Tracing Nested Timelines of Participation and Understanding in Asynchronous Online Discussions

• In Event: Connecting the Moving Dots: Comparing Approaches to Coordinating Temporal Analyses of Groups and Individuals

Abstract

Objectives and Analytical Framework
Asynchronous online discussions are of interest as a vehicle for learning in both online and blended higher education settings (Allen et al., 2007; Luppicini, 2007). The detailed traces of student activity created in online discussions also present rich opportunities for research on learning both from the perspective of a group collectively improving ideas and that of individuals in the group deepening their personal understanding (Stahl, 2003). Specifically, log-file data of actions (e.g. when and for how long students access others’ contributions etc.) facilitate analysis of group and individual participation patterns, while the content of the posts supports examination of collective and individual understandings. Each of these levels of analysis (see Figure 1) can be considered statically for discussions in whole or dynamically as they develop over time.

Figure1.

Methods
This work unites our previous research developing different analytic techniques to study how groups and individuals participate and develop understanding over time (Wise & Padmanabhan, 2009; Wise & Chiu, in press; Wise et al. 2011). Such coordination is challenging because of differing timescales (Lemke, 2000): while a group’s discussion contributions and idea development are distributed across days, individuals’ experience participation in concentrated bursts over minutes. Similarly, the artifact of a complete discussion is not how the living discussion appeared to its participants at different points in time. We address these challenges through four sequential analytical steps:

Log-file data analysis (see Figure 2)
1. Tracing Group Participation. Creation and interpretation of Time-Event Diagram that shows patterns of group participation distributed over threads and time.
2. Tracing Individual Participation. Inspection of session-by-session statistics and individual actions in the context of the discussion over time using Time-Event Diagram.

Post content analysis
3. Tracing Group Ideas. Tracking of flow of the foci, tenor and consensus of the groups’ ideas.
4. Tracing Individual Ideas. Examination of evolution of individual students’ ideas in the context of group’s idea development.

Figure 2.

Results and Significance
In this presentation, we illustrate our analytic approach by examining how the participation and ideas of one group-member (“Allan”) develop in relation to those of his five-student group as they interact in a week-long discussion as part of a blended undergraduate business course. The students were given a business challenge to analyze and recommend a solution. Results show a relationship between the flow of Allan’s participation and ideas with respect to that of the group. Specifically Allan is most active as a contributor when his ideas are in alignment with the group (early on when he drives the group towards a particular solution, and at the end when he acquiesces to a different one). In between, there is a divergence between his views and those of the group and also a divergence in participation: the group becomes very active, but Allan participates mainly as a “listener,” spending time reading others’ ideas, while contributing few of his own. The results suggest an intriguing relationship between consensus and participation and illustrate the value of this analytic approach.

Authors

• Alyssa F. Wise, Simon Fraser University

• Ying-Ting Hsiao, Simon Fraser University