Three interaction patterns on asynchronous online discussion behaviours: A methodological comparison

I. Jo, Y. Park, H. Lee

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

An 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 12 weeks. 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.

Original languageEnglish
Pages (from-to)106-122
Number of pages17
JournalJournal of Computer Assisted Learning
Volume33
Issue number2
DOIs
StatePublished - 1 Apr 2017

Keywords

  • asynchronous online discussion
  • content analysis
  • data-mining
  • social network analysis (SNA)

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