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DBCollab: Automated feedback for face-to-face group database design

Abstract:

Developing effective teamwork and collaboration skills is regarded as a key graduate attribute for employability. As a result, higher education institutions are striving to help students foster these skills through authentic learning scenarios. Although face-to-face (f2f) group tasks are common in most classrooms, it is challenging to collect evidence about the group processes. As a result, to date, it is difficult to assess group tasks in ways other than through teachers' direct observations and students' self-reports, or by measuring the quality of their final product. However, there are other critical aspects of group-work that students need to receive feedback on, for example, interaction dynamics or the collaboration processes. This paper explores the potential of using interactive surfaces and sensors to track key indicators of group-work, to provide automated feedback about epistemic and social aspects. We conducted a pilot study in an authentic classroom, in the context of database design. The contributions of this paper are: 1) the operationalisation of the DBCollab tool as a means for supporting group database design and collecting multimodal traces of the activity using interactive surfaces and sensors; and 2) empirical evidence that points at the potential of presenting these traces to group members in order to provoke immediate and post-hoc productive reflection about their activity.