Collaborating with AI in Programming Education: A Qualitative Study of Student Experiences with a Chatbot-Supported Learning Environment

Document Type

Conference Proceeding

Source of Publication

Ichora 2026 8th International Congress on Human Computer Interaction Optimization and Robotic Applications Proceedings

Publication Date

5-21-2026

Abstract

Introductory programming education is often experienced as uncertain and demanding, especially during debugging and problem-solving. This study qualitatively explores students' experiences with an AI-supported collaborative coding environment that integrates shared code editing, peer discussion, and an LLM (GPT-4) providing concise hints rather than full solutions. After completing programming tasks, 102 undergraduate students shared open-ended reflections, which were analyzed thematically. Students largely described the environment as supportive, highlighting how immediate AI assistance within a shared workspace helped reduce frustration and maintain momentum. The chatbot was often perceived as a facilitator of discussion that clarified misunderstandings and complemented peer interaction. Participants also noted limitations, including occasional unclear responses, challenges in effective prompting, and minor interface issues. Overall, the findings suggest that AI can serve as a complementary scaffold in collaborative programming learning environments, shaping students' engagement and sensemaking during complex tasks.

ISBN

[9798331581503]

Publisher

IEEE

Disciplines

Computer Sciences | Education

Keywords

AI-supported learning, collaborative learning, computer programming education, computer science education, educational chatbots, large language models, peer interaction, qualitative study

Scopus ID

105042097583

Indexed in Scopus

yes

Open Access

no

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