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By their nature, Exploratory Learning Environments allow a high degree of freedom which leads to a diversity of learner trajectories and make the modelling of all possible behaviours difficult. To address this, we propose an approach for knowledge representation and identification of task-dependent strategies that learners follow during exploration. The knowledge representation combines heterogeneous sources of information which are used for strategy identification by means of appropriate similarity metrics. Scenarios capturing educational aspects are presented and the outputs of the similarity metrics are discussed with examples from the domain of mathematical generalisation.
|Title of host publication||The 2nd international workshop on intelligent support for exploratory environments (ISEE'09), in conjunction with the 14th international conference on artificial intelligence in education (AIED 2009)|
|Editors||Manolis Mavrikis, Sergio Gutierrez, Paul Mulholland|
|Place of Publication||London|
|Publisher||Teaching Enhanced Learning|
|Publication status||Published - 2009|
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