Authors:
Cosima Schenk
1
and
Sven Strickroth
2
Affiliations:
1
Institute of Psychology, Goethe University Frankfurt, Frankfurt, Germany
;
2
LMU Munich, Munich, Germany
Keyword(s):
CSCL, Collaborative Learning, Student Learning, Group Composition, Self-Organised Collaborative Learning.
Abstract:
Learning in study groups offers students the opportunity to exchange ideas about lecture content, discuss questions, and network with others. However, little is known about how self-organised study groups (i. e., study groups that are organised and managed by students themselves) should ideally be composed to meet students’ needs. Following previous studies on group composition in collaborative learning, a requirement analysis was carried out, consisting of a focus group and an online survey. Three factors were identified as being particularly important to students: A similar level of conscientiousness, a similar attitude towards reliable attendance at meetings, and a similar preference for online meetings. Based on these results, a tool was implemented that uses a genetic algorithm for group formation. This prototype was tested and evaluated in a field study in two university courses. The field study suggests that there is a general interest in using such a tool. However, it seems t
o be a challenge for many students to establish contact and meet with the other members of the proposed study group. Possible reasons and solutions to this problem are discussed.
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