ASR usage frequency moderately predicts reflective behavior but does not significantly predict learning motivation¶

Claim · All claims
Evidence · 2 studies · 2 associational r1–r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? System usage frequency has a modest significant positive effect on reflective behavior. → Chen D 2026 q2 i? System usage frequency does not significantly predict learning motivation. → Chen D 2026 (2)

Evidence¶

Chen D 2026¶

Chen D, Zeng L, Ou W and Zhong S (2026) ASR technology in college English speaking instruction: the role of feedback internalization and metacognitive strategies. Front. Psychol. 17:1847238. https://doi.org/10.3389/fpsyg.2026.1847238

q2 · i? · associational · r1

SEM path analysis of the 325-response questionnaire survey. Frequency significantly, modestly predicted reflective behavior (p = 0.021); the article prints no standardized effect size.

"The path coefficient for system usage Frequency was 0.131 (SE = 0.057, CR = 2.303, p = 0.021), indicating that frequent system use can moderately stimulate reflective behavior."

Chen D 2026 (2)¶

Chen D, Zeng L, Ou W and Zhong S (2026) ASR technology in college English speaking instruction: the role of feedback internalization and metacognitive strategies. Front. Psychol. 17:1847238. https://doi.org/10.3389/fpsyg.2026.1847238

q2 · i? · associational · r2

Same SEM path analysis predicting learning motivation. The frequency path was non-significant (p = 0.402); no effect size is printed, so the null is not treated as equivalence.

"system usage frequency did not have a significant effect on learning motivation, with a path coefficient of only 0.048 (SE = 0.057, CR = 0.837, p = 0.402)."

Discussion¶

Related Claims¶

• ASR recognition accuracy enhances learning motivation but does not significantly predict reflective behavior — related
• In ASR-assisted college English speaking instruction, corrective feedback and reflection tasks each significantly predict reflective behavior — related
• Structural paths did not differ significantly across AI usage-frequency groups, though exploratory coefficients varied numerically — related
• Technology acceptance directly predicts reflective AI use and learning engagement in AI-supported programming (survey SEM, N=131) — related