Analyzing academic discussion forum data with topic detection and data visualization

Ka Wai Gary WONG, Yiu Keung LI, Wai Yan WONG

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

In this paper, we are going to present the latest development of an ongoing learning analytics project extended based on [9] and [12], which sets the directions for the next stages of our experiment to aim for a better educational technology application in helping teacher evaluate the learning process of students through performance analytics of a general education course module with an online discussion forum. As it is time-consuming to manually spot the discussion forums by humans to know the changes and therefore, better tools are needed. In this project, contents of discussion forums of students were extracted into for mining patterns. In our latest experiments, we deployed topic detection and data visualization tools to analyze the discussion forum data better to generate intelligence to understand the how the students are performing in and feeling about the course modules they are taking. Copyright © 2016 by the Institute of Electrical and Electronics Engineers, Inc.
Original languageEnglish
Title of host publicationProceedings of 2016 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)
Place of PublicationNew York
PublisherIEEE
Pages109-115
ISBN (Print)9781509055982, 9781509055999
DOIs
Publication statusPublished - 2016

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Citation

Wong, G. K. W., Li, S. Y. K., & Wong, E. W. Y. (2016). Analyzing academic discussion forum data with topic detection and data visualization. In Proceedings of 2016 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE) (pp. 109-115). New York: IEEE.

Keywords

  • LDA
  • LDAvis
  • Data visualization
  • Topic detection
  • Education Data Mining
  • TDG project code: T0165
  • Period: TDG 2015-2016
  • Teaching Development Grant (TDG)
  • Teaching Development Grant (TDG) Output