An automatic approach for analysing online discussion forums via text mining

Tak Lam WONG, Wai-Shing HO, Jeff K. T. TANG, Fu Lee WANG, Kwok Shing CHENG

Research output: Contribution to conferencePapers

Abstract

Online discussion forums have been widely used in distance learning and blended learning for developing critical thinking and communication skills. To handle the increasing number of posts in discussion forums, we developed an automatic approach for analysing online discussion data based on a text mining technique. One characteristic of our approach is that text clustering was applied to automatically extract the arguments from posts on a discussion topic. Similar arguments from different users can be grouped together for better analysis by teachers or students. We have conducted a case study using a discussion forum on a course for in-service teachers to evaluate the effectiveness and usefulness of our approach.
Original languageEnglish
Publication statusPublished - 2014
EventInaugural International Conference on Open and Flexible Education - The Open University of Hong Kong, Hong Kong
Duration: 16 Jan 201417 Jan 2014
http://icofe2014.ouhk.edu.hk/index.html

Conference

ConferenceInaugural International Conference on Open and Flexible Education
Abbreviated titleICOFE 2014
Country/TerritoryHong Kong
Period16/01/1417/01/14
Internet address

Citation

Wong, T.-L., Ho, W. S., Tang, J., Wang, F. L., & Cheng, G. (2014, January). An automatic approach for analysing online discussion forums via text mining. Paper presented at the Inaugural International Conference on Open and Flexible Education (ICOFE 2014), The Open University of Hong Kong, China.

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