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Background: The use of artificial intelligence-driven code completion tools, particularly the integration of GitHub Copilot with Visual Studio, has potential implications for Health Informatics education, particularly for students learning SQL and Python. Objectives: This study aims to evaluate the effectiveness of these tools in solving or assisting with the solution of problems found in Health Informatics coursework, ranging from simple to complex. Methods: The study assesses the performance of GitHub Copilot in generating code for Health Informatics coding assignments from graduate classes, with a focus on the impact of detailed explanations on the tool’s effectiveness. Results: Findings reveal that GitHub Copilot can generate correct code for straightforward problems. The correctness and effectiveness of solutions decrease with problem complexity, and the tool struggles with the most challenging problems, although performance on complex problems improves with more detailed explanations. Conclusions: The study underscores the relevance of these tools to programming in Health Informatics education but also highlights the need for critical evaluation by students. It concludes with a call for educators to adapt swiftly to this rapidly evolving technology.
Avramovic et al. (Fri,) studied this question.
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