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Title: Collaborative Reflection “In the Flow” of Programming: Designing Effective Collaborative Learning Activities in Advanced Computer Science Contexts
Authors: Sankaranarayanan, Sreecharan
Ma, Lanmingqi
Kandimalla, Siddharth Reddy
Markevych, Ihor
Nguyen, Huy
Murray, R. Charles
Bogart, Christopher
Hilton, Michael
Sakr, Majd
Rosé, Carolyn Penstein
Keywords: CSCL
Issue Date: 2022
Publisher: International Society of the Learning Sciences
Citation: Sankaranarayanan, S., Ma, L., Kandimalla, S. R., Markevych, I., Nguyen, H., Murray, R. C., Bogart, C., Hilton, M., Sakr, M., & Rosé, C. P. (2022). Collaborative reflection “in the flow” of programming: Designing effective collaborative learning activities in advanced computer science contexts. In Weinberger, A. Chen, W., Hernández-Leo, D., & Chen, B. (Eds.), Proceedings of the 15th International Conference on Computer-Supported Collaborative Learning - CSCL 2022 (pp. 67-74). International Society of the Learning Sciences.
Abstract: Designing activities for maximizing collaborative learning in advanced computer science contexts is of broad interest. While programming exercises remain the dominant form of pedagogy here, prior work showed that collaborative reflection over worked examples is as good or even better for conceptual learning and future programming. This work used a “phased” design, with separate collaborative reflection and programming phases, and varied the time boundary between the two to determine their differential impact. A more effective design, however, could involve collaborative reflection prompted “in the flow” of programming, with benefits similar to self-explanation prompts interleaved into individual problem-solving. While total time-on-task is the same, this “interleaved” design might allow learners to spend a larger proportion of this time on reflection. Thus, this paper compares this novel interleaved approach to the phased design. We determine that interleaving increases the proportion of time available for reflection resulting in performance improvements on future programming.
Description: Long Paper
Appears in Collections:ISLS Annual Meeting 2022

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