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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. 

Pursuing productivity, students often adopt a divide-and-conquer strategy that undercuts collaborative learning opportunities. In this study, we introduce a task structuring and role scaffolding paradigm to create opportunities for transactive exchange in such performance-oriented tasks and experimentally compare two prompting strategies -- one designed to create a focused discussion and another to intensify transactivity -- while controlling for time on task. We find significant learning gains of each strategy when used separately, but not in tandem. 

Prior research in Team-Based Massive Open Online Project courses (TB-MOOPs) has demonstrated both the importance of effective group composition and the potential for using automated methods for forming effective teams. Past work on automated team assignment has produced both spectacular failures and spectacular successes. In either case, different contexts pose particular challenges that may interfere with the applicability of approaches that have succeeded in other contexts. This paper reports on a case study investigating the applicability of an automated team assignment approach that has succeeded spectacularly in TB-MOOP contexts to a large online project-based course. The analysis offers both evidence of partial success of the paradigm as well as insights into areas for growth.