Enhancing Programming Education with ChatGPT: A Case Study on Student Perceptions and Interactions in a Python Course
Boxaun Ma, Li Chen, Shin'ichi Konomi
TL;DR
This study investigates how first-year university students perceive and interact with ChatGPT in an eight-week Python programming course. Using mixed methods, the authors analyze pre/post-questionnaires and a corpus of student–ChatGPT dialogues to assess utility, benefits, and limitations, identifying rapid debugging, explanations, and code examples as key advantages. Results show strong positive reception and high intent to continue using ChatGPT, with usage spikes aligning to more challenging topics and nuanced concerns about dependency and accuracy. The work provides actionable guidance for integrating AI tutors into programming education and outlines avenues for future research on learning outcomes and educator perspectives.
Abstract
The integration of ChatGPT as a supportive tool in education, notably in programming courses, addresses the unique challenges of programming education by providing assistance with debugging, code generation, and explanations. Despite existing research validating ChatGPT's effectiveness, its application in university-level programming education and a detailed understanding of student interactions and perspectives remain limited. This paper explores ChatGPT's impact on learning in a Python programming course tailored for first-year students over eight weeks. By analyzing responses from surveys, open-ended questions, and student-ChatGPT dialog data, we aim to provide a comprehensive view of ChatGPT's utility and identify both its advantages and limitations as perceived by students. Our study uncovers a generally positive reception toward ChatGPT and offers insights into its role in enhancing the programming education experience. These findings contribute to the broader discourse on AI's potential in education, suggesting paths for future research and application.