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Conference Paper: Analyzing academic discussion forum data with topic detection and data visualization

TitleAnalyzing academic discussion forum data with topic detection and data visualization
Authors
Issue Date2017
PublisherIEEE. The Journal's web site is located at http://tale-conference.org/TALE_past-conferences.php
Citation
2016 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), Bangkok, Thailand, 7-9 December 2016, p. 109-115 How to Cite?
AbstractIn 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.
Persistent Identifierhttp://hdl.handle.net/10722/245666

 

DC FieldValueLanguage
dc.contributor.authorWong, KWG-
dc.contributor.authorLi, SYK-
dc.contributor.authorWong, EWY-
dc.date.accessioned2017-09-18T02:14:45Z-
dc.date.available2017-09-18T02:14:45Z-
dc.date.issued2017-
dc.identifier.citation2016 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), Bangkok, Thailand, 7-9 December 2016, p. 109-115-
dc.identifier.urihttp://hdl.handle.net/10722/245666-
dc.description.abstractIn 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.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at http://tale-conference.org/TALE_past-conferences.php-
dc.relation.ispartofIEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE)-
dc.rightsIEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE). Copyright © IEEE.-
dc.rights©2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.titleAnalyzing academic discussion forum data with topic detection and data visualization-
dc.typeConference_Paper-
dc.identifier.emailWong, KWG: wongkwg@hku.hk-
dc.identifier.authorityWong, KWG=rp02193-
dc.identifier.doi10.1109/TALE.2016.7851779-
dc.identifier.hkuros276095-
dc.identifier.spage109-
dc.identifier.epage115-
dc.publisher.placeUnited States-

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