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Multilevel IRT models for the university teaching evaluation


  • Silvia Bacci
  • Valeria Caviezel


In this paper, a generalization of the two-parameter partial credit model (2PL-PCM) and of two special cases, the partial credit model (PCM) and the rating scale model (RSM), with a hierarchical data structure will be presented. Having shown how 2PL-PCM, as with other item response theory (IRT) models, may be read in terms of a generalized linear mixed model (GLMM) with two aggregation levels, a presentation will be given of an extension to the case of measuring the latent trait of individuals aggregated in groups. The use of this Multilevel IRT model will be illustrated via reference to the evaluation of university teaching by students following the courses. The aim is to generate a ranking of teaching on the basis of student satisfaction, so as to give teachers, and those responsible for organizing study courses, a background of information that takes the opinions of the direct target group for university teaching (that is, the students) into account, in the context of improving the teaching courses available.

Suggested Citation

  • Silvia Bacci & Valeria Caviezel, 2011. "Multilevel IRT models for the university teaching evaluation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(12), pages 2775-2791, February.
  • Handle: RePEc:taf:japsta:v:38:y:2011:i:12:p:2775-2791
    DOI: 10.1080/02664763.2011.570316

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    Cited by:

    1. Galeotti, Marzio & Rubashkina, Yana & Salini, Silvia & Verdolini, Elena, 2018. "Environmental policy performance and its determinants: Application of a three-level random intercept model," Energy Policy, Elsevier, vol. 114(C), pages 134-144.
    2. Michele La Rocca & Maria Lucia Parrella & Ilaria Primerano & Isabella Sulis & Maria Prosperina Vitale, 2017. "An integrated strategy for the analysis of student evaluation of teaching: from descriptive measures to explanatory models," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(2), pages 675-691, March.
    3. Silvia Bacci & Michela Gnaldi, 2015. "A classification of university courses based on students’ satisfaction: an application of a two-level mixture item response model," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 927-940, May.

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