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dc.contributor.authorSaqr, M
dc.contributor.authorFors, U
dc.contributor.authorTedre, M
dc.contributor.authorNouri, J
dc.date.accessioned2018-04-04T08:01:30Z
dc.date.available2018-04-04T08:01:30Z
dc.date.issued2018
dc.identifier.urihttps://erepo.uef.fi/handle/123456789/6211
dc.description.abstractTo ensure online collaborative learning meets the intended pedagogical goals (is actually collaborative and stimulates learning), mechanisms are needed for monitoring the efficiency of online collaboration. Various studies have indicated that social network analysis can be particularly effective in studying students’ interactions in online collaboration. However, research in education has only focused on the theoretical potential of using SNA, not on the actual benefits they achieved. This study investigated how social network analysis can be used to monitor online collaborative learning, find aspects in need of improvement, guide an informed intervention, and assess the efficacy of intervention using an experimental, observational repeated-measurement design in three courses over a full-term duration. Using a combination of SNA-based visual and quantitative analysis, we monitored three SNA constructs for each participant: the level of interactivity, the role, and position in information exchange, and the role played by each participant in the collaboration. On the group level, we monitored interactivity and group cohesion indicators. Our monitoring uncovered a non-collaborative teacher-centered pattern of interactions in the three studied courses as well as very few interactions among students, limited information exchange or negotiation, and very limited student networks dominated by the teacher. An intervention based on SNA-generated insights was designed. The intervention was structured into five actions: increasing awareness, promoting collaboration, improving the content, preparing teachers, and finally practicing with feedback. Evaluation of the intervention revealed that it has significantly enhanced student-student interactions and teacher-student interactions, as well as produced a collaborative pattern of interactions among most students and teachers. Since efficient and communicative activities are essential prerequisites for successful content discussion and for realizing the goals of collaboration, we suggest that our SNA-based approach will positively affect teaching and learning in many educational domains. Our study offers a proof-of-concept of what SNA can add to the current tools for monitoring and supporting teaching and learning in higher education.
dc.language.isoEN
dc.publisherPublic Library of Science (PLoS)
dc.relation.ispartofseriesPLOS ONE
dc.relation.urihttp://dx.doi.org/10.1371/journal.pone.0194777
dc.rightsCC BY 4.0
dc.titleHow social network analysis can be used to monitor online collaborative learning and guide an informed intervention
dc.description.versionpublished version
dc.contributor.departmentSchool of Computing, activities
uef.solecris.id53585283en
dc.type.publicationTieteelliset aikakauslehtiartikkelit
dc.relation.doi10.1371/journal.pone.0194777
dc.description.reviewstatuspeerReviewed
dc.relation.articlenumbere0194777
dc.relation.issn1932-6203
dc.relation.issue3
dc.relation.volume13
dc.rights.accesslevelopenAccess
dc.type.okmA1
uef.solecris.openaccessOpen access -julkaisukanavassa ilmestynyt julkaisu
dc.rights.copyright© Authors
dc.type.displayTypearticleen
dc.type.displayTypeartikkelifi
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/


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