Generative AI dependency on programming among university students: a scale development and validation study
Hao Zhang, Yanchao Yang, Ying Zhang, Baishuang Qiu, Jiongzhao Yang · 2026
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Description
Hao Zhang leads a five-author team with a 2026 project to build a questionnaire measuring how dependent university students become on generative AI for programming. No validated instrument existed for this reliance, which differs from general technology use. Drawing on reliance research and learning theory, the team drafted items covering three dimensions: cognitive, affective, and behavioural reliance. Convenience sampling gathered 1,295 students who had used generative AI while learning to program.
Item analysis first screened the questions, exploratory factor analysis then uncovered the underlying structure, and confirmatory factor analysis tested how well the three-factor model fit. Correlation checks supplied evidence that the scale relates to outside criteria as expected. The three-factor structure held up with sound reliability and validity. The authors offer the scale to researchers and teachers who want to gauge AI reliance in programming courses and keep students from leaning too heavily on the tools.
Catalog record
| CREATOR | Hao Zhang, Yanchao Yang, Ying Zhang, Baishuang Qiu, Jiongzhao Yang |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 47831 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |