A GPT-based Code Review System for Programming Language Learning
Project Overview
The document explores the integration of generative AI, specifically a GPT-4 based code review system, into programming language education for primary and secondary school students. This innovative system is designed to provide personalized and learner-friendly feedback, addressing the limitations of traditional code review methods while minimizing the potential for AI-assisted cheating. By incorporating strict correctness checks and optimizing response times, the system enhances the quality of feedback, ultimately leading to an improved learning experience for students. The findings suggest that such AI applications not only facilitate a more engaging and effective educational environment but also support educators in delivering tailored instruction that meets the diverse needs of learners. Overall, the use of generative AI in education is positioned as a transformative approach that fosters student understanding and skill development in programming.
Key Applications
GPT-4 based Code Review System
Context: Primary and secondary school students learning programming languages, specifically Python.
Implementation: The system was developed by collecting a dataset from an online judge system and was evaluated through usability tests with software education experts.
Outcomes: The system demonstrated improved accuracy in identifying errors, reduced response times for code reviews, minimized API call costs, and maintained high-quality feedback.
Challenges: AI-assist cheating concerns, managing diverse learner needs, and ensuring prompt accuracy.
Implementation Barriers
Technical Barrier
Concerns about AI-assist cheating when students use GPT models in programming classes.
Proposed Solutions: The system only provides comments on student-submitted code, minimizing direct solutions to encourage independent problem-solving.
Usability Barrier
Learners did not know how to use the system before utilizing it, impacting their experience.
Proposed Solutions: Add a how-to guide and instructional videos to help new users understand the system.
Project Team
Lee Dong-Kyu
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Lee Dong-Kyu
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai