Frequent generative AI use for essay writing can foster metacognitive laziness, reducing intrinsic motivation and learning autonomy¶

Claim · All claims
Evidence · 1 study (2 entries) · theoretical r2 · q2
Currency · newest study 2025 · checked against its sources 2026-10-16 (automated, 2 of 2 entries) · not reviewed by a person

Subclaims¶

q2 i? A randomized controlled study indicated frequent generative AI use for argumentative essay writing can foster metacognitive laziness in undergraduates, who offload evaluative tasks to the tool. → Yan 2025 q2 i? Undergraduates who interacted frequently with generative-AI chatbots reported lower learning autonomy than students with infrequent chatbot interactions. → Yan 2025 (2)

Evidence¶

Yan 2025¶

Yan, L., Greiff, S., Lodge, J. M., & Gašević, D. (2025). Distinguishing performance gains from learning when using generative AI. Nature Reviews Psychology, 4, 435–436. https://doi.org/10.1038/s44159-025-00467-5

q2 · i? · theoretical · r2

The article reports, citing Fan et al., a randomized controlled study in which frequent generative AI use for argumentative essay writing fostered "metacognitive laziness": learners offloaded evaluative tasks such as reviewing criteria and assessing drafts against rubrics. No effect size is printed.

"A randomized controlled study indicated that frequent use of generative AI for argumentative essay writing tasks can foster “metacognitive laziness” in undergraduate students[4]."

Yan 2025 (2)¶

Yan, L., Greiff, S., Lodge, J. M., & Gašević, D. (2025). Distinguishing performance gains from learning when using generative AI. Nature Reviews Psychology, 4, 435–436. https://doi.org/10.1038/s44159-025-00467-5

q2 · i? · theoretical · r2

The article reports, citing Zhai et al., that frequent chatbot interaction for acquiring academic domain-specific knowledge was associated with "lower learning autonomy" relative to infrequent interaction. No effect size is printed.

"undergraduate learners who interacted frequently with generative-AI-powered chatbots for acquiring academic domain-specific knowledge reported lower learning autonomy relative to students who had infrequent chatbot interactions"

Discussion¶

Learner Variables¶

• Motivation — outcome: instruction changes it
• Self-Regulation — outcome: instruction changes it
• Metacognition — outcome: instruction changes it

Related Claims¶

• Evidence suggests over-reliance on generative AI may negatively affect students' self-regulated learning behaviors, potentially harming retention and transfer to novel contexts — the general claim this finding bears on, with the studies behind it
• GenAI use collapses SRL cycle transitions, with metacognitive activity restructuring around the tool — related
• As cited second-hand in an AI-literacy framework paper: ChatGPT use improved short-term essay scores but triggered metacognitive laziness with no significant knowledge-transfer gains — possibly the same claim (merge candidate)
• Dependent versus autonomous cognitive offloading to GenAI shows opposite motivational and cognitive outcome patterns — related
• Self-determination theory holds that autonomy support raises intrinsic motivation, and a meta-analysis finds expected tangible rewards undermine it — related
• The availability of AI assistants improved the quality of submitted admissions essays, particularly mechanical aspects and especially for international applicants — related
• Extended chatbot use produced dose-dependent increases in loneliness and emotional dependence alongside lower socialisation (review attribution) — related
• AI-assisted task performance can rise without corresponding gains in underlying knowledge, metacognitive processing, or independent reasoning — possibly the same claim (merge candidate)
• Purpose-built AI chatbot coaching is generally well received and supports short-term motivation and selected behavior change, but effects on sustained, meaningful outcomes are inconsistent — related
• Across studies, ChatGPT serves as a convenient tool assisting teachers, students and researchers in various tasks, with the consistent underlying motivation of seeking personal benefits and reducing academic burdens. — related
• GCLA does not bolster motivational aspects of SRL: traditional ChatGPT users showed higher intrinsic motivation and higher amotivation than GCLA users — related
• Learners perceive AI applications as useful for regulating their learning but not for regulating motivation — related
• Effective AI use positively influences sustainable learning performance — related
• LLMs can deliver scalable, personalized, interactive feedback almost instantly, reducing dependency on teacher availability and supporting self-regulated learning in large courses — reports the opposite
• Autonomy, meaningful purpose, and interest improve intrinsic motivation and deeper processing — related
• Metacognitive analysis activities were positively associated with transfer, but metacognitive activities showed no association with essay quality — related
• Generative AI support can foster self-regulated learning more effectively than traditional AI-based implementations — related
• Advanced learners may benefit from learner-controlled selection of learning tasks and levels of generality — related
• AI over-reliance can produce inversion effects, reducing cognitive processing depth and learning outcomes — a narrower finding that bears on this claim