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Building up adjusted indicators of students’ evaluation of university courses using generalized item response models

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  • Isabella Sulis
  • Vincenza Capursi

Abstract

This article advances a proposal for building up adjusted composite indicators of the quality of university courses from students’ assessments. The flexible framework of Generalized Item Response Models is adopted here for controlling the sources of heterogeneity in the data structure that make evaluations across courses not directly comparable. Specifically, it allows us to: jointly model students’ ratings to the set of items which define the quality of university courses; explicitly consider the dimensionality of the items composing the evaluation form; evaluate and remove the effect of potential confounding factors which may affect students’ evaluation; model the intra-cluster variability at course level. The approach simultaneously deals with: (i) multilevel data structure; (ii) multidimensional latent trait; (iii) personal explanatory latent regression models. The paper pays attention to the potential of such a flexible approach in the analysis of students evaluation of university courses in order to explore both how the quality of the different aspects (teaching, management, etc.) is perceived by students and how to make meaningful comparisons across them on the basis of adjusted indicators.

Suggested Citation

  • Isabella Sulis & Vincenza Capursi, 2013. "Building up adjusted indicators of students’ evaluation of university courses using generalized item response models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(1), pages 88-102, January.
  • Handle: RePEc:taf:japsta:v:40:y:2013:i:1:p:88-102
    DOI: 10.1080/02664763.2012.734796
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    Cited by:

    1. Isabella Sulis & Mariano Porcu & Vincenza Capursi, 2019. "On the Use of Student Evaluation of Teaching: A Longitudinal Analysis Combining Measurement Issues and Implications of the Exercise," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(3), pages 1305-1331, April.
    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. Sulis, Isabella & Giambona, Francesca & Porcu, Mariano, 2020. "Adjusted indicators of quality and equity for monitoring the education systems over time. Insights on EU15 countries from PISA surveys," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    4. Francesca Giambona & Mariano Porcu & Isabella Sulis, 2023. "Does education protect families' well-being in times of crisis? Measurement issues and empirical findings from IT-SILC data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(1), pages 299-328, March.

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