Over the past years, Italian universities have come under increased pressure to be more competitive and attract more students, and students’ satisfaction has received increasing attention. Students’ opinions about a few aspects of academic life are sought by Italian universities in the form of a satisfaction feedback questionnaire. The aim of this paper is to classify university courses into homogeneous classes with respect to the level of students’ satisfaction through the use of a two-level mixture item response model. The data are drawn from the Italian questionnaire on students’ satisfaction administered at a Faculty of Political Sciences. The latent variables measured by the questionnaire are detected performing a model-based hierarchical clustering. Then, a special case of multilevel mixture factor model characterised by an item response parameterisation and discrete latent variables at all hierarchical levels is estimated. The study allowed us to ascertain (i) the latent dimensionality of students’ satisfac- tion with higher education courses; (ii) the varied effect of first and second-level covariates on the satisfaction dimensions; and (iii) the different sources of strength/weaknesses of the best and worst courses.

A classification of university courses based on students’ satisfaction: an application of a two-level mixture item response model

BACCI, Silvia;GNALDI, MICHELA
2015-01-01

Abstract

Over the past years, Italian universities have come under increased pressure to be more competitive and attract more students, and students’ satisfaction has received increasing attention. Students’ opinions about a few aspects of academic life are sought by Italian universities in the form of a satisfaction feedback questionnaire. The aim of this paper is to classify university courses into homogeneous classes with respect to the level of students’ satisfaction through the use of a two-level mixture item response model. The data are drawn from the Italian questionnaire on students’ satisfaction administered at a Faculty of Political Sciences. The latent variables measured by the questionnaire are detected performing a model-based hierarchical clustering. Then, a special case of multilevel mixture factor model characterised by an item response parameterisation and discrete latent variables at all hierarchical levels is estimated. The study allowed us to ascertain (i) the latent dimensionality of students’ satisfac- tion with higher education courses; (ii) the varied effect of first and second-level covariates on the satisfaction dimensions; and (iii) the different sources of strength/weaknesses of the best and worst courses.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1355908
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