Estrategias de generación de datos para la aplicación de analítica de aprendizaje adaptativo

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dc.contributor.advisorDuque Méndez, Néstor Darío
dc.contributor.advisorJiménez Builes, Jovani Alberto
dc.contributor.authorQuijano Cabezas, Pablo Andres
dc.contributor.cvlac0002060090spa
dc.contributor.googlescholaruB6LIAsAAAAJspa
dc.contributor.orcidQuijano Cabezas, Pablo Andres [0009000776565998]spa
dc.contributor.researchgatePablo-Quijano-Cabezas-2spa
dc.contributor.researchgroupGaia Grupo de Ambientes Inteligentes Adaptativosspa
dc.contributor.researchgroupGrupo de Inteligencia Artificial en Educaciónspa
dc.date.accessioned2025-02-27T19:35:30Z
dc.date.available2025-02-27T19:35:30Z
dc.date.issued2024
dc.descriptionIlustracionesspa
dc.description.abstractLa educación de calidad es esencial para reducir desigualdades y mejorar la sociedad. La analítica de aprendizaje por su parte, es una disciplina que mediante técnicas de análisis de datos busca comprender y mejorar el aprendizaje y la enseñanza. Dentro de esta disciplina, la analítica de aprendizaje adaptativo personaliza la enseñanza según las acciones de los estudiantes. Esta tesis se centra en diseñar estrategias de generación de datos para la aplicación de analíticas de aprendizaje adaptativo en cursos híbridos. Tras una revisión sistemática de la literatura, se identificaron vacíos de conocimiento y se caracterizaron los elementos necesarios para las aplicaciones, definiendo consideraciones y estrategias CTP (Contexto, Teoría, Práctica), estructuradas y complementadas con aportes propios y ejemplos prácticos. Posteriormente, se desarrollaron las estrategias específicas de generación de datos con elementos tecnológicos, pedagógicos y comunicacionales, las cuales se integraron en un prototipo que proporciona una guía para docentes sobre cómo implementar estas estrategias en el diseño de cursos. Finalmente, la validación se realizó mediante un curso corto, evidenciando un correcto flujo de datos y siendo complementado con una aplicación ilustrativa en dos conjuntos de datos. De esta manera, se busca promover y ampliar la adopción de la analítica de aprendizaje adaptativo en el contexto educativo, mejorando la calidad en la educación, beneficiando el proceso de aprendizaje y contribuyendo con una mejor sociedad.spa
dc.description.abstractQuality education is essential to reduce inequalities and improve society. Learning analytics is a discipline that uses data analysis techniques to understand and improve learning and teaching. Within this discipline, adaptive learning analytics personalises teaching according to students' actions. This thesis focuses on designing data generation strategies for the application of adaptive learning analytics in hybrid courses. Through a systematic literature review, knowledge gaps were identified and the necessary elements for such applications were characterised, defining CTP (Context, Theory, Practice) considerations and strategies, structured and complemented with original contributions and practical examples. Subsequently, specific data generation strategies incorporating technological, pedagogical, and communicational elements were developed and integrated into a prototype that provides a guide for educators on implementing these strategies in course design. Finally, validation was conducted through a short course, demonstrating an effective data flow, and complemented with illustrative applications on two datasets. This approach aims to promote and expand the adoption of adaptive learning analytics in the educational context, thereby enhancing educational quality, benefiting the learning process, and contributing to a better society.eng
dc.description.curricularareaÁrea Curricular de Ingeniería de Sistemas e Informáticaspa
dc.description.degreelevelMaestríaspa
dc.description.degreenameMagíster en Ingeniería - Analíticaspa
dc.description.researchareaDescubrimiento de Conocimiento y Minería de Datosspa
dc.format.extent199 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameUniversidad Nacional de Colombiaspa
dc.identifier.reponameRepositorio Institucional Universidad Nacional de Colombiaspa
dc.identifier.repourlhttps://repositorio.unal.edu.co/spa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/87564
dc.language.isospaspa
dc.publisherUniversidad Nacional de Colombiaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Medellínspa
dc.publisher.facultyFacultad de Minasspa
dc.publisher.placeMedellín, Colombiaspa
dc.publisher.programMedellín - Minas - Maestría en Ingeniería - Analíticaspa
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dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseReconocimiento 4.0 Internacionalspa
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/spa
dc.subject.armarcInteligencia artificial - Procesamiento de datos
dc.subject.ddc000 - Ciencias de la computación, información y obras generales::004 - Procesamiento de datos Ciencia de los computadoresspa
dc.subject.ddc370 - Educación::378 - Educación superior (Educación terciaria)spa
dc.subject.ddc000 - Ciencias de la computación, información y obras generales::004 - Procesamiento de datos Ciencia de los computadoresspa
dc.subject.ddc000 - Ciencias de la computación, información y obras generales::005 - Programación, programas, datos de computaciónspa
dc.subject.ddc000 - Ciencias de la computación, información y obras generales::001 - Conocimientospa
dc.subject.lembAprendizaje automático (Inteligencia artificial)
dc.subject.lembEducación - Procesamiento de datos
dc.subject.proposalAnalítica de aprendizajespa
dc.subject.proposalEducación superiorspa
dc.subject.proposalGeneración de datosspa
dc.subject.proposalAprendizaje mixtospa
dc.subject.proposalAprendizaje adaptativospa
dc.subject.proposalProceso Enseñanza-Aprendizajespa
dc.subject.proposalInteligencia artificial predictivaspa
dc.subject.proposalLearning Analyticseng
dc.subject.proposalHigher Educationeng
dc.subject.proposalData Generationeng
dc.subject.proposalBlended Learningeng
dc.subject.proposalAdaptive Learningeng
dc.subject.proposalTeaching-Learning Processeng
dc.subject.proposalPredictive Artificial Intelligenceeng
dc.subject.wikidataAprendizaje semipresencial
dc.titleEstrategias de generación de datos para la aplicación de analítica de aprendizaje adaptativospa
dc.title.translatedData generation strategies for the implementation of adaptive learning analyticseng
dc.typeTrabajo de grado - Maestríaspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdccspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/masterThesisspa
dc.type.redcolhttp://purl.org/redcol/resource_type/TMspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

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