The convenience and low opportunity cost of LLMs poses a risk of over-reliance, deskilling, and reduced judgment competence when learners outsource tasks that are essential learning opportunities.¶
Claim · All claims
Evidence · 1 study · theoreticalr2·q1
Currency · newest study 2024 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q1 i? Over-reliance on LLMs in educational contexts risks learners losing essential ingredients of expertise development, with associated risks of deskilling, automation bias, and reduced human autonomy and judgment competence. → Huber 2024
Evidence¶
Huber 2024¶
Huber, S. E., Kiili, K., Nebel, S., Ryan, R. M., Sailer, M., & Ninaus, M. (2024). Leveraging the Potential of Large Language Models in Education Through Playful and Game-Based Learning. Educational Psychology Review. https://doi.org/10.1007/s10648-024-09868-z
q1 · i? · theoretical · r2
Authors' theoretical argument in the section on interaction between LLM use and expertise development: outsourcing tasks that "represent essential learning opportunities" is problematic, citing prior literature. No data are reported in this piece.
"Over-reliance on LLMs in educational contexts is thus associated with some risk of losing out on essential ingredients for the development and preservation of expertise, potentially and inadvertently providing also a risk of deskilling"
Discussion¶
Related Claims¶
- Outsourcing productive struggle to AI risks cognitive debt, and reactive compliance-focused approaches are insufficient — possibly the same claim (merge candidate)
- Task completion with GenAI is a weak proxy for durable competence, with struggling learners at risk of an illusion of competence — related
- Reviewed literature reports risks of overreliance, AI errors in complex tasks, and students' uncritical acceptance of AI-generated outputs — related
- Task-level account of upskilling and the Triad of Skill Failure (deskilling, never-skilling, mis-skilling) with differing empirical support — related
- Over-reliance on GAI risks weakening teaching and social presence and depriving students of foundational skill development — related
- Well-designed games can promote persistence in practice and high-quality engagement, and when basic needs of autonomy, competence, and relatedness are met, learning becomes its own reward, reducing the temptation to outsource cognitive effort to LLMs. — related
- AI takeover of metacognitive monitoring may foster illusion of competence (untested conjecture) — a narrower finding that bears on this claim
- Documented GenAI-related challenges to active learning include cognitive debt, metacognitive laziness, unreflected acceptance, and overreliance on GenAI access — a broader claim this one bears on
- Before instruction, physics students show skepticism about LLM learning impacts, agreeing that over-reliance risks dependence, false confidence, and reduced conceptual understanding — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
llm-over-reliance-deskilling-risk |
title |
The convenience and low opportunity cost of LLMs poses a risk of over-reliance, deskilling, and reduced judgment competence when learners outsource tasks that are essential learning opportunities. |
description |
The convenience and low opportunity cost of LLMs poses a risk of over-reliance, deskilling, and reduced judgment competence when learners outsource tasks that are essential learning opportunities. |
status |
review |
evidence_strength |
weak |
newest_evidence |
2024 |
source_checked |
2026-10-20 |
generated |
by process:wiki-ingest on 2026-10-15 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — huber-2024 |
Frontmatter is the page's machine-readable record — see the Schema & Guide.