Validez de las encuestas de satisfacción de los estudiantes para evaluar la calidad docenteel caso de la UPCT (Cartagena)

  1. García Martín, A. 1
  2. Montero Cases, T. 1
  3. García León, J. 1
  4. Vázquez Arenas, G. 1
  1. 1 Universidad Politécnica de Cartagena
    info

    Universidad Politécnica de Cartagena

    Cartagena, España

    ROR https://ror.org/02k5kx966

Journal:
REDU: Revista de Docencia Universitaria

ISSN: 1696-1412,  1887-4592

Year of publication: 2020

Volume: 18

Issue: 1

Pages: 275-290

Type: Article

DOI: 10.4995/REDU.2020.12996 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

More publications in: REDU: Revista de Docencia Universitaria

Abstract

 ANECA´s DOCENTIA program was developed to support the evaluation of teaching by the Spanish universities. Nowadays, teaching quality evaluation is a need linked to the transparency and continuous improvement requirements inherent to the European Higher Education Area. The indicators on the quality models frequently include student evaluation of teaching (SET), whose validity is the subject of a broad debate from the beginning of its use. One of the most widespread critical opinions argues that student surveys are not a good reference, as they contain non-assumable biases. With the aim of verify whether these biases actually exist, a statistical study has been carried out based on quality indicators data from the Technical University of Cartagena. Multiple linear regression has been used, through backward stepwise regression, to identify variables that may influence students’ opinions and to quantify their effects. The main result is that the variables analyzed, many of which are often cited as causes of bias, show little or no significant influence on student satisfaction with teaching. It is also important to remark that there are aspects of the teaching activity that can only be evaluated from the systematic observation made by students. Therefore, we believe that student surveys are an essential indicator, and their weight within teaching evaluation models should reflect their relevance.

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Data source: Dialnet