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Impact of Generative AI-assisted programming on the computational thinking of high school students
Rong Guo1, Guian Li2, Haifei Miao1
1Faculty of Education, Shaanxi Normal University, Xi'an, China.
Frontiers in Psychology
|April 9, 2026
Summary
Generative AI significantly improved high-school students' computational thinking, especially in algorithmic thinking and abstraction. This AI-assisted programming approach offers personalized learning and boosts enthusiasm for coding education.
Area of Science:
- Computer Science Education
- Artificial Intelligence in Education
- Cognitive Science
Background:
- Generative AI shows promise in education, but its impact on programming education requires further study.
- Few empirical studies explore Generative AI's role in developing computational thinking skills.
Purpose of the Study:
- To investigate the effect of Generative AI-assisted programming on high-school students' computational thinking.
- To analyze changes in computational thinking, algorithmic thinking, and abstraction.
Main Methods:
- Convergent parallel mixed-methods design with 83 high-school students.
- Quantitative analysis of computational thinking changes.
- Qualitative interviews to elaborate on findings.
Main Results:
- Significant improvement in computational thinking (p < 0.01) in the experimental group.
- Substantial gains in algorithmic thinking and abstraction (p < 0.01).
- Qualitative data revealed AI's role in personalized scaffolding for cognitive development.
Conclusions:
- Generative AI-assisted programming enhances personalized learning and student engagement in programming.
- This learning strategy shows potential for application in similar educational contexts.
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