New perspectives on university quality assessment: A Mamdani Fuzzy Inference System approach

Higher education has traditionally played the role of an overarching factor in economic growth and development. The implementation of the European Higher Education Area (EHEA) has already achieved improvements in many educational areas, but there remain, within the requirement to ensure academic excellence, cases where the quality criteria are not entirely harmonized. Genuine harmonization among the 48 countries that have so far been affiliated with the EHEA has been a key challenge for national educational assessment agencies and related bodies. This study aims to analyze the quality of the Spanish university system partially through a model based on the Mamdani Fuzzy Inference System (FIS) methodology. Numerous studies have been identified that evaluate university quality from the perspective of the student, but there are no studies that analyze the quality of public higher education institutions from the perspective of faculty employees. This research gap prompted an extensive literature review, considering fifteen main elements classified into five categories: internationalization; scientific production, occupational category, academic background, and professional experience. Researchers collected and curated data from a database of four Madrid-based public institutions. A Mamdani FIS, yielding a unique assessment in each case, was implemented using the MATLAB Fuzzy Logic Toolbox. Therefore, the results have been evaluated to determine which institution has led to better educational quality. The research approach leads to measuring the quality of public higher education institutions. First, thanks to the quality evaluation from the perspective of the workers and the professors who are part of the four public universities in Madrid. Second, we carried out this analysis under a methodology that has not been used before on that issue. Concerning its practical implications, this study can help policymakers design better practices to improve the careers of university professors and, as a result, the quality of higher education and the future employability of graduates.

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Publication Details

Journal
PLoS ONE
Published
2025-05-19
DOI
https://doi.org/10.1371/journal.pone.0321013
Citations
2
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
3.39

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article

New perspectives on university quality assessment: A Mamdani Fuzzy Inference System approach

Cristina Carrasco-Garrido, Belen Maria Moreno-Cabezali, Antonio Martínez Raya
2 citations
PLoS ONE
Online Learning and Analytics
3.39
article

New perspectives on university quality assessment: A Mamdani Fuzzy Inference System approach

Cristina Carrasco-Garrido, Belen Maria Moreno-Cabezali, Antonio Martínez Raya
article en
2 citations

Abstract

Higher education has traditionally played the role of an overarching factor in economic growth and development. The implementation of the European Higher Education Area (EHEA) has already achieved improvements in many educational areas, but there remain, within the requirement to ensure academic excellence, cases where the quality criteria are not entirely harmonized. Genuine harmonization among the 48 countries that have so far been affiliated with the EHEA has been a key challenge for national educational assessment agencies and related bodies. This study aims to analyze the quality of the Spanish university system partially through a model based on the Mamdani Fuzzy Inference System (FIS) methodology. Numerous studies have been identified that evaluate university quality from the perspective of the student, but there are no studies that analyze the quality of public higher education institutions from the perspective of faculty employees. This research gap prompted an extensive literature review, considering fifteen main elements classified into five categories: internationalization; scientific production, occupational category, academic background, and professional experience. Researchers collected and curated data from a database of four Madrid-based public institutions. A Mamdani FIS, yielding a unique assessment in each case, was implemented using the MATLAB Fuzzy Logic Toolbox. Therefore, the results have been evaluated to determine which institution has led to better educational quality. The research approach leads to measuring the quality of public higher education institutions. First, thanks to the quality evaluation from the perspective of the workers and the professors who are part of the four public universities in Madrid. Second, we carried out this analysis under a methodology that has not been used before on that issue. Concerning its practical implications, this study can help policymakers design better practices to improve the careers of university professors and, as a result, the quality of higher education and the future employability of graduates.

PLoS ONEVol. 20(5)
Universidad Rey Juan Carlos (ES), Universidad Politécnica de Madrid (ES)
Ministerio de Ciencia e Innovación
Partnerships for the goals
Openalex Percentile: Top 7%
Online Learning and Analytics
3.39
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