Higher baseline autonomy and higher baseline competence frustration predict greater perceived relief from competence frustration after AI chatbot use, while higher baseline personal agency predicts less¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r2 · q2
Currency · newest study 2026 · checked against its sources 2026-10-20 (automated, 2 of 2 entries) · not reviewed by a person

Subclaims¶

q2 i? Baseline autonomy (β = .479) and baseline competence frustration (β = .291) positively predict perceived reduction in competence frustration. → Kevin Zhongyang Shao 2026 q2 i? Higher baseline personal agency is associated with lower perceived relief from competence frustration (β = −.335). → Kevin Zhongyang Shao 2026 (2)

Evidence¶

Kevin Zhongyang Shao 2026¶

Kevin Zhongyang Shao, Denise Wilson, Yale Quan, Sep Makhsous. (2026). Designing Needs- and Attention-Aware AI Learning Tools for Engineering Education: Insights from Psychological Outcomes. arXiv. https://arxiv.org/abs/2607.26338 doi:10.48550/arxiv.2607.26338

q2 · i? · associational · r2

Structural equation model (robust maximum likelihood, lavaan) of the 206-student survey, controlling for inattention and demographics. "higher baseline autonomy (β=. 479,p<. 001) and higher baseline competence frustration (β=. 291,p<. 001) were associated with greater perceived reduction in competence frustration."

"Students with higher baseline autonomy (𝛽=. 479,𝑝<. 001) and higher baseline competence frustration (𝛽=. 291,𝑝<. 001) were associated with greater perceived reduction in competence frustration following AI use."

Kevin Zhongyang Shao 2026 (2)¶

Kevin Zhongyang Shao, Denise Wilson, Yale Quan, Sep Makhsous. (2026). Designing Needs- and Attention-Aware AI Learning Tools for Engineering Education: Insights from Psychological Outcomes. arXiv. https://arxiv.org/abs/2607.26338

q2 · i? · associational · r2

Same SEM of the 206-student survey. "higher baseline personal agency was associated with lower perceived relief from competence frustration when using AI (β=−. 335,p<. 001)" and higher inattention with greater relief (β=. 290, p<.001).

"In contrast, higher baseline personal agency was associated with lower perceived relief from competence frustration when using AI (𝛽=−. 335,𝑝<. 001), and higher inattention was associated with greater perceived relief from competence frustration (𝛽=. 290,𝑝<. 001)."

Discussion¶

Learner Variables¶

• Affect Regulation — outcome: instruction changes it

Related Claims¶

• Engineering students perceive AI chatbot benefits as strongest for relief from competence frustration, moderate for autonomy, and weakest for relatedness — related
• Baseline motivational states shape perceived AI benefits more than demographics, with female-coded gender the only significant demographic effect (lower perceived competence relief) — a narrower finding that bears on this claim
• Inattention moderates how baseline competence frustration and baseline autonomy translate into perceived AI benefits, weakening both positive associations — related
• Students with higher baseline relatedness satisfaction perceive less additional relatedness support from AI chatbot use — related
• Chatbot support systems in online learning are associated with higher learner satisfaction and engagement when perceived as useful — related