Generative Artificial Intelligence-Based Gamified Programming Teaching System: Promoting Peer Competition and Learning Motivation

In traditional programming education, teachers typically design fixed questions and standard answers, manually grading the solutions submitted by students. This process not only requires significant time and effort from educators but may also fail to provide timely and personalized feedback due to l...

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Vydáno v:Engineering proceedings Ročník 98; číslo 1; s. 9
Hlavní autoři: You-Jen Chen, Ze-Ping Chen, Chien-Hung Lai, Chen-Wei Peng
Médium: Journal Article
Jazyk:angličtina
Vydáno: MDPI AG 01.06.2025
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ISSN:2673-4591
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Abstract In traditional programming education, teachers typically design fixed questions and standard answers, manually grading the solutions submitted by students. This process not only requires significant time and effort from educators but may also fail to provide timely and personalized feedback due to limited teaching resources. To alleviate these burdens and enhance teaching efficiency, this study leverages generative artificial intelligence (AI) technology to develop a system capable of automatically generating questions and grading answers. Students engage in programming exercises through a gamified approach, with the system providing instant feedback on their answers. Additionally, student performance is displayed via leaderboards, incorporating peer competition to boost learning motivation. According to a user survey, the gamified system demonstrates significant advantages: 56.67% of students found the system easy to use; 40% considered the system well-integrated; 60% indicated that they quickly mastered the system’s functionality, and over half (53.33%) believed that the leaderboard effectively enhanced their competitive awareness and motivation. These results suggest that the system not only reduces teachers’ workload but also increases student engagement and learning outcomes through gamified design.
AbstractList In traditional programming education, teachers typically design fixed questions and standard answers, manually grading the solutions submitted by students. This process not only requires significant time and effort from educators but may also fail to provide timely and personalized feedback due to limited teaching resources. To alleviate these burdens and enhance teaching efficiency, this study leverages generative artificial intelligence (AI) technology to develop a system capable of automatically generating questions and grading answers. Students engage in programming exercises through a gamified approach, with the system providing instant feedback on their answers. Additionally, student performance is displayed via leaderboards, incorporating peer competition to boost learning motivation. According to a user survey, the gamified system demonstrates significant advantages: 56.67% of students found the system easy to use; 40% considered the system well-integrated; 60% indicated that they quickly mastered the system’s functionality, and over half (53.33%) believed that the leaderboard effectively enhanced their competitive awareness and motivation. These results suggest that the system not only reduces teachers’ workload but also increases student engagement and learning outcomes through gamified design.
Author You-Jen Chen
Ze-Ping Chen
Chien-Hung Lai
Chen-Wei Peng
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SubjectTerms educational technology
game-based learning
generative AI
learning motivation
programming education
Title Generative Artificial Intelligence-Based Gamified Programming Teaching System: Promoting Peer Competition and Learning Motivation
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