Ayaan M. Kazerouni
Stephen H. Edwards
T. Simin Hall
Clifford A. Shaffer
ABSTRACT
Good project management practices are hard to teach, and hard for novices to learn. Procrastination and bad project management practice occur frequently, and may interfere with successfully completing major programming projects in mid-level programming courses. Students often see these as abstract concepts that do not need to be actively applied in practice. Changing student behavior requires changing how this material is taught, and more importantly, changing how learning and practice are assessed. To provide proper assessment, we need to collect detailed data about how each student conducts their project development as they work on solutions. We present DevEventTracker, a system that continuously collects data from the Eclipse IDE as students program, giving us in-depth insight into students' programming habits. We report on data collected using DevEventTracker over the course of four programming projects involving 370 students in five sections of a Data Structures and Algorithms course over two semesters. These data support a new measure for how well students apply "incremental development" practices. We present a detailed description of the system, our methodology, and an initial evaluation of our ability to accurately assess incremental development on the part of the students. The goal is to help students improve their programming habits, with an emphasis on incremental development and time management.
- S. H. Edwards, J. Martin, and C. A. Shaffer. Examining classroom interventions to reduce procrastination. In Proceedings of the 2015 ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE '15, pages 254--259, New York, NY, USA, 2015. ACM. Google Scholar
Digital Library
- S. H. Edwards and M. A. Perez-Quinones. Web-cat: Automatically grading programming assignments. In Proceedings of the 13th Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE '08, pages 328--328, New York, NY, USA, 2008. ACM. Google ScholarDigital Library
- S. H. Edwards, J. Snyder, M. A. Pérez-Quiñones, A. Allevato, D. Kim, and B. Tretola. Comparing effective and ineffective behaviors of student programmers. In Proceedings of the Fifth International Workshop on Computing Education Research Workshop, ICER '09, pages 3--14, New York, NY, USA, 2009. ACM. Google ScholarDigital Library
- R. Hosseini, A. Vihavainen, and P. Brusilovsky. Exploring problem solving paths in a java programming course. In Psychology of Programming Interest Group Conference, PPIG 2014, pages 65--76, 2014.Google Scholar
- P. M. Johnson, H. Kou, J. M. Agustin, Q. Zhang, A. Kagawa, and T. Yamashita. Practical automated process and product metric collection and analysis in a classroom setting: Lessons learned from hackystat-uh. In Empirical Software Engineering, 2004. ISESE'04. Proceedings. 2004 International Symposium on, pages 136--144. IEEE, 2004. Google ScholarDigital Library
- J. Spacco, J. Strecker, D. Hovemeyer, and W. Pugh. Software repository mining with marmoset: an automated programming project snapshot and testing system. In ACM SIGSOFT Software Engineering Notes, volume 30, pages 1--5. ACM, 2005. Google ScholarDigital Library
- A. Vihavainen, T. Vikberg, M. Luukkainen, and M. Päartel. Scaffolding students' learning using test my code. In Proceedings of the 18th ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE '13, pages 117--122, New York, NY, USA, 2013. ACM. Google ScholarDigital Library
Index Terms
- DevEventTracker: Tracking Development Events to Assess Incremental Development and Procrastination
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