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Automated alerts to avoid unfavourable interaction patterns in collaborative learning: Which design do students prefer?

dc.contributor.authorHawlitschek, Anja
dc.contributor.authorRudolf, Galina
dc.contributor.authorBerndt, Sarah
dc.contributor.authorZug, Sebastian
dc.contributor.editorRöpke, René
dc.contributor.editorSchroeder, Ulrik
dc.date.accessioned2023-08-30T09:09:36Z
dc.date.available2023-08-30T09:09:36Z
dc.date.issued2023
dc.description.abstractLonger 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.en
dc.identifier.doi10.18420/delfi2023-33
dc.identifier.isbn978-3-88579-732-6
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/42193
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof21. Fachtagung Bildungstechnologien (DELFI)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-322
dc.subjectautomated alerts
dc.subjectdesign
dc.subjectteamwork
dc.titleAutomated alerts to avoid unfavourable interaction patterns in collaborative learning: Which design do students prefer?en
dc.typeText/Conference Paper
gi.citation.endPage212
gi.citation.publisherPlaceBonn
gi.citation.startPage207
gi.conference.date11.-13. September 2023
gi.conference.locationAachen
gi.conference.reviewfull
gi.conference.sessiontitleLearning Analytics und Künstliche Intelligenz

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