Using a Hierarchical Clustering Algorithm to Explore the Relationship Between Students' Program Debugging and Learning Performance

The programming course poses a significant challenge for students who are just starting to learn a programming language. Many beginners, upon encountering an "ERROR" message from the system, tend to give up on learning. However, there are also students who persist in overcoming difficulties, exerting continued effort to complete their code, and achieving better learning outcomes. Therefore, this study aimed to cluster students based on their behavior during debugging in a programming course. It sought to explore the impact and differences among students in terms of program success and course grades within different debugging frequency clusters.