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

• URL: http://arxiv.org/abs/2312.11719v1
• Date: Mon, 18 Dec 2023 21:38:00 GMT
• Title: How Far Are We? The Triumphs and Trials of Generative AI in Learning Software Engineering
• Authors: Rudrajit Choudhuri, Dylan Liu, Igor Steinmacher, Marco Gerosa, Anita Sarma
• Abstract summary: We evaluate the effectiveness of ChatGPT, a convo-genAI platform, in assisting students in Software Engineering tasks. Our study did not find statistical differences in participants' productivity or self-efficacy when using ChatGPT as compared to traditional resources. Our study also revealed 5 distinct faults arising from violations of Human-AI interaction guidelines, which led to 7 different (negative) consequences on participants.
• Score: 16.5141990552784
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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