Text mining approach to automate teamwork assessment in group chats
Pages 434 - 435
Abstract
The increasing use of chat tools for learning and collaboration emphasizes the need for automating assessment. We propose a text mining approach to automate teamwork assessment in chat data. This supervised training approach can be extended to other domains for efficient assessment.
References
[1]
Crowston, K., Allen, E. E., & Heckman, R. 2012. Using natural language processing technology for qualitative data analysis. International Journal of Social Research Methodology, 15(6), 523--543.
[2]
Dong, H., Hui, S. C., & He, Y. 2006. Structural analysis of chat messages for topic detection. Online Information Review, 30(5), 496--516.
[3]
Koh, E., Hong, H., & Seah, J. (2014). An Analytic Frame and Multi-method Approach to Measure Teamwork Competency. Proceedings of the 14th IEEE International Conference on Advanced Learning Technologies, 7--9 July 2014 (pp. 264--266). IEEE.
[4]
�zyurt, �., & K�se, C. 2010. Chat mining: Automatically determination of chat conversations' topic in Turkish text based chat mediums. Expert Systems with Applications, 37(12), 8705--8710
[5]
Ros�, C., Wang, Y. C., Cui, Y., Arguello, J., Stegmann, K., Weinberger, A., & Fischer, F. 2008. Analyzing collaborative learning processes automatically: Exploiting the advances of computational linguistics in computer-supported collaborative learning. International journal of computer-supported collaborative learning, 3(3), 237--271.
[6]
Tschan, S., & Nicolcev, P. 2013. Package AJAX_Chat (Version 0.8.7) {Software}. Available from http://frug.github.io/AJAX-Chat/
[7]
Yoon, S. W., & Johnson, S. D. 2008. Phases and patterns of group development in virtual learning teams. Educational Technology Research and Development, 56(5--6), 595--618.
Index Terms
- Text mining approach to automate teamwork assessment in group chats
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Information & Contributors
Information
Published In
March 2015
448 pages
ISBN:9781450334174
DOI:10.1145/2723576
- Conference Chairs:
- Josh Baron,
- Grace Lynch,
- Nicole Maziarz,
- Program Chairs:
- Paulo Blikstein,
- Agathe Merceron,
- George Siemens
Copyright � 2015 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 16 March 2015
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- Poster
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- Education Research Funding Programme, National Institute of Education, Nanyang Technological University, Singapore
Conference
LAK '15
LAK '15: the 5th International Learning Analytics and Knowledge Conference
March 16 - 20, 2015
New York, Poughkeepsie
Acceptance Rates
LAK '15 Paper Acceptance Rate 20 of 74 submissions, 27%;
Overall Acceptance Rate 236 of 782 submissions, 30%
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