mediates the relationship between academic self-efficacy and learning burnout¶
Claim · All claims
Evidence · 1 study · associationalr1·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? The indirect effect of academic self-efficacy on learning burnout through AI dependency is significant, with the direct effect becoming non-significant (full mediation pattern). → Huang Q 2026
Evidence¶
Huang Q 2026¶
Huang Q, Tu S, Lin J, Lu L and Lv C (2026). The dark side of AI in education: AI dependency as a mediator linking academic self-efficacy and teacher support to learning burnout among university students. Front. Psychol. 17:1889053. https://doi.org/10.3389/fpsyg.2026.1889053
q2 · i? · associational · r1
PROCESS Model 4 mediation with 5,000 bootstrap resamples on the 276-respondent survey. The indirect effect was "significant (indirect effect = −0.239"; the direct effect became non-significant, suggesting full mediation. Proportion mediated was 84.2% (Table 7).
"the indirect effect of academic self-efficacy on learning burnout through AI dependency was significant (indirect effect = −0.239, 95% CI [ −0.331, −0.154]), as the bootstrap confidence interval did not include zero."
Discussion¶
Learner Variables¶
- Motivation — predictor: learners who differ on it differ in outcomes
- Self-Efficacy — predictor: learners who differ on it differ in outcomes
Related Claims¶
- AI dependency mediates the relationship between teacher support and learning burnout — related
- AI dependency is positively associated with learning burnout among university students — related
- Academic self-efficacy is negatively associated with AI dependency among university students — related
- Metacognitive self-regulation mediates the relationships between all three AI interaction mechanisms and both higher-order outcomes — related
- Both academic self-efficacy and AI self-efficacy are negatively associated with reported AI dependency, supporting a unified compensatory mechanism — related
- Burnout is the strongest predictor of principals' motivation to quit and mediates other predictors — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
ai-dependency-mediates-self-efficacy-burnout |
title |
AI dependency mediates the relationship between academic self-efficacy and learning burnout |
description |
AI dependency mediates the relationship between academic self-efficacy and learning burnout |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
source_checked |
2026-10-20 |
generated |
by process:wiki-ingest on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — huang-q-2026 |
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