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Towards Educational Sustainability: An AI System for Identifying and Preventing Student Dropout

dc.contributor.authorBrand C E.J
dc.contributor.authorRamirez G.M
dc.contributor.authorDiaz J
dc.contributor.authorMoreira F.
dc.date.accessioned2024-07-31T21:07:08Z
dc.date.available2024-07-31T21:07:08Z
dc.date.created2024
dc.identifier.issn19328540
dc.identifier.urihttp://hdl.handle.net/11407/8478
dc.descriptionThe design and development of a web application to identify a high or low probability of student dropout at the National Learning Service (SENA) in Colombia, aiming to streamline the process of identifying and supporting potential candidates for assistance provided by the institution through the student welfare department. Throughout the development, socioeconomic variables with the highest impact on characterized academic dropout processes to create a dataset. This dataset was then utilized with various artificial intelligence techniques explored in Machine Learning (Decision Trees, K-means, and Regression), ultimately determining the most effective algorithm for integration into the Software. The decision tree classification technique emerged as the most effective, achieving an impressive accuracy of 91% and a minimal error rate of 9%, substantiating its state-of-the-art standing. As a result, this Software has optimized processes within the Student Welfare Department at SENA and is adaptable for use in any higher education institution. IEEE
dc.language.isoeng
dc.publisherEducation Society of IEEE (Spanish Chapter)
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85189184531&doi=10.1109%2fRITA.2024.3381850&partnerID=40&md5=ebff4160ec30ef0f214c3cbbcb87eb69
dc.sourceRevista Iberoamericana de Tecnologias del Aprendizaje
dc.sourceRev. Iberoam. Technol. Aprendizaje
dc.sourceScopus
dc.subjectArtificial Intelligenceeng
dc.subjectBiological system modelingeng
dc.subjectClassification algorithmseng
dc.subjectColombiaeng
dc.subjectData miningeng
dc.subjectDecision treeseng
dc.subjectEducationeng
dc.subjectHigher Educationeng
dc.subjectMachine Learning School Dropouteng
dc.subjectPrediction algorithmseng
dc.subjectTrainingeng
dc.subjectBioinformaticseng
dc.subjectDecision treeseng
dc.subjectK-means clusteringeng
dc.subjectLearning algorithmseng
dc.subjectLearning systemseng
dc.subjectMachine learningeng
dc.subjectStudentseng
dc.subjectAI systemseng
dc.subjectBiological system modelingeng
dc.subjectClassification algorithmeng
dc.subjectColombiaeng
dc.subjectDesign and Developmenteng
dc.subjectHigh educationseng
dc.subjectMachine learning school dropouteng
dc.subjectMachine-learningeng
dc.subjectPrediction algorithmseng
dc.subjectWEB applicationeng
dc.subjectData miningeng
dc.titleTowards Educational Sustainability: An AI System for Identifying and Preventing Student Dropouteng
dc.typearticle
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.publisher.programIngeniería de Sistemasspa
dc.type.spaArtículo
dc.identifier.doi10.1109/RITA.2024.3381850
dc.relation.citationstartpage1
dc.relation.citationendpage1
dc.publisher.facultyFacultad de Ingenieríasspa
dc.affiliationBrand C, E.J., Servicio Nacional de Aprendizaje (SENA), Bogotá, Colombia
dc.affiliationRamirez, G.M., Facultad de Ingenierías, Universidad de Medellín, Medellín, Colombia
dc.affiliationDiaz, J., Departamento de Ciencias de Computación e Informatíca, Universidad de la Frontera, Temuco, Chile
dc.affiliationMoreira, F., REMIT, IJP, Universidade Portucalense, Porto &#x0026
dc.affiliationIEETA, Universidade de Aveiro, Aveiro, Portugal
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellín
dc.identifier.repourlrepourl:https://repository.udem.edu.co/
dc.identifier.instnameinstname:Universidad de Medellín


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