Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMuukkonen, Hanni
dc.contributor.authorDamşa, Crina
dc.contributor.authorvan Leeuwen, Anouschka
dc.contributor.authorJanssen, Jeroen
dc.contributor.authorRaković, Mladen
dc.contributor.authorGašević, Danijela
dc.contributor.authorGašević, Dragan
dc.contributor.authorEsterhazy, Rachelle
dc.contributor.authorNerland, Monika
dc.contributor.authorAraos, Andres
dc.contributor.authorHernández-Leo, Davinia
dc.identifier.citationMuukkonen, H., Damşa, C., van Leeuwen, A., Janssen, J., Raković, M., Gašević, D., Gašević, D., Esterhazy, R., Nerland, M., Araos, A., & Hernández-Leo, D. (2022). Contrasting analytical approaches to trace collaborative learning with knowledge objects. In Weinberger, A. Chen, W., Hernández-Leo, D., & Chen, B. (Eds.), Proceedings of the 15th International Conference on Computer-Supported Collaborative Learning - CSCL 2022 (pp. 509-516). International Society of the Learning Sciences.en
dc.description.abstractSocial, discursive and regulatory aspects of collaborative learning have been examined extensively. Yet, there is less research and systematic analysis on how the collaboratively constructed knowledge objects introduce and structure the conditions for collaborative processes and learning. In this symposium, we share and contrast methods and approaches to analyzing collaboration activities that involve digital knowledge objects being developed jointly (i.e., essays, posts in online discussions, versions of a product) in four different educational contexts in tertiary education. The four contributions, from Netherlands, Australia, Norway and Finland present a range of analytical approaches, collaboration analytics and qualitative interpretations of collaborative learning with knowledge objects. The contributions are part of an overarching effort to develop analytics-based approaches, frameworks and instruments that allow to systematically capture the complexities of the collaborative process, for further use in research and for supporting educational practice.en
dc.publisherInternational Society of the Learning Sciences
dc.relation.ispartofProceedings of the 15th International Conference on Computer-Supported Collaborative Learning - CSCL 2022, pp. 509-516
dc.titleContrasting Analytical Approaches to Trace Collaborative Learning With Knowledge Objectsen
Appears in Collections:ISLS Annual Meeting 2022

Files in This Item:
File SizeFormat 
CSCL2022_509-516.pdf434.08 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.