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.
CITATION STYLE
Guzmán, E., & Conejo, R. (2015). Measuring misconceptions through item response theory. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9112, pp. 608–611). Springer Verlag. https://doi.org/10.1007/978-3-319-19773-9_73
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