Comunicación acceptada al International Workshop on Learning Analytics Across Spaces (CrossLak) 2017.

Learning via collaboration has gained much success over past few decades given their learning benefits. Group composition has been seen as a relevant design element that contributes to the potential effectiveness of collaborative learning. To support practitioners in this context this paper addresses the problem of automatic group formation implementing policies related to well-known collaboration techniques and considering personal attributes in across-spaces contexts where multiple activities, places and tools are involved in a learning situation. Analytics of contextual and progress-in-activity information about learners presented as a summary would support practitioners to obtain a comprehensive knowledge about them to subsequently facilitate formation of effective collaborative groups to face forthcoming activities. The paper discusses a work in progress web based architecture of a group formation service to compute groupings which also assists in recommending grouping constraints via learning analytics which will facilitate practitioners in the adaptive set-up of the group formation design element across-spaces.

This research is partially funded by Spanish Ministry of Economy and Competitiveness under RESET (TIN2014-53199-C3-3-R) and the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502).