Please use this identifier to cite or link to this item: http://hdl.handle.net/10497/18693
Title: 
Authors: 
Keywords: 
Learning analytics
Discourse analysis
Temporality
Social network analysis
Idea measurement
Issue Date: 
2017
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). Vancouver, BC, Canada: Simon Fraser University of Southern Queensland. Retrieved from http://dx.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.
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
URI: 
Other Identifiers: 
10.1145/3027385.3027386
Appears in Collections:Conference Papers

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