How do Chinese undergraduates harness the potential of appraisal and emotions in generative AI-Powered learning? A multigroup analysis based on appraisal theory

IF 8.9 1区 教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Education Pub Date : 2025-01-13 DOI:10.1016/j.compedu.2025.105250
Chan Wang, Hongbiao Yin
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引用次数: 0

Abstract

The rapid development of generative AI (GenAI) has sparked increasing interest in its potential impact on student learning. Drawing on cognitive appraisal theory and AI device use acceptance (AIDUA) model, this study aims to investigate the complex dynamics of GenAI adoption among university undergraduates. Especially, our study examined how social, personal, and technological factors (social influence, hedonic motivation, and anthropomorphism) contributed to their cognitive appraisal and emotional experience with GenAI, analyzed how these cognitive-emotional responses affected their GenAI-powered learning productivity, and explored how this influential mechanism differs across various groups. We surveyed 2,026 Chinese undergraduates who had used GenAI in their studies. The findings indicated that the influence from others on using GenAI and hedonic motivation toward using GenAI were positively related to undergraduates’ appraisal of using GenAI as a challenge and negatively related to their view of it as a hindrance. Conversely, the anthropomorphic features of GenAI showed the opposite pattern. Undergraduates who viewed using GenAI as a challenge reported more positive emotions and demonstrated higher GenAI-powered learning productivity. Those who saw it as a hindrance experienced more negative emotions but showed no significant relationship with GenAI-powered learning productivity. Moreover, undergraduate students’ appraisal of using GenAI as a challenge or a hindrance and their emotional experiences played mediating roles in this influential process. Importantly, these relationships varied significantly across different student groups, highlighting the need for tailored approaches in GenAI integration. Our study provides insights for educators and policymakers on effectively integrating GenAI in higher education.
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来源期刊
Computers & Education
Computers & Education 工程技术-计算机:跨学科应用
CiteScore
27.10
自引率
5.80%
发文量
204
审稿时长
42 days
期刊介绍: Computers & Education seeks to advance understanding of how digital technology can improve education by publishing high-quality research that expands both theory and practice. The journal welcomes research papers exploring the pedagogical applications of digital technology, with a focus broad enough to appeal to the wider education community.
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