Students report higher engagement and motivation with the AI tutor, with comparable enjoyment and growth mindset¶

Claim · All claims
Evidence · 1 study · causal r2 · q3
Currency · newest study 2025 · checked against its sources 2026-10-17 (automated, 1 of 1 entry) · not reviewed by a person

Subclaims¶

q3 i? AI-group students agreed more strongly with engagement and motivation statements than in-class students; enjoyment and growth-mindset ratings did not differ significantly. → Kestin 2025

Evidence¶

Kestin 2025¶

Kestin, G., Miller, K., Klales, A., Milbourne, T. & Ponti, G. (2025). AI tutoring outperforms in-class active learning: an RCT introducing a novel research-based design in an authentic educational setting. Scientific Reports 15:17458. https://doi.org/10.1038/s41598-025-97652-6

q3 · i? · causal · r2

Five-point Likert perception ratings after each lesson in the crossover RCT (Fig. 3). Engagement means were 4.1 (AI) versus 3.6 (in-class); motivation was 3.4 versus 3.1, t(311) = -3.4, p < 0.001.

"the students in the AI group agreed more strongly (Mean = 4.1, SD = 0.98) than those in the in-class active learning group (Mean = 3.6, SD = 0.92), t(311) = − 4.5, p < 0.0001."

Discussion¶

Learner Variables¶

• Motivation — outcome: instruction changes it
• Interest — outcome: instruction changes it
• Achievement Emotions — outcome: instruction changes it

Related Claims¶

• GenAI-assisted education produces significantly higher learning motivation than non-GenAI approaches (g = 0.81) — the general claim this finding bears on, with the studies behind it
• Students learn more with a research-based AI tutor than with in-class active learning on identical content (post-test scores) — related
• In a randomised experiment, AI access raised students' enjoyment of learning (p = 0.063) with no statistically detectable effect on self-assessed knowledge or felt effectiveness — related
• Students with a stronger sense of belonging tend to show more academic self-confidence, motivation, engagement and achievement (review reports Pedler et al.) — related
• Learners invest more effort in tasks they perceive as interesting, personally important, or useful to their future goals. — related
• SupplyNet was rated significantly more immersive, motivating, and enjoyable than the baseline, with engagement showing the most pronounced difference. — related
• A carefully engineered AI tutor produced more than twice the learning of a strong active-learning class, in less time (Kestin et al., 2025, as reported) — a broader claim this one bears on
• KBD configuration produced no significant between-condition differences in system acceptance, intrinsic motivation, or subjective learning effectiveness in a single tutoring session — related