Generative artificial intelligence (AI) tools like ChatGPT are becoming increasingly common in educational settings, especially in programming education. However, the impact of these tools on the learning process, student performance, and best practices for their integration remains underexplored. This study examines student experiences and interactions using ChatGPT in a beginner-level Python programming course through a combination of questionnaire responses and student-ChatGPT dialogue data analysis. The findings reveal a generally positive student reception toward ChatGPT, emphasizing its role in enhancing the programming education experience. Additionally, by clustering and analyzing the types of prompts students use, we identify four distinct patterns of ChatGPT usage and compare the performance outcomes associated with each pattern. In addition, we evaluated the quality of the ChatGPT-generated responses. This empirical research provides a deeper understanding of AI-enhanced programming education, offering valuable insights and suggesting pathways for future research and practical applications.

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Examining Student-ChatGPT Interactions in Programming Education

  • Boxuan Ma,
  • Li Chen,
  • Shin’ichi Konomi

摘要

Generative artificial intelligence (AI) tools like ChatGPT are becoming increasingly common in educational settings, especially in programming education. However, the impact of these tools on the learning process, student performance, and best practices for their integration remains underexplored. This study examines student experiences and interactions using ChatGPT in a beginner-level Python programming course through a combination of questionnaire responses and student-ChatGPT dialogue data analysis. The findings reveal a generally positive student reception toward ChatGPT, emphasizing its role in enhancing the programming education experience. Additionally, by clustering and analyzing the types of prompts students use, we identify four distinct patterns of ChatGPT usage and compare the performance outcomes associated with each pattern. In addition, we evaluated the quality of the ChatGPT-generated responses. This empirical research provides a deeper understanding of AI-enhanced programming education, offering valuable insights and suggesting pathways for future research and practical applications.