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Temporal analytics with discourse analysis: Tracing ideas and impact on communal discourse
Citation
Lee, A. V. Y., & Tan, S. C. (2017). Temporal analytics with discourse analysis: Tracing ideas and impact on communal discourse. In LAK '17 Proceedings of the Seventh International Learning Analytics & Knowledge Conference (pp. 120-127). Simon Fraser University of Southern Queensland. https://doi.org/10.1145/3027385.3027386
Abstract
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.
Date Issued
2017
Description
This is the accepted version published in LAK '17 Proceedings of the Seventh International Learning Analytics & Knowledge Conference. The published version is available online at http://dx.doi.org/10.1145/3027385.3027386