Abstract
The Item Response Theory (IRT) is a statistical mechanism successfully used since the beginning of the 20th century to infer student knowledge through tests. Nevertheless, existing well-founded techniques to assess procedural tasks are generally complex and applied to well-defined tasks. In this paper, we describe how, using a set of techniques we have developed based on IRT, it is possible to infer declarative student knowledge through procedural tasks. We describe how these techniques have been used with undergraduate students, in the object oriented programming domain, through ill-defined procedural exercises.
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Gálvez, J., Guzmán, E., Conejo, R. (2010). Data-Driven Student Knowledge Assessment through Ill-Defined Procedural Tasks. In: Meseguer, P., Mandow, L., Gasca, R.M. (eds) Current Topics in Artificial Intelligence. CAEPIA 2009. Lecture Notes in Computer Science(), vol 5988. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14264-2_24
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DOI: https://doi.org/10.1007/978-3-642-14264-2_24
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