Using automated and fine-grained analysis of pronoun use as indicators of progress in an online collaborative project

Thompson, Kate and Kennedy-Clark, Shannon and Kelly, Nick and Wheeler, Penny (2013) Using automated and fine-grained analysis of pronoun use as indicators of progress in an online collaborative project. In: 10th International Conference on Computer-Supported Collaborative Learning (CSCL 2013): To See the World and a Grain of Sand: Learning across Levels of Space, Time, and Scale, 15-19 Jun 2013, Madison, WI. United States.

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Abstract

Multimodal discourse analysis has been shown to be useful in adding depth to our understanding of the processes of computer supported collaborative learning. We take one of the codes used in a multi-modal coding scheme (CPACS), and apply automated data extraction techniques to a large corpus of data aimed at one code in the micro-level (pronouns). The results of this are plotted over time, and patterns of pronoun use identified for further investigation using an in depth systemic functional linguistics (SFL) approach. Complications concerned with singular and plural second person are discussed, and patterns of pronoun use that indicate movement of the group from one phase of design work the next are identified. Further refinement of the techniques of automated extraction are required to capture additional patterns noted in the SFL analysis.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: © ISLS. This publication is copyright. It may be reproduced in whole or in part for the purposes of study, research, or review, but is subject to the inclusion of an acknowledgment of the source.
Faculty / Department / School: Historic - Australian Digital Futures Institute
Date Deposited: 02 Mar 2014 03:00
Last Modified: 24 Sep 2014 22:42
Uncontrolled Keywords: CPACS; pronoun; analysis; collaborative learning; nlp; computational linguistics; cscl
Fields of Research : 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080107 Natural Language Processing
08 Information and Computing Sciences > 0804 Data Format > 080401 Coding and Information Theory
13 Education > 1303 Specialist Studies in Education > 130309 Learning Sciences
Socio-Economic Objective: C Society > 93 Education and Training > 9301 Learner and Learning > 930103 Learner Development
C Society > 93 Education and Training > 9301 Learner and Learning > 930102 Learner and Learning Processes
URI: http://eprints.usq.edu.au/id/eprint/24732

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