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dc.contributor.authorTalamás Carvajal, Juan Andrés
dc.date.accessioned2023-09-20T19:11:54Z
dc.date.available2023-09-20T19:11:54Z
dc.date.issued2023
dc.identifier.citationTalamas-Carvajal, J.A. (2023). Research plan on the effects of interventions on dropout predictions for Higher Education Institutions. In Proceedings of the 11th International Conference on Technological Ecosystems for Enhancing Multiculturality (TEEM 2023). Braganca, Portugal.es_MX
dc.identifier.urihttps://hdl.handle.net/11285/651171
dc.description.abstractOne of the main challenges that Higher Education Institutions face currently is dropout/ student retention. In most cases, identifying this group of stu-dents is no easy task, and doing so on time is even harder. This challenge re-quires both speed and accuracy, which makes it a prime candidate for the use of machine learning models and predictions. We are currently developing a series of models capable of early identification of students at risk of dropping out, with one key difference from classic approaches: we want to not only find out who these students are, but how we can best help them avoid that prediction. By developing methodologies capable of identifying and measur-ing the effects of a series of interventions (academic guidance courses, extra-curricular encouragement, diminished course load, etc.), we intend to devel-op a system capable of providing counterfactuals (what the student needs to change or do to reverse a prediction) based on the causal effects of the previ-ously mentioned interventions. In this manner, we would not only identify groups of students at risk of dropping out, but would be doing so on time, and with a viable and specific strategy for each individual to improve.es_MX
dc.format.mediumTextoes_MX
dc.language.isoenges_MX
dc.relationProject ID # I004 - IFE001 - C2-T3 – T.es_MX
dc.relationFondo de Apoyo a Publicaciones Tecnologico de Monterreyes_MX
dc.relation.isFormatOfsubmittedVersiones_MX
dc.rightsopenAccesses_MX
dc.rights.urihttp://creativecommons.org/licenses/by/4.0es_MX
dc.subjectHUMANIDADES Y CIENCIAS DE LA CONDUCTA::PEDAGOGÍA::TEORÍA Y MÉTODOS EDUCATIVOSes_MX
dc.subject.lcshTechnologyes_MX
dc.titleResearch plan on the effects of interventions on dropout predictions for higher education institutionses_MX
dc.title.alternativeTechnological Ecosystems for Enhancing Multiculturality 2023es_MX
dc.typeObjeto de congreso/Conference Objectes_MX
dc.identifier.orcidhttps://orcid.org/0000-0002-6140-088Xes_MX
dc.subject.keywordDropoutes_MX
dc.subject.keywordIntervention effectses_MX
dc.subject.keywordHigher educationes_MX
dc.subject.keywordEducational Innovationes_MX
dc.subject.keywordinteligencia artificiales_MX
dc.contributor.institutionPolytechnic Institute of Bragançaes_MX
dc.contributor.affiliationTecnologico de Monterreyes_MX
dc.contributor.affiliationhttps://ror.org/03ayjn504es_MX
dc.subject.countryPortugal / Portugales_MX
dc.identifier.cvu840053es_MX
dc.identifier.scopusid58126519600es_MX
dc.identificator4||58||5801es_MX


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