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Inferential confidence intervals for fuzzy analysis of teaching satisfaction

Author

Listed:
  • Donata Marasini

    (Università degli Studi di Milano-Bicocca)

  • Piero Quatto

    (Università degli Studi di Milano-Bicocca)

  • Enrico Ripamonti

    (Università degli Studi di Milano-Bicocca)

Abstract

Fuzzy sets are an extension of classical sets, used to mathematically model indefinite concepts, such as that of customer satisfaction. This is obtained by introducing a membership function expressing the degree of membership of the elements to a set. Intuitionistic fuzzy sets represent an extension of the theory of fuzzy sets, in which also a suitable non-membership function is defined. In this paper we aim at quantifying a latent construct, namely satisfaction, using fuzzy sets and intuitionistic fuzzy sets. We put forth a general evaluation method: first, we introduce a fuzzy satisfaction index to obtain membership values. Second, inferential confidence intervals (ICI), calculated through Bootstrap-t and percentile procedures, are used to assess the uncertainty underpinning membership and non-membership estimates. Third, we address the problem of optimal and multiple ICI, as well as their generalization through p values and q-values. In particular, we consider the problem of analyzing the responses to evaluation questionnaires. We apply this new method to a national program of evaluation of University courses and we discuss our framework in comparison with other evaluation techniques.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:qualqt:v:51:y:2017:i:4:d:10.1007_s11135-016-0349-7
    DOI: 10.1007/s11135-016-0349-7
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    References listed on IDEAS

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    Cited by:

    1. E. Nardo & R. Simone, 2019. "A model-based fuzzy analysis of questionnaires," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(2), pages 187-215, June.

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