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An Online Tool for Learning Collaboration and Learning While Collaborating

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Kildare, RA and Williams, R and Hartnett, J (2006) An Online Tool for Learning Collaboration and Learning While Collaborating. In: Australasian Computing Education Conference 2006, 16 - 19 January, 2006, Hobart, Tasmania.

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Abstract

Independent individuals are increasingly required to join as teams to complete online tasks. This impacts education in three ways . Firstly teachers increasingly set collaborative online tasks for students when teaching curriculum. Secondly individuals need to learn online collaboration skills. Finally, collaborative knowledge creation and innovation can occur when team members take risks. Educationally sound software must promote a psychologically secure environment. Software currently available for online learning and collaboration is predominantly task-based and does not support personal and social aspects of team interaction. Computer Supported Collaborative Learning (CSCL) and Computer Supported Collaborative Work (CSCW) communities are actively researching team interaction. Time Interaction and Performance (TIP) theory, while providing some framework for understanding interaction, does not recognise the unpredictability of team processes. This paper describes software which is hypothesised to support the education and performance of online team members. The software captures democratically created symbolic interaction rules and monitors indicators of the team's interaction. If the conditions are met for the rules to fire, the software enacts the consequent. The software, based on a model-free expert system, will accommodate emergent team interaction patterns and provide evolutionary, analytical feedback to both team members and researchers. Constructivist principles of activity and metacognition underlie the validity of this as an educational tool.

Item Type: Conference or Workshop Item (Paper)
Keywords: trust, conflict, collaborative learning, knowledge creation, virtual teams, complex systems, expert systems, data mining
Date Deposited: 23 Aug 2006
Last Modified: 18 Nov 2014 03:11
URI: http://eprints.utas.edu.au/id/eprint/371
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