Introduction

Topic.

AI introduces an additional risk: automation bias. Users may overweight a system’s recommendation and under-check it against evidence, especially under time pressure or low accountability. In clinical decision-aid studies, participants often adjusted their judgements toward AI suggestions, even when those suggestions were imperfect (Gaube et al., 2021). A student revising an essay might replace a defensible claim with an AI-proposed sentence without verifying sources, thereby skipping evaluation. Such patterns support the concern that frequent, unstructured AI use undermines critical-thinking engagement unless courses build in safeguards.

To evaluate whether frequent use of generative AI weakens undergraduates’ critical thinking via cognitive offloading by synthesising evidence on offloading, attention and memory, and automation bias, and by identifying task and instructional conditions that mitigate harm.

Frequent, unstructured reliance on generative AI is likely to erode critical-thinking effort through offloading and automation-bias mechanisms; however, requirements for justification, source-checking, and counter-argument can reduce these risks while preserving efficiency.

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References (APA 7th)

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