Teaching statistics: an assessment framework based on Multidimensional IRT and Knowledge Space Theory

In recent years, there is an increasing need for technology-based platforms to assist traditional learning methodologies. However, it is challenging to set up a common assessment framework to evaluate user knowledge. To address this issue, we propose an approach to teaching undergraduate statistics that makes use of the psychometric Item Response Theory based on latent class categorization to evaluate the user ability based on the European learning outcomes - the Dublin descriptors. Additionally, we enclose the user assessment workflow in a formalized structure using the principles of Knowledge Space Theory to track the current user knowledge state adaptively. The methodological framework serves as a base for the app developed within the ALEAS ERASMUS+ Project.