Abstract
This paper describes our research lines that focus on modeling and inferring student procedural knowledge in Intelligent Tutoring Systems. Our proposal is to apply Item Response Theory, a well-founded theory for declarative knowledge assessment, to infer procedural knowledge in problem solving environments. Therefore, we treat the problems as tests and the steps of problem solving as options (or choices) in a question. An important feature of our system is that it is not only based on an expert analysis, but also on data-driven techniques so that it can collect the largest amount of students’ problem solving strategies as possible.
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Hernando, M. (2011). Student Procedural Knowledge Inference through Item Response Theory. In: Konstan, J.A., Conejo, R., Marzo, J.L., Oliver, N. (eds) User Modeling, Adaption and Personalization. UMAP 2011. Lecture Notes in Computer Science, vol 6787. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22362-4_43
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DOI: https://doi.org/10.1007/978-3-642-22362-4_43
Publisher Name: Springer, Berlin, Heidelberg
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