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Automated alerts to avoid unfavourable interaction patterns in collaborative learning: Which design do students prefer?
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2023
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Gesellschaft für Informatik e.V.
Zusammenfassung
Longer phases without interaction or a later start into task processing are often related to problems in collaborative learning. Teams that exhibit such patterns of teamwork are more likely to underperform or fail in collaboration. Automated alerts are a way to contact such student teams, make them aware of unfavourable interaction patterns and offer support. An adequate design of such alerts is a basis for their efficacy. In this study, we investigated students’ (N = 39) attitudes towards alerts and ana-lysed which types of automated alerts students prefer. Based on findings of previous studies, we have designed three types of alerts – “impersonal-with response”, “personal-with response” and “information only”. Students in our study mainly preferred “personal-with response”. However, in-depth investigation revealed restrictions. Based on results, we give recommendations for the design of automated alerts.