This contribution makes an attempt to analyze students' ratings of university teaching on a broad prospective, trying to adjust the final assessment from a wide range of factors which jointly may influence the process under evaluation: academic year peculiarities, course characteristics, students' characteristics and item dimensionality. From a methodological point of view, by setting complex Item Response models as special case of Generalized Linear or Mixed Models a large flexibility is introduced in the specification of ad hoc modelling approaches for the analysis of students' ratings.
Sulis, I., Capursi, V. (2013). Analysing SET over time using multilevel multidimensional explanatory IRT models. In Proceedings of the 28th International Workshop on Statistical Modelling. Palermo : Istituto Poligrafico Europeo.
Analysing SET over time using multilevel multidimensional explanatory IRT models
CAPURSI, Vincenza
2013-01-01
Abstract
This contribution makes an attempt to analyze students' ratings of university teaching on a broad prospective, trying to adjust the final assessment from a wide range of factors which jointly may influence the process under evaluation: academic year peculiarities, course characteristics, students' characteristics and item dimensionality. From a methodological point of view, by setting complex Item Response models as special case of Generalized Linear or Mixed Models a large flexibility is introduced in the specification of ad hoc modelling approaches for the analysis of students' ratings.
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