When optimal team formation is a choice - Self-selection versus intelligent team formation strategies in a large online project-based course

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Abstract

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.

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Sankaranarayanan, S., Dashti, C., Bogart, C., Wang, X., Sakr, M., & Rosé, C. P. (2018). When optimal team formation is a choice - Self-selection versus intelligent team formation strategies in a large online project-based course. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10947 LNAI, pp. 518–531). Springer Verlag. https://doi.org/10.1007/978-3-319-93843-1_38

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