How Far Are We? The Triumphs and Trials of Generative AI in Learning Software Engineering

Conversational Generative AI (convo-genAI) is revolutionizing Software Engineering (SE) as engineers and academics embrace this technology in their work. However, there is a gap in understanding the current potential and pitfalls of this technology, specifically in supporting students in SE tasks. I...

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Veröffentlicht in:Proceedings / International Conference on Software Engineering S. 2270 - 2282
Hauptverfasser: Choudhuri, Rudrajit, Liu, Dylan, Steinmacher, Igor, Gerosa, Marco, Sarma, Anita
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: ACM 14.04.2024
Schlagworte:
Chatbots
ChatGPT
Empirical Study
Generative AI
Navigation
Productivity
Software Engineering
Task analysis
Uncertainty
ISSN:1558-1225
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Zusammenfassung:Conversational Generative AI (convo-genAI) is revolutionizing Software Engineering (SE) as engineers and academics embrace this technology in their work. However, there is a gap in understanding the current potential and pitfalls of this technology, specifically in supporting students in SE tasks. In this work, we evaluate through a between-subjects study (N=22) the effectiveness of ChatGPT, a convo-genAI platform, in assisting students in SE tasks. Our study did not find statistical differences in participants' productivity or self-efficacy when using ChatGPT as compared to traditional resources, but we found significantly increased frustration levels. Our study also revealed 5 distinct faults arising from violations of Human-AI interaction guidelines, which led to 7 different (negative) consequences on participants.
ISSN:1558-1225
DOI:10.1145/3597503.3639201