Abstract
In this paper we propose an assessment model to measure both student knowledge and misconceptions through testing. For this purpose we use a well-founded psychometric theory, i.e. the Item Response Theory (IRT). Our proposal is an extension of our previous work in this field and permits, in the same test, the data-driven evaluation of knowledge and several misconceptions, thereby more efficiently using the evidence provided by the students, while solving a test, to enrich student perturbation models.
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Guzmán, E., Conejo, R. (2015). Measuring Misconceptions Through Item Response Theory. In: Conati, C., Heffernan, N., Mitrovic, A., Verdejo, M. (eds) Artificial Intelligence in Education. AIED 2015. Lecture Notes in Computer Science(), vol 9112. Springer, Cham. https://doi.org/10.1007/978-3-319-19773-9_73
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DOI: https://doi.org/10.1007/978-3-319-19773-9_73
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