Three interaction patterns on asynchronous online discussion behaviours: A methodological comparison
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.
Lay Description
What is already known about this topic?
- An asynchronous online discussion (AOD) is one format of instructional methods that facilitate student‐centered learning. A series of studies on AOD have actively discussed to imply the benefits and limitations in higher education.
- Although AOD can overcome physical and temporal limitations in classroom discussion, critical limitations, for example, lack of participation or unequal participation and difficulties to guide in‐depth discussion have been reported.
- In order to facilitate more active participation and to improve students' learning achievement in student‐centered learning environment, analyzing students' interactions and detecting isolated or active students in AOD by different methods have been proceeded.
What this paper adds?
- This study effectively ‘integrated’ three multiple methodologies such as Social Network Analysis (SNA), Content Analysis (CA) and Log‐data Analysis (LA) to analyse the quality of AOD. Through combination of those research approaches, the concept of interaction in AOD was described in three different views.
- Person to Person (P2P), Person to Content (P2C) and Person to System (P2S) are suggested suitable ways to explain students' interaction efficiently. These manners observe the situations at the multiple level and provide the opportunity for understanding learners' behavior in AOD.
- This study compared and analysed each methodology in detail. With comparison of different interaction analysis, this study proposed the convergence among P2P, P2C and P2S. Also, it investigated a synergetic effect of AOD interaction evaluation approach based on every methodology's strength.
Implications for practice and/or policy
- Consideration and understanding of each method's characteristics are essential for adapting respective methodology to various circumstances. Each approach has different strengths in analyzing students' discussion patterns.
- For example, P2P can find out students' interaction patterns with network centralities or centralizations, P2C can understand the level and the depth of content through a cognitive process and P2S can analyse learners' participation objectively according to the real‐time tracked data.
- Because there were synergetic effects of integrating methodologies, it implies that it is not adequate to use a single method for the analysis for AOD evaluation.
