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Fuzzy Analysis of Students’ Ratings

Author

Listed:
  • Donata Marasini
  • Piero Quatto
  • Enrico Ripamonti

Abstract

Background: Intuitionistic fuzzy sets (IFS) represent a methodology for quantifying latent variables in questionnaire analysis through membership and non-membership functions, which are linked by an uncertainty function. Objectives: We aim to apply an IFS approach to the problem of students’ satisfaction of university teaching. Such framework can take into account a source of uncertainty related to items and another related to subjects. Results: A new technique for IFS analysis is set forth and generalized to a multivariate scenario. Potential advantages of the IFS perspective with respect to other nonfuzzy approaches are provided. Application: We apply this method to a national program of university courses evaluation and we focus, in particular, on the outcomes of two Masters in Statistics.

Suggested Citation

  • Donata Marasini & Piero Quatto & Enrico Ripamonti, 2016. "Fuzzy Analysis of Students’ Ratings," Evaluation Review, , vol. 40(2), pages 122-141, April.
    • Handle: RePEc:sae:evarev:v:40:y:2016:i:2:p:122-141
    DOI: 10.1177/0193841X16662421
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    References listed on IDEAS

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    1. Donata Marasini & Piero Quatto, 2014. "A characterization of linear satisfaction measures," METRON, Springer;Sapienza Università di Roma, vol. 72(1), pages 17-23, April.
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    1. Donata Marasini & Piero Quatto & Enrico Ripamonti, 2017. "Inferential confidence intervals for fuzzy analysis of teaching satisfaction," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(4), pages 1513-1529, July.

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