This study analyzes the relation of group formation on outcomes of a 4-week online course for prospective students. Group formation was experimentally manipulated based on predefined criteria, personality traits conscientiousness and extraversion. As research questions, groups were considered advantageous if they were formed (a) heterogeneously in extraversion, and (b) homogeneously in conscientiousness. As a result, no uniform outcome was identified. Most variance could be explained on group level, but no significant main effect for experimental grouping was found. Significant interaction between both main effects hint that the results do not provide final answers, but guidance for further research.

Using digital tools for teaching allows to unburden teachers from organizational load and even provides qualitative improvements that are not achieved in traditional teaching. Algorithmically supported learning group formation aims at optimizing group composition so that each learner can achieve his or her maximum learning gain and learning groups stay stable and productive. Selecting and weighting relevant criteria for learning group formation is an interdisciplinary challenge. This contribution presents the status quo of algorithmic approaches and respective criteria for learning group formation. Based on this theoretical foundation, we describe an empirical study that investigated the influence of distributing two personality traits (conscientiousness and extraversion) either homogeneously or heterogeneously on subjective and objective measures of productivity, time investment, satisfaction, and performance. Results are compared to an earlier study that also included motivation and prior knowledge as criteria. We find both personality traits to enhance group satisfaction and performance when distributed heterogeneously.

No abstract