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Advantages Of Using Self-Organizing Maps To Analyse Student Evaluations Of Teaching

Author

Listed:
  • Sorrosal Forradellas, M. T.

    (Department of Business, Universitat Rovira i Virgili, Spain.)

  • Barberà-Mariné, M. G.

    (Department of Business, Universitat Rovira i Virgili, Spain.)

  • Fernández Bariviera, Aurelio

    (Department of Business, Universitat Rovira i Virgili, Spain.)

  • Garbajosa-Cabello, M. J.

    (Department of Business, Universitat Rovira i Virgili, Spain.)

Abstract

Surveys to evaluate teaching performance are one of the most widely used instruments for assessing teaching capabilities and, consequently, the quality of teaching. Their success is largely due to how they are designed and the way in which they process information. The aim of this paper is to simplify the design of the student evaluations by removing the most correlated items, and to propose that Kohonen’s self-organizing Kohonen maps be used to group teachers in accordance with all the characteristics surveyed. The methodology is applied to the particular case of the Rovira i Virgili University.

Suggested Citation

  • Sorrosal Forradellas, M. T. & Barberà-Mariné, M. G. & Fernández Bariviera, Aurelio & Garbajosa-Cabello, M. J., 2012. "Advantages Of Using Self-Organizing Maps To Analyse Student Evaluations Of Teaching," Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), vol. 0(1), pages 53-71, May.
  • Handle: RePEc:fzy:fuzeco:v:xvii:y:2012:i:1:p:53-71
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    Cited by:

    1. Marco Aurélio de Oliveira & Antonio Schalata Pacheco & André Hideto Futami & Luiz Veriano Oliveira Dalla Valentina & Carlos Alberto Flesch, 2023. "Self‐organizing maps and Bayesian networks in organizational modelling: A case study in innovation projects management," Systems Research and Behavioral Science, Wiley Blackwell, vol. 40(1), pages 61-87, January.

    More about this item

    Keywords

    surveys to evaluate teaching performance; higher education; kohonen’s self-organizing maps;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

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