Publicación: Análisis de competencias adquiridas en la formación académica con las demandas laborales de ingenieros de sistemas utilizando técnicas de aprendizaje automático
dc.audience | ||
dc.contributor.advisor | Salas Álvarez, Daniel José | |
dc.contributor.author | Hoyos Cordero, Teófilo José | |
dc.contributor.author | Herazo Gonzalez, Sebastian | |
dc.contributor.jury | Fernandez Arango, Alexander | |
dc.contributor.jury | Crawford Vidal, Richard Adolfo | |
dc.date.accessioned | 2023-12-13T02:16:37Z | |
dc.date.available | 2023-12-13T02:16:37Z | |
dc.date.issued | 2023-12-12 | |
dc.description.abstract | Esta investigación se enfocó en analizar las competencias adquiridas durante la formación académica de ingenieros de sistemas con las exigencias actuales del mercado laboral. La metodología empleada incorporó técnicas de Aprendizaje Automático para un análisis exhaustivo. El proceso se dividió en cuatro etapas fundamentales. En la primera etapa, se recopilaron ofertas de empleo y se evaluaron las habilidades técnicas requeridas por las empresas. La segunda fase implicó la creación de un cuestionario basado en estas habilidades. La tercera etapa incluyó la administración del cuestionario a egresados, registrando sus respuestas en una matriz binaria. Finalmente, en la última etapa, se utilizó un software de Aprendizaje Automático para cotejar las competencias demandadas por las empresas con las habilidades de los egresados. Los resultados obtenidos revelaron tanto coincidencias como discrepancias en habilidades blandas, como trabajo en equipo, liderazgo y comunicación efectiva, donde solo un pequeño porcentaje de los 109 egresados encuestados las posee. Por otro lado, existe una coincidencia significativa en habilidades técnicas como "inglés B1 o más," "Bases de datos" y "Metodologías Ágiles" entre las requeridas por el mercado laboral y las habilidades de los egresados. Estos hallazgos destacaron la presencia de brechas entre las competencias de los egresados y las requeridas por el mercado laboral. La implementación de software de Aprendizaje Automático facilitó una comparación cuantitativa precisa y orientada de los requerimientos de las empresas y las habilidades de los ingenieros de sistemas. En consecuencia, se resalta la necesidad de una capacitación adicional para los futuros ingenieros de sistemas en áreas específicas. Además, se proporcionan directrices para mejorar la formación académica, alineándola eficazmente con las cambiantes exigencias del mercado laboral. Este enfoque beneficia tanto a las instituciones educativas como a las futuras generaciones de ingenieros de sistemas, asegurando su competitividad y éxito en un entorno laboral en constante evolución. | spa |
dc.description.abstract | This research focused on analyzing the competencies acquired during the academic training of systems engineers with the current demands of the labor market. The methodology used incorporated Machine Learning techniques for an exhaustive analysis. The process was divided into four fundamental stages. In the first stage, job offers were collected and the technical skills required by the companies were evaluated. The second stage involved the creation of a questionnaire based on these skills. The third stage involved administering the questionnaire to graduates, recording their responses in a binary matrix. Finally, in the last stage, Machine Learning software was used to match the competencies demanded by companies with the skills of the graduates. The results obtained revealed both coincidences and discrepancies in soft skills, such as teamwork, leadership, and effective communication, where only a small percentage of the 109 graduates surveyed possess them. On the other hand, there is a significant coincidence in technical skills such as "English B1 or more," "Databases" and "Agile Methodologies" between those required by the labor market and the skills of the graduates. These findings highlighted the presence of gaps between the skills of graduates and those required by the labor market. The implementation of Machine Learning software facilitated an accurate and targeted quantitative comparison of the requirements of companies and the skills of systems engineers. Consequently, the need for additional training for future system engineers in specific areas is highlighted. In addition, guidelines are provided for improving academic training, effectively aligning it with the changing demands of the labor market. This approach benefits both educational institutions and future generations of systems engineers, ensuring their competitiveness and success in a constantly evolving work environment. | eng |
dc.description.degreelevel | Pregrado | |
dc.description.degreename | Ingeniero(a) de Sistemas | |
dc.description.modality | Trabajos de Investigación y/o Extensión | |
dc.description.tableofcontents | 1. INTRODUCCIÓN 16 | spa |
dc.description.tableofcontents | 2. DESCRIPCIÓN Y FORMULACIÓN DEL PROBLEMA 17 | spa |
dc.description.tableofcontents | 2.1. ÁRBOL DE PROBLEMAS 20 | spa |
dc.description.tableofcontents | 3. JUSTIFICACIÓN 20 | spa |
dc.description.tableofcontents | 4. OBJETIVOS 22 | spa |
dc.description.tableofcontents | 4.1. OBJETIVO GENERAL 22 | spa |
dc.description.tableofcontents | 4.2. OBJETIVO ESPECÍFICOS 22 | spa |
dc.description.tableofcontents | 5. ESTADO DEL ARTE 23 | spa |
dc.description.tableofcontents | 6. MARCO TEÓRICO 42 | spa |
dc.description.tableofcontents | 6.1. Base de Datos 43 | spa |
dc.description.tableofcontents | 6.2. Aprendizaje Automático 43 | spa |
dc.description.tableofcontents | 6.3. Regresión Logística 43 | spa |
dc.description.tableofcontents | 6.4. Regresión Lineal 44 | spa |
dc.description.tableofcontents | 7. MATERIALES Y MÉTODOS 44 | spa |
dc.description.tableofcontents | 7.1. Materiales: 44 | spa |
dc.description.tableofcontents | 7.1.1. Plataforma de Desarrollo de Software 44 | spa |
dc.description.tableofcontents | 7.1.2. Base de Datos MySQL 44 | spa |
dc.description.tableofcontents | 7.1.3. Python 44 | spa |
dc.description.tableofcontents | 7.1.4. Flask 45 | spa |
dc.description.tableofcontents | 7.1.5. Interfaz de Usuario 45 | spa |
dc.description.tableofcontents | 7.1.6. Conjunto de Datos de Vacantes 46 | spa |
dc.description.tableofcontents | 7.2. Métodos: 46 | spa |
dc.description.tableofcontents | 7.2.1. Regresión Logística 46 | spa |
dc.description.tableofcontents | 7.2.2. Regresión Lineal 46 | spa |
dc.description.tableofcontents | 7.2.3. Gestión de Bases de Datos 46 | spa |
dc.description.tableofcontents | 7.2.4. Diseño de Interfaz de Usuario 46 | spa |
dc.description.tableofcontents | 8. METODOLOGÍA 46 | spa |
dc.description.tableofcontents | 8.1. Población 46 | spa |
dc.description.tableofcontents | 8.2. Muestra 47 | spa |
dc.description.tableofcontents | 8.3 TIPO DE INVESTIGACIÓN 47 | spa |
dc.description.tableofcontents | 8.4 LÍNEA DE INVESTIGACIÓN 47 | spa |
dc.description.tableofcontents | 8.5 FUENTES DE INVESTIGACIÓN 47 | spa |
dc.description.tableofcontents | 8.5.1. FUENTES DE INVESTIGACIÓN PRIMARIAS 47 | spa |
dc.description.tableofcontents | 8.5.2 FUENTES DE INVESTIGACIÓN SECUNDARIAS 47 | spa |
dc.description.tableofcontents | 8.6. FASES Y ETAPAS DE LA INVESTIGACIÓN 48 | spa |
dc.description.tableofcontents | 8.6.1 Fase 1: Recopilación de Vacantes Laborales 48 | spa |
dc.description.tableofcontents | 8.6.2. Fase 2: Diseño del instrumento 49 | spa |
dc.description.tableofcontents | 8.6.3. Fase 3: Construcción de la Matriz Binaria 51 | spa |
dc.description.tableofcontents | 8.6.4. Fase 4: Análisis de Resultados Utilizando el Software de Aprendizaje Automático 52 | spa |
dc.description.tableofcontents | 9. RESULTADOS Y DISCUSIONES 52 | spa |
dc.description.tableofcontents | 9.1. Análisis de las Habilidades Requeridas en el Mercado Laboral: 52 | spa |
dc.description.tableofcontents | 9.2. Análisis de Publicaciones de Vacantes Laborales en LinkedIn y CompuTrabajo 53 | spa |
dc.description.tableofcontents | 9.3. Creación de Base de Datos Estructurada y Análisis de Habilidades Demandadas 53 | spa |
dc.description.tableofcontents | 9.4. Software con Técnicas de Aprendizaje Automático 56 | spa |
dc.description.tableofcontents | 9.5. Diagrama de casos de uso 58 | spa |
dc.description.tableofcontents | 9.6. Diagrama casos de uso inicio de sesión 61 | spa |
dc.description.tableofcontents | 9.7. Diagrama casos de uso para análisis de competencias 62 | spa |
dc.description.tableofcontents | 9.8. Funcionamiento del Software 65 | spa |
dc.description.tableofcontents | 9.8.1. Brechas de Competencias Identificadas: 65 | spa |
dc.description.tableofcontents | 9.8.2. Potencial Educativo y Aprendizaje Continuo en Ingeniería de Sistemas: 68 | spa |
dc.description.tableofcontents | 9.8.3. Implicaciones para el Futuro y el Aprendizaje Continuo: 69 | spa |
dc.description.tableofcontents | 9.8.4. Fortalecimiento de la Formación Académica: 69 | spa |
dc.description.tableofcontents | 10. CONCLUSIONES 69 | spa |
dc.description.tableofcontents | 10.1. Demanda Evolutiva de Habilidades Técnicas 70 | spa |
dc.description.tableofcontents | 10.2. Importancia de las Habilidades Blandas 70 | spa |
dc.description.tableofcontents | 10.3. Concordancia entre la Formación y las Demandas Laborales 70 | spa |
dc.description.tableofcontents | 10.4. Aprendizaje Continuo y Adaptación 70 | spa |
dc.description.tableofcontents | 10.5. Colaboración entre la Universidad y las Empresas 71 | spa |
dc.description.tableofcontents | 10.6. Recomendación de Priorización de Habilidades 71 | spa |
dc.description.tableofcontents | 11. RECOMENDACIONES 71 | spa |
dc.description.tableofcontents | 12. BIBLIOGRAFÍA 72 | spa |
dc.description.tableofcontents | 13. ANEXOS 79 | spa |
dc.description.tableofcontents | Anexo 1 79 | spa |
dc.description.tableofcontents | Anexo 2 79 | spa |
dc.format.mimetype | application/pdf | |
dc.identifier.instname | Universidad de Córdoba | |
dc.identifier.reponame | Repositorio Universidad de Córdoba | |
dc.identifier.repourl | https://repositorio.unicordoba.edu.co/ | |
dc.identifier.uri | https://repositorio.unicordoba.edu.co/handle/ucordoba/7965 | |
dc.language.iso | spa | |
dc.publisher | Universidad de Córdoba | |
dc.publisher.faculty | Facultad de Ingeniería | |
dc.publisher.program | Ingeniería de Sistemas | |
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dc.rights | Copyright Universidad de Córdoba, 2023 | |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | |
dc.rights.license | Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.subject.keywords | Professional competencies | |
dc.subject.keywords | Systems engineering | |
dc.subject.keywords | Labor demand | |
dc.subject.keywords | Skills gap | |
dc.subject.keywords | Machine learning | |
dc.subject.proposal | Competencias profesionales | spa |
dc.subject.proposal | Ingeniería de sistemas | spa |
dc.subject.proposal | Demanda laboral | spa |
dc.subject.proposal | Brecha de habilidades | spa |
dc.subject.proposal | Aprendizaje automático | spa |
dc.title | Análisis de competencias adquiridas en la formación académica con las demandas laborales de ingenieros de sistemas utilizando técnicas de aprendizaje automático | spa |
dc.type | Trabajo de grado - Pregrado | |
dc.type.coar | http://purl.org/coar/resource_type/c_7a1f | |
dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | |
dc.type.content | Text | |
dc.type.driver | info:eu-repo/semantics/bachelorThesis | |
dc.type.version | info:eu-repo/semantics/acceptedVersion | |
dspace.entity.type | Publication |
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