Exploring the Potential of Generative AI Use in Python Game Development Instruction for Adolescents

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While adolescents perceive generative AI as highly useful in Python game development instruction and show positive trends in learning satisfaction and achievement perception, these improvements are not statistically significant compared to teacher-led instruction alone. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Soon-Nam Lee; Young-Suk Chung

doi:10.9708/jksci.2026.31.05.325

May 31, 2026Journal of the Korea Society of Computer and Information

Exploring the Potential of Generative AI Use in Python Game Development Instruction for Adolescents

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Key Points

This research aims to explore the potential of generative AI in enhancing programming achievement and learning satisfaction among adolescents in Python game development classes.
Comparative design applied with 11 adolescents aged 13-16 years
Participants experienced teacher-led and AI-assisted conditions in two projects sequentially
Data collected through surveys, open responses, observations, and prompt logs, analyzed using descriptive statistics and Wilcoxon signed-rank test.
No statistically significant differences were found in programming achievement and learning satisfaction between conditions
Positive responses towards AI usefulness were noted (M=4.27–4.45)
Findings may reflect exploratory trends rather than direct effects due to small sample size and fixed project order.

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Implication

Examines the effects of generative AI on programming achievement in adolescents, suggesting potential benefits.

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Lee et al. (2026) studied this question.

synapsesocial.com/papers/6a23baa771a5da9775e765af https://doi.org/10.9708/jksci.2026.31.05.325

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Exploring the Potential of Generative AI Use in Python Game Development Instruction for Adolescents

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Exploring the Potential of Generative AI Use in Python Game Development Instruction for Adolescents

Key Points

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