Students given AI assistance in peer feedback tended to rely on the AI-generated feedback and struggled to perform the task when the assistance was removed¶

Claim · All claims
Evidence · 1 study · causal r? · 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? In a controlled study of AI assistance in peer feedback, students tended to rely on AI-generated feedback rather than actively learning from the process, and struggled when AI assistance was removed. → darvishi

Evidence¶

darvishi¶

Jacob, S., Miceli, H., & Schneider, H. (2026, May). Landscape of emerging technologies in higher education: A review. Digital Promise & The American Association of Colleges & Universities. https://doi.org/10.51388/20.500.12265/293

q2 · i? · causal · r?

The review reports, citing Darvishi et al. (2024), a controlled study in which "students tended to rely on the AI-generated feedback" and, once assistance was removed, "struggled to perform the task on their own." No effect size is printed.

"A controlled study by Darvishi et al. (2024) on AI assistance in peer feedback found that students tended to rely on the AI-generated feedback rather than actively learning from the process. When the AI assistance was removed, those students struggled to perform the task on their own."

Discussion¶

Related Claims¶

• Coaches cautioned that AI-generated feedback should be used formatively rather than for summative assessment because of AI's probabilistic nature — related
• Peer assessment improves academic performance by a small average amount relative to no assessment or to teacher assessment — related
• In two secondary-school writing studies, peer reviewers' own performance predicted how helpful their feedback was but not how accurately it identified problems — related
• Developers who used AI assistance scored 17% lower on a subsequent comprehension assessment than developers who completed the same tasks without AI, per the cited controlled study — related
• AI tools can enhance short-term task performance while undermining durable learning (the learning-performance paradox) — possibly the same claim (merge candidate)
• Reviewed literature reports risks of overreliance, AI errors in complex tasks, and students' uncritical acceptance of AI-generated outputs — related
• AI assistance that substitutes for learning activities may improve immediate performance while impeding long-term skill development — a broader claim this one bears on
• Overreliance on AWE may lower learners' critical thinking and creativity — related
• In the model, interventions that alter the feedback channel (verification visibility, social-proof damping) reduce overreliance and regret, while lowering verification cost alone does not lower regret — related
• Emerging evidence indicates generative AI tutors currently struggle to accurately infer student knowledge at the outset of an interaction or as the activity progresses — related
• AI-induced gains are not purely delegation: treated participants do not perform worse once AI is removed, and lower-education participants retain part of their gain, though a 0.200 SD gap re-emerges — reports the opposite
• Performance improvements from generative AI assistance diminished once the assistance was removed — possibly the same claim (merge candidate)
• Outsourcing productive struggle to AI risks cognitive debt, and reactive compliance-focused approaches are insufficient — a broader claim this one bears on
• High-school students given GPT-4 access solved more problems in the moment but performed worse than controls once the tool was removed (review attribution) — related
• Substituting tasks with generative AI may promote inclusion and free time for more demanding activities, but risks foundational-skill loss and presupposes prior knowledge — related
• Outcome feedback (mere knowledge of results) impedes learning of complex tasks in the multiple-cue probability learning paradigm — related