Group Formation in the Digital Age: Relevant Characteristics, Their Diagnosis, and Combination for Productive Collaboration

Published on Jan 1, 2019
· DOI :10.22318/CSCL2019.719
Dimitra Tsovaltzi13
Estimated H-index: 13
(Saarland University),
Armin Weinberger32
Estimated H-index: 32
(Saarland University)
+ 19 AuthorsJan van Aalst17
Estimated H-index: 17
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Abstract
This symposium tackles a central topic in CSCL, group formation for productive collaborative learning with / in digital media. Traditional research on group formation has investigated mostly separate learner characteristics as preconditions of learning. Combinations of different learner characteristics and of learner characteristics with collaborative processes have been less in focus. Considering such combinations is necessary to represent the complexity of group interactions and learning. Despite the digitalization of learning, there has been only few attempts to investigate the diagnostic information that mining learner texts and learning processes can contribute to addressing this complexity for optimal group formation, and to assign groups automatically based on multiple parameters simultaneously. This symposium brings together a multi-disciplinary and international consortium of researchers who all focus on group formation for computer supported collaborative learning. They complement each other in investigating different combinations of learner characteristics, learning processes and automatic techniques for optimal group formation.
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