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dc.contributor.author조일현-
dc.contributor.author박연정-
dc.date.accessioned2017-04-07T01:04:14Z-
dc.date.available2017-04-07T01:04:14Z-
dc.date.issued2017-
dc.identifier.issn0266-4909-
dc.identifier.issn1365-2729-
dc.identifier.otherOAK-20148-
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/234942-
dc.description.abstractAn asynchronous online discussion (AOD) is one format of instructional methods that facilitate student-centered learning. In the wealth of AOD research, this study evaluated how students' behavior on AOD influences their academic outcomes. This case study compared the differential analytic methods including web log mining, social network analysis and content analysis which were selected by three interaction patterns: person to system (P2S), person to person (P2P) and person to content (P2C) interaction. Forty-three undergraduate students participated in an online discussion forum for 12weeks. Multiple regression analyses with the predictor variables from P2S, P2P and P2C and with a criterion variable of a final grade indicated several interesting findings. For P2S analysis, visits on board (VOB) had a significant variable to predict final grades. Also, the result of P2P analysis proved that in-degree and out-degree centrality predicted final grades. The P2C results based on cognitive presence represent that students' messages were mostly affiliated to the exploration and integration levels and also predicted the final grades. This study ultimately demonstrated the effectiveness of using multiple analytic methodologies to address and facilitate students' participation at AOD.-
dc.languageEnglish-
dc.publisherWILEY-
dc.subjectasynchronous online discussion-
dc.subjectcontent analysis-
dc.subjectdata-mining-
dc.subjectsocial network analysis (SNA)-
dc.titleThree interaction patterns on asynchronous online discussion behaviours: A methodological comparison-
dc.typeArticle-
dc.relation.issue2-
dc.relation.volume33-
dc.relation.indexSSCI-
dc.relation.indexSCOPUS-
dc.relation.startpage106-
dc.relation.lastpage122-
dc.relation.journaltitleJOURNAL OF COMPUTER ASSISTED LEARNING-
dc.identifier.doi10.1111/jcal.12168-
dc.identifier.wosidWOS:000395431100002-
dc.identifier.scopusid2-s2.0-85010699906-
dc.author.googleJo, I.-
dc.author.googlePark, Y.-
dc.author.googleLee, H.-
dc.contributor.scopusid조일현(26641169300)-
dc.contributor.scopusid박연정(56699008000)-
dc.date.modifydate20211117150924-
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연구기관 > 교육과학연구소 > Journal papers
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