Please use this identifier to cite or link to this item: http://hdl.handle.net/10497/19430
Title: 
Discovering dynamics of an idea pipeline: Understanding idea development within a knowledge building discourse
Authors: 
Keywords: 
Online discourse analysis
Knowledge building discourse
Idea pipeline
Idea
Development
Text mining
Network analysis
Issue Date: 
2017
Citation: 
Lee, A. V. Y., & Tan, S. C. (2017). Discovering dynamics of an idea pipeline: Understanding idea development within a knowledge building discourse. In W. Chen, J.-C. Yang, A. F. Mohd Ayub, S. L. Wong, & A. Mitrovic (Eds.), Proceedings of the 25th International Conference on Computers in Education (pp. 119-128). Retrieved from http://icce2017.canterbury.ac.nz/proceedings_main
Abstract: 
Idea development is an important process within a knowledge-building discourse and it is crucial to understand the dynamics of idea development throughout the discourse, such as the growth, flourishing or fading of ideas. This study proposes a framework called Idea Pipeline that explores and tracks the dynamics of idea development within a knowledge-building discourse. This pipeline consists of three phases: discovery, identification and analysis, and ‘rise above’ of ideas. Each phase of the pipeline will be illustrated using findings from a comparison study of two online knowledge building discourses. During the discovery phase, a
text miner is used to identify groups of related keywords from the discourse; this is represented as keyword graphs with weighted frequencies to show the diversity of ideas that were embedded within the knowledge-building discourse. In the idea identification and analysis phase, network analysis was conducted to help label key ideas that were promising to the discourse community; this would provide the community with information to decide which ideas to pursue so that advancement of communal knowledge could be achieved leading to the ‘rise above’ phase. This Idea Pipeline framework can be an additional method for the temporal analysis of a
computer-supported collaborative learning discourse over a longer duration of weeks or even months.
URI: 
Website: 
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