A Systematic Literature Review of the Opportunities and Advantages for AIGC (OpenAI ChatGPT, Copilot, Codex) in Programming Course
Chi In Chang, Wan Chong Choi, Iek Chong Choi
Abstract
This systematic literature review explored the opportunities and advantages of integrating Artificial Intelligence Generated Content (AIGC) tools like OpenAI's ChatGPT, Copilot, and Codex in programming education. From an initial pool of 1,173 papers, 24 were rigorously selected for detailed analysis. The findings highlighted the dominant use of ChatGPT, particularly versions 3/3.5 and 4, underscoring its effectiveness and accessibility. Python emerged as the most frequently studied language, followed by Java, C, R, and Scala. A notable research gap was identified in block-based programming languages and online/blended learning environments. Key opportunities and advantages identified included enhanced code review, where AIGC tools offer efficient and comprehensive assessments; personalized learning, with ChatGPT providing individualized feedback and improving student comprehension; and increased student engagement and motivation through interactive features. Additionally, AIGC tools significantly improved problem-solving and debugging support, effectively identifying and correcting coding errors. They also supported diverse learning styles by offering varied examples and solutions, facilitated innovative teaching strategies that improved educational outcomes, and reduced teacher workload by automating routine tasks. These insights demonstrated the transformative potential of AIGC tools in revolutionizing programming education.