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https://dx.doi.org/10.48550/ar...
Article . 2025
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
DBLP
Preprint . 2025
Data sources: DBLP
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Exploring The Use of ChatGPT by Computer Science Students in Software Development: Applications, Ethical Considerations, and Insights for Engineering Education

Authors: Xu, D.; Martin, D.;

Exploring The Use of ChatGPT by Computer Science Students in Software Development: Applications, Ethical Considerations, and Insights for Engineering Education

Abstract

ChatGPT has been increasingly used in computer science, offering efficient support across software development tasks. While it helps students navigate programming challenges, its use also raises concerns about academic integrity and overreliance. Despite growing interest in this topic, prior research has largely relied on surveys, emphasizing trends over in-depth analysis of students' strategies and ethical awareness. This study complements existing work through a qualitative investigation of how computer science students in one UK institution strategically and ethically engage with ChatGPT in software development projects. Drawing on semi-structured interviews, it explores two key questions: How do computer science students ethically and strategically report using ChatGPT in software development projects? How do students understand and perceive the ethical issues associated with using ChatGPT in academic and professional contexts? Findings reveal a shift in students' learning models, moving from traditional "independent thinking-manual coding-iterative debugging" to "AI-assisted ideation-interactive programming-collaborative optimization." Importantly, many use ChatGPT conversationally to deepen understanding, while consciously reserving creative and high-level decision-making tasks for themselves. Students tend to cap ChatGPT's contribution to roughly 30%, and evaluate its output to mitigate overreliance. However, only a minority thoroughly analyze AI-generated code, raising concerns about reduced critical engagement. Meanwhile, students reject uncredited use, highlight risks such as privacy breaches and skill degradation, and call for clear usage guidelines set by their teachers. This research offers novel insights into the evolving learner-AI dynamic and highlights the need for explicit guidance to support responsible and pedagogically sound use of such tools.

Full paper oral presentation at the European Society for Engineering Education (SEFI) 2025 Annual Conference (September 2025)

Related Organizations
Keywords

Human-Computer Interaction, Software Engineering (cs.SE), FOS: Computer and information sciences, Large Language Models, ChatGPT, Computer Science Education, Software Engineering, Software Projects, Human-Computer Interaction (cs.HC)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green