From AI access to perceived learning capability in rural schools: a capital-capability account of pedagogically mediated use
Meili Li, Shuai Xu · 2026
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Description
Meili Li and Shuai Xu study why giving rural schools AI tools does not by itself make students feel more able to learn. Their 2026 paper covers six rural lower-secondary schools in China. It blends survey data from 486 students and 24 teachers with 32 interviews of students, teachers, parents, and school leaders, giving the interviews the lead role.
The authors frame the story with two theories: one about the resources families and schools hold, and one about what people can actually do with them. How often students used AI, and how much teachers guided that use, varied with family resources and home internet. Teacher guidance, planned study use of AI, and confidence in judging AI output tied most strongly to feeling capable. The interviews showed a routine that worked: try, get feedback, hear an explanation, revise. Access alone, the authors argue, converts to learning only through such teaching.
Catalog record
| CREATOR | Meili Li, Shuai Xu |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 58 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |