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- Vol 4 RE: Chapter 25
ai literacyself-regulated learninggenerative artificial intelligencewriting performancestudent well-beingstructural equation modelingai ethicsJournal article Evidence summaryAt a glance
Shi, Liu, and Hu investigate associations among AI literacy, self-regulated learning, perceived writing performance, and well-being in generative-AI-supported higher education. Survey responses from 257 university students in China were analyzed with structural equation modeling.
Key ideas
Both AI literacy and self-regulated learning positively predicted students’ perceived writing performance, with self-regulation showing the stronger association. AI literacy also had a positive relationship with generative-AI-related well-being, and writing performance partially mediated that relationship. The model brings technological competence and strategic learning behavior together rather than treating tool knowledge as sufficient on its own. For teaching, the results support developing students’ ability to plan, monitor, and reflect while also teaching awareness, effective use, evaluation, and ethics of AI.
Why it matters
Important limits temper the findings: measures were self-reported, the writing-performance scale had modest reliability, the sample came from one national context, and the cross-sectional design cannot establish causal effects. The study therefore indicates relationships worth supporting and testing, not proof that AI literacy or AI use automatically improves writing or psychological well-being.
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Edition abbreviations
- TE
- Teacher Edition
- PE
- Practice Edition
- RE
- Research Edition
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