Assessing university students’ perception of academic quality using machine learning
Metadatos
Afficher la notice complèteAuteur
Guillén Perales, Alberto; Liébana Cabanillas, Francisco José; Sánchez Fernández, Juan; Herrera Maldonado, Luis JavierEditorial
Elsevier
Materia
Service quality Higher education SERVQUAL
Date
2020Referencia bibliográfica
Applied Computing and Informatics Vol. 20 No. 1/2, 2024 pp. 20-34 [10.1108/ACI-06-2020-0003]
Patrocinador
Spanish Ministry of Economy and Competitiveness (MINECO) #1 under Grant RTI2018-101674-B-I00; European Regional Development Fund (ERDF) #2 under Grant FPA2017-85197-P; ERDF #3 under Grant B-SEJ-209-UGR18Résumé
Purpose – The aim of this research is to assess the influence of the underlying service quality variable, usually
related to university students’ perception of the educational experience. Another aspect analysed in this work is
the development of a procedure to determinewhich variables are more significant to assess students’ satisfaction.
Design/methodology/approach – In order to achieve both goals, a twofold methodology was approached.
In the first phase of research, an assessment of the service quality was performed with data gathered from 580
students in a process involving the adaptation of the SERVQUAL scale through a multi-objective optimization
methodology. In the second phase of research, results obtained from students were compared with those
obtained from the teaching staff at the university.
Findings – Results from the analysis revealed the most significant service quality dimensions from the
students’ viewpoint according to the scores that they provided. Comparison of the results with the teaching
staff showed noticeable differences when assessing academic quality.
Originality/value – Significant conclusions can be drawn from the theoretical review of the empirical
evidences obtained through this study helping with the practical design and implementation of quality
strategies in higher education especially in regard to university education.