Exploring how generative AI usage modes induce distinct learning pathways and specific creativity outcomes
Bibliographic Data
| ID | 22420097 |
|---|---|
| Authors | Zhang Yingying (Jinling Institute of Technology, corresponding author), Hui Zhang (0000-0002-8814-226X, City University), Zhang Hui (0000-0003-2667-4524, Hangzhou City University), Yao Chi (0000-0002-9018-3597, Zhejiang Gongshang University) |
| Year | 2026 |
| Pages | 1-15 |
| Publication date | 2026-07-10 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Interactive Learning Environments (JOURNAL) |
| Journal identifiers | ISSN: 1049-4820 • E-ISSN: 1744-5191 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/10494820.2026.2693963 |
| OpenAlex | W7167942934 |
| Language | EN |
| References cited | 23 |
The rapid diffusion of generative artificial intelligence (GenAI) is reshaping higher education and raising questions about its impact on student learning and creativity. This study investigates how AI usage modes (instructional and non-instructional) influence students’ learning pathways (exploitative and exploratory) and how these pathways affect creativity outcomes (incremental and radical creativity). The moderating role of perceived ease of use is also examined. Using a cross-sectional survey design, data were collected from 502 undergraduate students at a comprehensive university in Eastern China. Structural equation modeling was employed to test the proposed research model grounded in dual-process learning and creativity theories. The findings reveal that both instructional and non-instructional AI use significantly enhance exploitative and exploratory learning. Exploratory learning shows a stronger effect on radical creativity, whereas exploitative learning primarily supports incremental creativity. Perceived ease of use negatively moderates the relationships between GenAI use and exploitative learning, suggesting that overly accessible AI tools may reduce cognitive engagement in knowledge refinement and skill development. The findings provide new insights into AI-supported learning mechanisms and offer practical implications for integrating generative AI into higher education to foster student creativity.
Cognition · Creativity · Educational technology · Generative grammar · Generative model · AI in Service Interactions · Artificial Intelligence in Healthcare and Education · Creativity in Education and Neuroscience
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| Highly cited | No |
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