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ERIC Number: EJ1022848
Record Type: Journal
Publication Date: 2014-May
Pages: 10
Abstractor: As Provided
Reference Count: N/A
ISBN: N/A
ISSN: ISSN-0007-1013
Discovering Indicators of Successful Collaboration Using Tense: Automated Extraction of Patterns in Discourse
Thompson, Kate; Kennedy-Clark, Shannon; Wheeler, Penny; Kelly, Nick
British Journal of Educational Technology, v45 n3 p461-470 May 2014
This paper describes a technique for locating indicators of success within the data collected from complex learning environments, proposing an application of e-research to access learner processes and measure and track group progress. The technique combines automated extraction of tense and modality via parts-of-speech tagging with a visualisation of the timing and speaker for each utterance developed to code and analyse learner discourse, exploiting the results of previous, non-automated analyses for validation. The work is developed using a dataset of interactions within a multi-user virtual environment and extended to a more complex dataset of synchronous chat texts during a collaborative design task. This methodology extends natural language processing into computer-based collaboration contexts, discovering the linguistic micro-events that construct the larger phases of successful design-based learning.
Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA/
Publication Type: Reports - Descriptive; Journal Articles
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A