Claims

AI dependency is positively associated with learning burnout among university students

Claim · All claims
Evidence · 1 study · associational r2 · q2 · i3 large
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 Higher AI dependency is associated with higher learning burnout (β = 0.451, p < 0.001), controlling for self-efficacy and teacher support. → 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 · i3 · associational · r2

Regression Model 3 in the cross-sectional survey, controlling for academic self-efficacy and teacher support. AI dependency was "significantly and positively associated with learning burnout" with β = 0.451, R2 = 0.203, f 2 = 0.255.

"AI dependency was significantly and positively associated with learning burnout ( β = 0.451, p < 0.001, 95% CI [0.392, 0.634]), explaining 20.3% of the variance in learning burnout ( R2 = 0.203, f 2 = 0.255)."

Discussion

Page metadata
Field Value
type claim
id ai-dependency-positively-associated-learning-burnout
title AI dependency is positively associated with learning burnout among university students
description AI dependency is positively associated with learning burnout among university students
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 — huang-q-2026

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