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Abstract
We present initial results from a study comparing the effects of domain and collaboration feedback on learning withinCOLLECT-\(\mathcal{UML}\), a collaborative problem-solving ITS. UsingCOLLECT-\(\mathcal{UML}\), two students in separate physical locations (a collaborative pair) construct UML class diagrams to solve problems together. In the default version,COLLECT-\(\mathcal{UML}\) provides both domain and collaboration feedback. In this study however, collaborative pairs were randomly assigned to one of four modes (treatment conditions) which varied the feedback presented by the system: no feedback (NF), domain feedback only (DF), collaborative feedback only (CF), and both domain and collaborative feedback (DCF). All conditions improved significantly between pre- and post-test, showing that practicing withinCOLLECT-\(\mathcal{UML}\) helps learning. At a surface level, collaborative pairs in all modes had similar amounts of collaboration. The DCF mode had significantly higher learning gains than the other modes, indicating the value of receiving both domain and collaborative feedback. Surprisingly, the CF mode had the lowest learning gains (lower than NF), suggesting that, in this case, good collaboration without domain feedback could have simply reinforced erroneous domain knowledge.
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Authors and Affiliations
Intelligent Computer Tutoring Group, University of Canterbury, Private Bag 4800, Christchurch, 8140, New Zealand
Jay Holland, Moffat Mathews & Antonija Mitrovic
Dept. of Computing, Unitec Institute of Technology, Auckland, New Zealand
Nilufar Baghaei
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- Nilufar Baghaei
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Editors and Affiliations
EECS Department/ISIS, Vanderbilt University, TN 37235, Nashville, USA
Gautam Biswas
Electronic, Electrical and Computer Engineering, University of Birmingham, U.K.
Susan Bull
School of Information Technologies, University of Sydney, 1 Cleveland Street, 2006, Sydney, Australia
Judy Kay
College of Engineering, Department of Computer Science and Software Engineering, University of Canterbury, Private Bag 4800, 8140, Christchurch, New Zealand
Antonija Mitrovic
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Holland, J., Baghaei, N., Mathews, M., Mitrovic, A. (2011). The Effects of Domain and Collaboration Feedback on Learning in a Collaborative Intelligent Tutoring System. In: Biswas, G., Bull, S., Kay, J., Mitrovic, A. (eds) Artificial Intelligence in Education. AIED 2011. Lecture Notes in Computer Science(), vol 6738. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21869-9_72
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