Task completion with GenAI is a weak proxy for durable competence, with struggling learners at risk of an illusion of competence¶

Claim · All claims
Evidence · 1 study (2 entries) · review r2–r3 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Novice-programming observation found some students used GenAI as an accelerator while struggling students could experience compounded metacognitive difficulties and an illusion of competence. → Qusay H. Mahmoud 2026 q2 i? A review of 31 code-comprehension studies found tailored-explanation opportunities alongside inaccurate explanations and novice difficulties in prompting and evaluation. → Qusay H. Mahmoud 2026 (2)

Evidence¶

Qusay H. Mahmoud 2026¶

Qusay H. Mahmoud. (2026). Judgment-Centred Software Engineering Education: A Post-Hype Review and Framework for AI-Augmented Learning. Preprint, September 2026. https://arxiv.org/abs/2609.29473 doi:10.48550/arxiv.2609.29473

q2 · i? · review · r3

The review reports observational novice-programming research by Prather et al. in which "some students used GenAI as an accelerator" while struggling students risked "an illusion of competence", showing completion does not reveal understanding.

"Prather et al. [2024] observed that some students used GenAI as an accelerator while struggling students could experience compounded metacognitive difficulties and an illusion of competence."

Qusay H. Mahmoud 2026 (2)¶

Qusay H. Mahmoud. (2026). Judgment-Centred Software Engineering Education: A Post-Hype Review and Framework for AI-Augmented Learning. Preprint, September 2026. https://arxiv.org/abs/2609.29473

q2 · i? · review · r2

The review attributes to Qiao et al.'s systematic review of 31 code-comprehension studies both "genuine opportunities for tailored explanation" and inaccurate or unclear explanations, with novices struggling to prompt and to evaluate output.

"Qiao et al. [2026], reviewing 31 studies of GenAI for code comprehension, found genuine opportunities for tailored explanation alongside inaccurate or unclear explanations and difficulties for novices in both prompting and evaluation."

Discussion¶

Related Claims¶

• Access to AI advice roughly doubled reported confidence in answers in one experiment — the general claim this finding bears on, with the studies behind it
• Novice programmers' GenAI use produces a widening gap in outcomes by metacognitive skill (attributed to Prather et al.) — possibly the same claim (merge candidate)
• Some GenAI tools can inhibit productive struggle by reducing cognitive effort (metacognitive laziness) — related
• genAI-supported work can improve while the constructive processing underlying durable expertise erodes (the performance–metacognition dilemma) — a broader claim this one bears on
• Some AI tools can inhibit productive struggle by reducing cognitive effort when they automate processes students would otherwise reason through — related
• Learners Misjudge Retrieval Benefit — related
• Fluent Illusions Mislead Self Assessment — related
• Review-attributed evidence: user confidence in model answers exceeds model internal confidence, and explanation design narrows the gap — related
• Students attributed initial passive reliance on GenAI to prompting paralysis and an authority bias compounded by low academic self-efficacy — related
• Immediate LLM explanations risk bypassing the generative processes required for durable understanding — related
• Engagement remains an observable and evidential proxy for learning that AI has not broken, though it is not invulnerable — related
• 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. — related
• Explicit metacognition has severely limited access to underlying cognitive processes, and metacognitive reports can be inaccurate — related
• AI takeover of metacognitive monitoring may foster illusion of competence (untested conjecture) — related
• GenAI fluency corrupts metacognitive monitoring by producing cognitive ease that is misread as comprehension, weakening the regulation needed to keep offloading beneficial — related