When Thinking Is Outsourced: Cognitive Offloading and the Heterogeneity of Critical Thinking Among Chinese University Students Using Generative Artificial Intelligence

Generative artificial intelligence (GAI) enables students to offload cognitive tasks to an external system, yet the consequences of such cognitive offloading for the development of critical thinking—a core dimension of human intelligence—remain underexplored. Drawing upon cognitive offloading theory and distributed cognition theory, this study investigates the heterogeneity of critical thinking outcomes among Chinese university students who use GAI, focusing on how different patterns of human–AI collaboration relate to cognitive autonomy relinquishment. A questionnaire survey was administered to 353 university students across multiple provinces in China. Cluster analysis and regression analysis were employed to identify distinct user profiles and to examine predictors of critical thinking gains and cognitive autonomy. Four distinct user profiles emerged, ranging from “simple Q&A users” (25.2%) to “critical co-thinkers” (15.6%). Learning motivation was the strongest predictor of both critical thinking gains (β = 0.42) and lower cognitive autonomy relinquishment (β = −0.35). Notably, offloading depth positively predicted cognitive autonomy relinquishment (β = 0.25), revealing a paradoxical pattern: sophisticated GAI use was associated with greater dependence. A “high depth–high dependence” subgroup (25.8%) was identified, disproportionately composed of female students and Information and Communication Technology (ICT) majors. The findings challenge the assumption that deeper GAI engagement automatically yields cognitive benefits. Because all constructs were measured through self-report, the findings are interpreted as reflecting students’ perceptions of their cognitive behaviors and abilities; the methodological implications of this design are discussed in detail. Educational interventions should prioritize metacognitive training over technical skill development to ensure that cognitive offloading enhances rather than undermines critical thinking.

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Publication Details

Journal
Journal of Intelligence
Published
2026-06-24
DOI
https://doi.org/10.3390/jintelligence14070116
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

When Thinking Is Outsourced: Cognitive Offloading and the Heterogeneity of Critical Thinking Among Chinese University Students Using Generative Artificial Intelligence

Xinyu Qi, S Si, Yong Qi, Jingming Xu
Journal of Intelligence
Artificial Intelligence in Healthcare and Education
article

When Thinking Is Outsourced: Cognitive Offloading and the Heterogeneity of Critical Thinking Among Chinese University Students Using Generative Artificial Intelligence

Xinyu Qi, S Si, Yong Qi, Jingming Xu
article en

Abstract

Generative artificial intelligence (GAI) enables students to offload cognitive tasks to an external system, yet the consequences of such cognitive offloading for the development of critical thinking—a core dimension of human intelligence—remain underexplored. Drawing upon cognitive offloading theory and distributed cognition theory, this study investigates the heterogeneity of critical thinking outcomes among Chinese university students who use GAI, focusing on how different patterns of human–AI collaboration relate to cognitive autonomy relinquishment. A questionnaire survey was administered to 353 university students across multiple provinces in China. Cluster analysis and regression analysis were employed to identify distinct user profiles and to examine predictors of critical thinking gains and cognitive autonomy. Four distinct user profiles emerged, ranging from “simple Q&A users” (25.2%) to “critical co-thinkers” (15.6%). Learning motivation was the strongest predictor of both critical thinking gains (β = 0.42) and lower cognitive autonomy relinquishment (β = −0.35). Notably, offloading depth positively predicted cognitive autonomy relinquishment (β = 0.25), revealing a paradoxical pattern: sophisticated GAI use was associated with greater dependence. A “high depth–high dependence” subgroup (25.8%) was identified, disproportionately composed of female students and Information and Communication Technology (ICT) majors. The findings challenge the assumption that deeper GAI engagement automatically yields cognitive benefits. Because all constructs were measured through self-report, the findings are interpreted as reflecting students’ perceptions of their cognitive behaviors and abilities; the methodological implications of this design are discussed in detail. Educational interventions should prioritize metacognitive training over technical skill development to ensure that cognitive offloading enhances rather than undermines critical thinking.

Journal of IntelligenceVol. 14(7)
Beijing University of Civil Engineering and Architecture (CN)
Openalex Percentile: Top 9%
Artificial Intelligence in Healthcare and Education
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