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Book Chapter: Micro-Analysis of Collaborative Processes that Facilitate Productive Online Discussions: Statistical Discourse Analyses in Three Studies

TitleMicro-Analysis of Collaborative Processes that Facilitate Productive Online Discussions: Statistical Discourse Analyses in Three Studies
Authors
PublisherInformation Science Reference
Citation
Micro-Analysis of Collaborative Processes that Facilitate Productive Online Discussions: Statistical Discourse Analyses in Three Studies. In Barbera, E & Reimann, P (Eds.), Assessment and Evaluation of Time Factors in Online Teaching and Learning, p. 232-263. Hershey, PA: Information Science Reference How to Cite?
AbstractStudying time with statistics can help shed light on cause-effect relationships in large online data sets and address three sets of research questions regarding sequences, time periods, and influences of phenomena across different time-scales. As such studies face many analytic difficulties (related to the data, dependent variables, or explanatory variables), this chapter shows how the method of Statistical Discourse Analysis (SDA) addresses each of them. Then, the authors apply SDA to three online data sets: (a) 183 participants’ 894 messages in a mathematics forum without teacher moderation, (b) 17 students’ 1,330 messages in a 13-week graduate course, and (c) 21 students’ 252 messages across 8 weeks during a hybrid university course. Findings include (a) significant relationships between non-adjacent messages, (b) explanatory models of statistically-identified pivotal messages that distinguish distinct time periods, and (c) effects of larger phenomena on smaller phenomena (e.g., gender on message characteristics) and vice-versa (extensive summary on time periods).
Persistent Identifierhttp://hdl.handle.net/10722/205341
ISBN
Series/Report no.Research essentials

 

DC FieldValueLanguage
dc.contributor.authorChiu, Men_US
dc.contributor.authorMolenaar, Ien_US
dc.contributor.authorChen, Gen_US
dc.contributor.authorWise, Aen_US
dc.contributor.authorFujita, Nen_US
dc.date.accessioned2014-09-20T02:25:24Z-
dc.date.available2014-09-20T02:25:24Z-
dc.identifier.citationMicro-Analysis of Collaborative Processes that Facilitate Productive Online Discussions: Statistical Discourse Analyses in Three Studies. In Barbera, E & Reimann, P (Eds.), Assessment and Evaluation of Time Factors in Online Teaching and Learning, p. 232-263. Hershey, PA: Information Science Referenceen_US
dc.identifier.isbn9781466646513-
dc.identifier.urihttp://hdl.handle.net/10722/205341-
dc.description.abstractStudying time with statistics can help shed light on cause-effect relationships in large online data sets and address three sets of research questions regarding sequences, time periods, and influences of phenomena across different time-scales. As such studies face many analytic difficulties (related to the data, dependent variables, or explanatory variables), this chapter shows how the method of Statistical Discourse Analysis (SDA) addresses each of them. Then, the authors apply SDA to three online data sets: (a) 183 participants’ 894 messages in a mathematics forum without teacher moderation, (b) 17 students’ 1,330 messages in a 13-week graduate course, and (c) 21 students’ 252 messages across 8 weeks during a hybrid university course. Findings include (a) significant relationships between non-adjacent messages, (b) explanatory models of statistically-identified pivotal messages that distinguish distinct time periods, and (c) effects of larger phenomena on smaller phenomena (e.g., gender on message characteristics) and vice-versa (extensive summary on time periods).-
dc.languageengen_US
dc.publisherInformation Science Referenceen_US
dc.relation.ispartofAssessment and Evaluation of Time Factors in Online Teaching and Learning-
dc.relation.ispartofseriesResearch essentials-
dc.titleMicro-Analysis of Collaborative Processes that Facilitate Productive Online Discussions: Statistical Discourse Analyses in Three Studiesen_US
dc.typeBook_Chapteren_US
dc.identifier.emailChen, G: gwchen@hku.hken_US
dc.identifier.authorityChen, G=rp01874en_US
dc.identifier.doi10.4018/978-1-4666-4651-3.ch009-
dc.identifier.hkuros238842en_US
dc.identifier.spage232en_US
dc.identifier.epage263en_US
dc.publisher.placeHershey, PA-

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