Department of Mathematical Sciences
Rich, relevant, and immediate student feedback is a core ingredient supporting effective student learning. Feedback is particularly important for introductory computing courses where novice programmers are still learning the basic syntax and semantics of a programming language. Our project is aimed at detecting poor solutions to common problems, termed antipatterns, in student code and providing feedback that guides the student to better solutions. This paper discusses the first year of the project, specifically, the development of a Code Critiquer to detect antipatterns in student code and generate appropriate feedback. This important first step sets-up the project to advance knowledge about novice antipatterns and their detection. The use of these antipatterns and code critiquers in future classroom interventions will help the project improve our understanding of student learning, retention, and self-efficacy.
Proceedings of the 6th Educational Data Mining in Computer Science Education (CSEDM)
Ureel, L. C.,
Jarvie-Eggart, M. E.,
Work in Progress: The RICA Project: Rich, Immediate Critique of Antipatterns in Student Code.
Proceedings of the 6th Educational Data Mining in Computer Science Education (CSEDM), 75-81.
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/16803
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