Enhancing Programming Error Messages in Real Time with Generative AI
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Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 16 of its 37 references that are in the map. First posted on arXiv 12 Feb 2024.
Builds on
16 of 37 references.
References · 16
- 2022Automatic Generation of Programming Exercises and Code Explanations using Large Language Modelscited by 124
- 2022Programming Is Hard -- Or at Least It Used to Be: Educational Opportunities And Challenges of AI Code Generationcited by 97
- 2023Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programmingcited by 87
- 2023The Robots are Here: Navigating the Generative AI Revolution in Computing Educationcited by 85
- 2022Experiences from Using Code Explanations Generated by Large Language Models in a Web Software Development E-Bookcited by 84
- 2022Conversing with Copilot: Exploring Prompt Engineering for Solving CS1 Problems Using Natural Languagecited by 81
- 2023CodeHelp: Using Large Language Models with Guardrails for Scalable Support in Programming Classescited by 71
- 2022Using Large Language Models to Enhance Programming Error Messagescited by 67
- 2023Comparing Code Explanations Created by Students and Large Language Modelscited by 63
- 2023"It's Weird That it Knows What I Want": Usability and Interactions with Copilot for Novice Programmerscited by 62
- 2023Computing Education in the Era of Generative AIcited by 50
- 2023Exploring the Responses of Large Language Models to Beginner Programmers' Help Requestscited by 44
4 more
- 2023Thrilled by Your Progress! Large Language Models (GPT-4) No Longer Struggle to Pass Assessments in Higher Education Programming Coursescited by 38
- 2023Prompt Problems: A New Programming Exercise for the Generative AI Eracited by 31
- 2023Dcc --help: Generating Context-Aware Compiler Error Explanations with Large Language Modelscited by 11
- 2023Prompt Middleware: Mapping Prompts for Large Language Models to UI Affordancescited by 7
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Citing papers per year: 2024: 2; 2025: 1.
3 papers.