Enhancing Programming Error Messages in Real Time with Generative AI

February 12, 2024 Β· Declared Dead Β· πŸ› CHI Extended Abstracts

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Authors Bailey Kimmel, Austin Geisert, Lily Yaro, Brendan Gipson, Taylor Hotchkiss, Sidney Osae-Asante, Hunter Vaught, Grant Wininger, Chase Yamaguchi arXiv ID 2402.08072 Category cs.HC: Human-Computer Interaction Cross-listed cs.AI Citations 22 Venue CHI Extended Abstracts Last Checked 4 months ago
Abstract
Generative AI is changing the way that many disciplines are taught, including computer science. Researchers have shown that generative AI tools are capable of solving programming problems, writing extensive blocks of code, and explaining complex code in simple terms. Particular promise has been shown in using generative AI to enhance programming error messages. Both students and instructors have complained for decades that these messages are often cryptic and difficult to understand. Yet recent work has shown that students make fewer repeated errors when enhanced via GPT-4. We extend this work by implementing feedback from ChatGPT for all programs submitted to our automated assessment tool, Athene, providing help for compiler, run-time, and logic errors. Our results indicate that adding generative AI to an automated assessment tool does not necessarily make it better and that design of the interface matters greatly to the usability of the feedback that GPT-4 provided.
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