Association Rule Analysis of Student Satisfaction Surveys for Teaching Quality Evaluation

Jiménez Navarro, Manuel Jesús; Vega Márquez, Belén; Luna Romera, José María; Carranza García, Manuel; Martínez Ballesteros, María del Mar

doi:10.1007/978-3-031-42519-6_30

Ponencia

dc.creator	Jiménez Navarro, Manuel Jesús	es
dc.creator	Vega Márquez, Belén	es
dc.creator	Luna Romera, José María	es
dc.creator	Carranza García, Manuel	es
dc.creator	Martínez Ballesteros, María del Mar	es
dc.date.accessioned	2024-04-11T09:15:10Z
dc.date.available	2024-04-11T09:15:10Z
dc.date.issued	2023-08
dc.identifier.citation	Jiménez Navarro, M.J., Vega Márquez, B., Luna Romera, J.M., Carranza García, M. y Martínez Ballesteros, M.d.M. (2023). Association Rule Analysis of Student Satisfaction Surveys for Teaching Quality Evaluation. En 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) (319-328), Salamanca (España): Springer Link.
dc.identifier.isbn	978-3-031-42518-9	es
dc.identifier.isbn	978-3-031-42519-6 (online)	es
dc.identifier.uri	https://hdl.handle.net/11441/156784
dc.description.abstract	The quality of university teaching is essential for the success of students and the academic excellence of an educational institution. The purpose of this work is to provide a methodology based on the Association Rule technique using the Apriori algorithm to analyze the results obtained from the student evaluation process regarding their satisfaction with the teaching received. This methodology has been applied in programming courses of students of several courses both in the Computer Engineering and Health Engineering degrees at University of Seville, Spain. The proposed methodology can serve as a starting point for a self-improvement process that clearly identifies strengths and weaknesses.	es
dc.description.sponsorship	Ministerio de Ciencia e Innovación PID2020-117954RB-C22	es
dc.description.sponsorship	Ministerio de Ciencia e Innovación TED2021-131311B-C21	es
dc.description.sponsorship	Junta de Andalucía PYC20 RE 078 USE	es
dc.format	application/pdf	es
dc.format.extent	10	es
dc.language.iso	eng	es
dc.publisher	Springer Link	es
dc.relation.ispartof	16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) (2023), pp. 319-328.
dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 Internacional	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	*
dc.subject	Quality	es
dc.subject	Teacher evaluation	es
dc.subject	Machine learning	es
dc.subject	Association rules	es
dc.title	Association Rule Analysis of Student Satisfaction Surveys for Teaching Quality Evaluation	es
dc.type	info:eu-repo/semantics/conferenceObject	es
dc.type.version	info:eu-repo/semantics/publishedVersion	es
dc.rights.accessRights	info:eu-repo/semantics/openAccess	es
dc.contributor.affiliation	Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos	es
dc.relation.projectID	PID2020-117954RB-C22	es
dc.relation.projectID	TED2021-131311B-C21	es
dc.relation.projectID	PYC20 RE 078 USE	es
dc.relation.publisherversion	https://link.springer.com/chapter/10.1007/978-3-031-42519-6_30	es
dc.identifier.doi	10.1007/978-3-031-42519-6_30	es
dc.publication.initialPage	319	es
dc.publication.endPage	328	es
dc.eventtitle	16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023)	es
dc.eventinstitution	Salamanca (España)	es
dc.contributor.funder	Ministerio de Ciencia e Innovación (MICIN). España	es
dc.contributor.funder	Junta de Andalucía	es

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