Both academic self-efficacy and AI self-efficacy are negatively associated with reported AI dependency, supporting a unified compensatory mechanism¶
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? Higher academic self-efficacy and higher AI self-efficacy each predict lower reported AI dependency when other predictors are controlled. → Hilit Maizel 2026
Evidence¶
Hilit Maizel 2026¶
Hilit Maizel, Maya Kalman Halevi, Miri Sarid, and Rony Tutian. (2026). Understanding Student Dependency on AI: The Role of AI Literacy, Academic Self-Efficacy, and Resource Management Strategies. Educ. Sci. 2026, 16, 1123. https://doi.org/10.3390/educsci16071123
q2 · i? · associational · r2
Regression analysis of the same 478-student survey. Academic self-efficacy was also negative (β = −0.197, p < 0.001). The authors read both as one compensatory mechanism: "AI self-efficacy was negatively associated with AI dependency ( β = −0.132, p = 0.016), paralleling the role of academic self-efficacy".
"AI self-efficacy was negatively associated with AI dependency ( β = −0.132, p = 0.016), paralleling the role of academic self-efficacy"
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¶
- Learners' task-specific self-efficacy beliefs predict whether they initiate, persist through, and recover from difficulty on academic tasks. — a broader claim this one bears on
- Academic self-efficacy is negatively associated with AI dependency among university students — a narrower finding that bears on this claim
- AI dependency mediates the relationship between academic self-efficacy and learning burnout — related
- GenAI can support learner agency through self-regulated learning, self-efficacy, and feedback literacy under appropriate conditions — related
- The eight-predictor model explains 27.3% of variance in AI dependency, and multidimensional AI literacy adds explanatory value over a single aggregate score
- AI dependency is positively associated with learning burnout among university students — related
- Effort regulation negatively predicts, and general academic help seeking positively predicts, reported AI dependency; time management is non-significant — related
- Hints that instruction is suboptimal trigger compensatory self-regulation, but self-management carries cognitive and motivational costs that deplete over time — related
- SR mechanisms across the four traditions intersect in redundant, complementary, and compensatory ways — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
self-efficacy-negatively-predicts-ai-dependency |
title |
Both academic self-efficacy and AI self-efficacy are negatively associated with reported AI dependency, supporting a unified compensatory mechanism |
description |
Both academic self-efficacy and AI self-efficacy are negatively associated with reported AI dependency, supporting a unified compensatory mechanism |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
source_checked |
2026-10-20 |
generated |
by process:wiki-ingest on 2026-10-12 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — hilit-maizel-2026 |
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