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Using Generative AI in Learning and Students' Innovative Behavior: A Dual-Path Examination Based on the UTAUT Model
1School of Economics and Management, North China University of Technology, No. 5 Jinyuanzhuang Road, Shijingshan District, Beijing 100144, China.
Behavioral Sciences (Basel, Switzerland)
|June 26, 2026
Summary
Generative artificial intelligence (GAI) use boosts college students' learning expectancies and innovative behaviors. However, a growth mindset can lessen GAI's indirect impact on innovation, suggesting nuanced effects.
Area of Science:
- Educational Technology
- Artificial Intelligence in Education
- Learning Sciences
Background:
- Generative artificial intelligence (GAI) is rapidly evolving, significantly impacting higher education.
- Understanding GAI's influence on student learning behaviors is crucial for pedagogical advancement.
- The Unified Theory of Acceptance and Use of Technology (UTAUT) provides a framework for analyzing technology adoption.
Purpose of the Study:
- To investigate the impact of Generative Artificial Intelligence (GAI) usage on college students' innovative learning behaviors.
- To examine the mediating roles of effort expectancy and performance expectancy in the GAI-learning relationship.
- To explore the moderating effect of a growth mindset on the pathway from GAI usage to innovative behavior.
Main Methods:
- A quantitative study involving 430 Chinese college students across various academic disciplines.
- Latent structural equation modeling (SEM) was employed to analyze the proposed moderated mediation model.
- Data collection focused on GAI usage, effort expectancy, performance expectancy, growth mindset, and innovative learning behaviors.
Main Results:
- GAI usage positively influences both effort expectancy and performance expectancy among college students.
- Both expectancies significantly foster students' innovative learning behaviors.
- Performance expectancy mediates the relationship between GAI use and innovative behavior, but this indirect effect is weakened by a growth mindset.
Conclusions:
- GAI tools can enhance student learning by increasing perceived effort and performance expectations, leading to greater innovation.
- A growth mindset, while generally beneficial, may moderate the positive indirect effects of GAI on innovative behavior.
- Findings offer insights for educators and institutions on leveraging GAI effectively while considering student mindsets.
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