ArticleBehavioral sciences (Basel, Switzerland)2026
Using Generative AI in Learning and Students' Innovative Behavior: A Dual-Path Examination Based on the UTAUT Model.
Article in Behavioral sciences (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Exploring Middle School Students' Interactions and Perceptions of Using Generative AI in STEAM Learning Environments.Behavioral sciences (Basel, Switzerland) · 2026Article
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Abstract
The rapid development of generative artificial intelligence (GAI) has exerted extensive and far-reaching impacts on college students' learning, making it a topic worthy of in-depth investigation. This study aims to explore the impact of GAI usage on college students' innovative learning behaviors, drawing on the theoretical framework of the Unified Theory of Acceptance and Use of Technology (UTAUT). Specifically, the research explores the mediating mechanisms of effort expectancy and performance expectancy, as well as the moderating role of growth mindset in this process. Based on a sample of 430 Chinese college students recruited from diverse academic majors, the proposed moderated mediation model is empirically examined through latent structural equation modeling analysis. The results indicate that using GAI in learning significantly enhances students' perceptions of effort expectancy and performance expectancy, thereby fostering their subsequent innovative behavior. Notably, the findings reveal that while performance expectancy mediates the relationship between GAI usage and innovative behavior, a growth mindset weakens this indirect pathway. The practical implications of this study are also discussed for both students and universities.
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