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Licensed Unlicensed Requires Authentication Published by Oldenbourg Wissenschaftsverlag March 27, 2018

Who is the Perfect Match?

Effects of Algorithmic Learning Group Formation Using Personality Traits

Henrik Bellhäuser ORCID logo, Johannes Konert, Adrienne Müller and René Röpke
From the journal i-com


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.


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Published Online: 2018-03-27
Published in Print: 2018-04-25

© 2018 Walter de Gruyter GmbH, Berlin/Boston

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