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The Role of Generative Artificial Intelligence in Shaping University Students' Learning Behavior: A Mixed-Method
1Faculty of Artificial Intelligence Education, Central China Normal University, Wuhan 430079, China.
Behavioral Sciences (Basel, Switzerland)
|May 4, 2026
Summary
Generative AI (GenAI) significantly influences student learning behavior, with AI literacy acting as a key moderator. Universities can leverage these insights to better support student GenAI adoption.
Area of Science:
- Education Technology
- Artificial Intelligence in Education
- Student Behavior Analysis
Background:
- Generative AI (GenAI) is rapidly transforming educational landscapes.
- The specific impact of GenAI on student learning behavior and the role of AI literacy remain underexplored.
- Understanding these dynamics is crucial for effective educational strategies.
Purpose of the Study:
- To identify factors positively influencing student learning behavior in the context of GenAI.
- To investigate whether AI literacy moderates the relationship between GenAI and student learning behavior.
- To apply the COM-B model for a comprehensive analysis.
Main Methods:
- An online survey was administered to 438 participants.
- Covariance-based structural equation modeling (CB-SEM) was employed for quantitative analysis.
- Fuzzy-set qualitative comparative analysis (fsQCA) was used to identify causal configurations.
Main Results:
- Independent learning ability, receptive ability, learning environment, AI support equipment, and motivation (intrinsic/extrinsic) significantly impact learning behavior.
- AI literacy was confirmed as a significant moderator between GenAI and learning behavior.
- Seven distinct configurations of factors were identified as favorable for student learning behavior.
Conclusions:
- The study provides a nuanced understanding of how GenAI adoption is shaped by various factors and AI literacy.
- Findings offer actionable insights for universities to enhance student learning and GenAI integration.
- Recommendations focus on optimizing the learning environment and support systems for GenAI use.
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