Intensive LLM use in educational contexts may lead to an accumulation of cognitive debt that weakens critical thinking and epistemic ownership¶

Claim · All claims
Evidence · 1 study · theoretical r2 · q1
Currency · newest study 2025 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person

Subclaims¶

q1 i? The article reports, citing recent research, that intensive use of LLMs like ChatGPT in education may produce cognitive debt, lower brain connectivity, reduced intellectual engagement, and difficulty citing one's own ideas. → Ronnie Videla 2025

Evidence¶

Ronnie Videla 2025¶

Ronnie Videla, Simon Penny, Wendy Ross. (2025). 'If you can't dance your program, you can't write it': Challenges and Implications for AI in Education. https://doi.org/10.1145/3759257

q1 · i? · theoretical · r2

The article attributes this to recent research on AI assistants for essay writing (Kosmyna et al., cited as [3]), reporting that LLM users exhibit "lower brain connectivity, reduced intellectual engagement, and difficulty citing their own ideas". No effect sizes are printed in this article.

"the intensive use of Large Language Models (LLMs) like ChatGPT in educational contexts may lead to an “accumulation of cognitive debt” that weakens critical thinking and epistemic ownership"

Discussion¶

Related Claims¶

• Reviewed literature reports risks of overreliance, AI errors in complex tasks, and students' uncritical acceptance of AI-generated outputs — related
• LLM-group participants reported low ownership of their essays and fell behind in their ability to quote from essays written minutes earlier — a narrower finding that bears on this claim
• Nursing students and faculty report concerns that AI use may weaken critical thinking, enable plagiarism and misinformation, and create unequal access — related
• Over four months and four sessions, LLM-group participants performed worse than Brain-only participants at neural, linguistic, and scoring levels — a narrower finding that bears on this claim
• Brain connectivity during essay writing systematically scales down with the amount of external support, with Brain-only strongest, Search Engine intermediate, and LLM weakest — a narrower finding that bears on this claim
• Unguarded answer-giving AI harmed unaided exam performance while a guarded version of the same model erased the harm (Bastani et al., 2025, as reported) — related
• AI assistance raises individual creative self-assessments but reduces collective diversity of novel content (reviewed finding) — related
• Unstructured LLM use risks cognitive offloading that displaces effortful thought and weakens argument construction — related
• Unstructured LLM use contributes to epistemic narrowing by privileging convergent outputs and dominant viewpoints — related
• Delegating intellectual work to generative AI risks eroding epistemic agency through reduced critical effort and cognitive offloading — related
• Documented GenAI-related challenges to active learning include cognitive debt, metacognitive laziness, unreflected acceptance, and overreliance on GenAI access — possibly the same claim (merge candidate)