Models of Mastery Learning for Computing Education

Publication date

2025-02-18

Authors

Szabo, Claudia
Parker, Miranda C.
Friend, Michelle
Jeuring, JohanISNI 0000000110063265
Kohn, Tobias
Malmi, Lauri
Sheard, Judithe

Editors

Advisors

Supervisors

Document Type

Part of book
Open Access logo

License

cc_by

Abstract

The application of mastery learning, where students progress through their learning in a self-paced manner until they have mastered specific concepts, is considered appealing for teaching introductory programming courses. Despite its growing popularity in computing and its extensive use in other disciplines, there is no overview of the design of courses that use mastery learning. In this position paper, we present an overview of five mastery learning models and discuss examples of how these can be applied in practice, both in foundational programming as well as more advanced courses. Our analysis focuses on the student progression through the course, the assessment structure, and the support for self-paced learning, including for struggling students. This work provides a greater understanding of mastery learning and its application in a computing education context.

Keywords

competency-based learning, mastery learning, models of instruction, Computer Science (miscellaneous), Education

Citation

Szabo, C, Parker, M C, Friend, M, Jeuring, J, Kohn, T, Malmi, L & Sheard, J 2025, Models of Mastery Learning for Computing Education. in SIGCSE TS 2025 - Proceedings of the 56th ACM Technical Symposium on Computer Science Education. SIGCSE TS 2025 - Proceedings of the 56th ACM Technical Symposium on Computer Science Education, vol. 1, Association for Computing Machinery, pp. 1092-1098, 56th Annual SIGCSE Technical Symposium on Computer Science Education, SIGCSE TS 2025, Pittsburgh, United States, 26/02/25. https://doi.org/10.1145/3641554.3701868, conference