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Abstract
The nature of the activities that take place in Exploratory Learning Environments allow generating a variety of learner trajectories and makes difficult to develop a model of all possible behaviours (correct or incorrect). To alleviate this situation, we propose an approach for knowledge representation and identification of strategies followed by the learners during exploratory learning. Our approach combines heterogeneous sources of information and defines appropriate similarity measures for strategy identification. Some scenarios from the domain of mathematical generalisation are presented.
Original language | English |
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Title of host publication | Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling |
Editors | V. Dimitrova, R. Mizoguchi, B. Du Boulay, A. Graesser |
Place of Publication | Amsterdam |
Publisher | IOS Press |
Pages | 626-628 |
Number of pages | 3 |
ISBN (Print) | 9781607500285 |
Publication status | Published - 2009 |
Event | Proceeding of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling - Duration: 1 Jan 2009 → … |
Publication series
Name | Frontiers in Artificial Intelligence and Applications |
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Publisher | IOS Press |
Conference
Conference | Proceeding of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling |
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Period | 1/01/09 → … |
Keywords
- Exploratory Learning
- Similarity Metrics
- Strategy Identification
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