Temporal Analytics with Discourse Analysis: Tracing Ideas and Impact on Communal Discourse

This paper presents a study of temporal analytics and discourse analysis of an online discussion, through investigation of a group of 13 in-service teachers and 2 instructors. A discussion forum consisting of 281 posts on an online collaborative learning environment was investigated. A text-mining tool was used to discover keywords from the discourse, and through social network analysis based on these keywords, a significant presence of relevant and promising ideas within discourse was revealed. However, uncovering the key ideas alone is insufficient to clearly explain students' level of understanding regarding the discussed topics. A more thorough analysis was thus performed by using temporal analytics with step-wise discourse analysis to trace the ideas and determine their impact on communal discourse. The results indicated that most ideas within the discourse could be traced to the origin of a set of improvable ideas, which impacted and also increased the community's level of interest in sharing and discussing ideas through discourse.