Abstract
We present a computational framework designed to provide adaptive support aimed at triggering learning from problem-solving activities in the presence of worked-out examples. The key to the framework’s ability to provide this support is a user model that exploits a novel classification of similarity to infer the impact of a particular example on a given student’s metacognitive behaviors and subsequent learning.
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© 2005 Springer-Verlag Berlin Heidelberg
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Muldner, K., Conati, C. (2005). Using Similarity to Infer Meta-cognitive Behaviors During Analogical Problem Solving. In: Ardissono, L., Brna, P., Mitrovic, A. (eds) User Modeling 2005. UM 2005. Lecture Notes in Computer Science(), vol 3538. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527886_18
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DOI: https://doi.org/10.1007/11527886_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27885-6
Online ISBN: 978-3-540-31878-1
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