Self-efficacy and motivation positively predict self-directed learning, with motivation the strongest direct predictor¶

Claim · All claims
Evidence · 1 study · associational r1 · q2
Currency · newest study 2026 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person

Subclaims¶

q2 i? MOV (β = 0.68) and SE (β = 0.23) each significantly and positively predict SDL. → 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

Same PLS-SEM path analysis (Table 6). MOV was the strongest direct predictor of SDL and SE was also positive and significant, supporting H3 and H6; the article states MOV "exhibited the strongest effect".

"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¶

Learner Variables¶

• Motivation — predictor: learners who differ on it differ in outcomes

Related Claims¶

• The effects of thoughtless GenAI use on motivation, self-efficacy, and self-directed learning differ significantly by gender — related
• The TUGA, motivation, and self-efficacy jointly explain 75.3% of the variance in undergraduates’ self-directed learning — 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
• Self-efficacy has a significant positive effect on motivation among undergraduates using generative AI — related
• Thoughtless use of generative AI significantly and negatively predicts both self-efficacy and motivation — related
• Thoughtless use of generative AI is negatively associated with undergraduates' self-directed learning in a cross-sectional survey model (β = −0.42) — related
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