Team formation instruments to enhance learner interactions in open learning environments

Abstract

Open learning environments, such as Massive Open Online Courses (MOOCs), often lack adequate learner collaboration opportunities; they are also plagued by high levels of drop-out. Introducing project-based learning (PBL) can enhance learner collaboration and motivation, but PBL does not easily scale up into MOOCS. To support definition and staffing of projects, team formation principles and algorithms are introduced to form productive, creative, or learning teams. These use data on the project and on learner knowledge, personality and preferences. A study was carried out to validate the principles and the algorithms. Students (n=168) and educational practitioners (n=56) provided the data. The principles for learning teams and productive teams were accepted, while the principle for creative teams could not. The algorithms were validated using team classifying tasks and team ranking tasks. The practitioners classify and rank small productive, creative and learning teams in accordance with the algorithms, thereby validating the algorithms outcomes. When team size grows, for practitioners, forming teams quickly becomes complex, as demonstrated by the increased divergence in ranking and classifying accuracy. Discussion of the results, conclusions, and directions for future research are provided.