Thoughtless use of generative AI is negatively associated with undergraduates' self-directed learning in a cross-sectional survey model (β = −0.42)¶
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? TUGA significantly and negatively predicts SDL (β = −0.42, p < .001) in a PLS-SEM of 487 undergraduates. → Hui Zhao & Huijuan Gu 2026
Evidence¶
Hui Zhao & Huijuan Gu 2026¶
Hui Zhao & Huijuan Gu. (2026). Thoughtless use of generative artificial intelligence and college students’ self-directed learning: a multi-group SEM analysis of gender differences. Scientific Reports. https://doi.org/10.1038/s41598-026-54337-y
q2 · i? · associational · r1
Path analysis from the PLS-SEM bootstrapping results (Table 6) in the Results section. The TUGA→SDL path was significant and negative, with "β = − 0.42, t = 6.76, p < .001", supporting H1. No standardized effect size beyond β is printed.
"Among the direct predictors of SDL, MOV exhibited the strongest effect (β = 0.68, t = 11.63, p < .001), followed by the TUGA ( β = − 0.42, t = 6.76, p < .001) and SE ( β = 0.23, t = 3.93, p < .001)."
Discussion¶
Related Claims¶
- The effects of thoughtless GenAI use on motivation, self-efficacy, and self-directed learning differ significantly by gender — related
- Self-efficacy and motivation partially mediate the negative relationship between thoughtless GenAI use and self-directed learning, including a sequential SE→MOV pathway — related
- Thoughtless use of generative AI significantly and negatively predicts both self-efficacy and motivation — related
- Self-efficacy and motivation positively predict self-directed learning, with motivation the strongest direct predictor — related
- The TUGA, motivation, and self-efficacy jointly explain 75.3% of the variance in undergraduates’ self-directed learning — related
- Self-efficacy has a significant positive effect on motivation among undergraduates using generative AI — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
tuga-negative-direct-effect-sdl |
title |
Thoughtless use of generative AI is negatively associated with undergraduates' self-directed learning in a cross-sectional survey model (β = −0.42) |
description |
Thoughtless use of generative AI is negatively associated with undergraduates' self-directed learning in a cross-sectional survey model (β = −0.42) |
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 — hui-zhao-huijuan-gu-2026 |
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