Big data e inteligencia artificial, dos herramientas clave en procesos administrativos para instituciones de educación superior

Ingeniero Informático

Autores:: Moreno Cardozo, Santiago Nicolás

Tipo de recurso:: Trabajo de grado de pregrado

Fecha de publicación:: 2025

Institución:: Universidad Santo Tomás

Repositorio:: Repositorio Institucional USTA

Idioma:: spa

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dc.title.spa.fl_str_mv	Big data e inteligencia artificial, dos herramientas clave en procesos administrativos para instituciones de educación superior
title	Big data e inteligencia artificial, dos herramientas clave en procesos administrativos para instituciones de educación superior
spellingShingle	Big data e inteligencia artificial, dos herramientas clave en procesos administrativos para instituciones de educación superior Big Data Artificial Intelligence Administrative processes Student enrollment Enrollment processes Big Data Inteligencia Artificial Procesos administrativos Matriculación de estudiantes procesos de matrícula
title_short	Big data e inteligencia artificial, dos herramientas clave en procesos administrativos para instituciones de educación superior
title_full	Big data e inteligencia artificial, dos herramientas clave en procesos administrativos para instituciones de educación superior
title_fullStr	Big data e inteligencia artificial, dos herramientas clave en procesos administrativos para instituciones de educación superior
title_full_unstemmed	Big data e inteligencia artificial, dos herramientas clave en procesos administrativos para instituciones de educación superior
title_sort	Big data e inteligencia artificial, dos herramientas clave en procesos administrativos para instituciones de educación superior
dc.creator.fl_str_mv	Moreno Cardozo, Santiago Nicolás
dc.contributor.advisor.none.fl_str_mv	Botello Herrera, Antony Reynel
dc.contributor.author.none.fl_str_mv	Moreno Cardozo, Santiago Nicolás
dc.contributor.corporatename.spa.fl_str_mv	Universidad Santo Tomás
dc.subject.keyword.spa.fl_str_mv	Big Data Artificial Intelligence Administrative processes Student enrollment Enrollment processes
topic	Big Data Artificial Intelligence Administrative processes Student enrollment Enrollment processes Big Data Inteligencia Artificial Procesos administrativos Matriculación de estudiantes procesos de matrícula
dc.subject.proposal.spa.fl_str_mv	Big Data Inteligencia Artificial Procesos administrativos Matriculación de estudiantes procesos de matrícula
description	Ingeniero Informático
publishDate	2025
dc.date.accessioned.none.fl_str_mv	2025-01-20T16:32:34Z
dc.date.available.none.fl_str_mv	2025-01-20T16:32:34Z
dc.type.local.spa.fl_str_mv	Trabajo de grado
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dc.identifier.citation.spa.fl_str_mv	Moreno Cardozo, S. N. (2024). Big data e inteligencia artificial, dos herramientas clave en procesos administrativos para instituciones de educación superior. [Trabajo de Grado, Universidad Santo Tomás]. Repositorio Institucional.
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identifier_str_mv	Moreno Cardozo, S. N. (2024). Big data e inteligencia artificial, dos herramientas clave en procesos administrativos para instituciones de educación superior. [Trabajo de Grado, Universidad Santo Tomás]. Repositorio Institucional. reponame:Repositorio Institucional Universidad Santo Tomás instname:Universidad Santo Tomás repourl:https://repository.usta.edu.co
url	http://hdl.handle.net/11634/59101
dc.language.iso.spa.fl_str_mv	spa
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dc.relation.references.spa.fl_str_mv	L. M. Castro Benavides, J. A. Tamayo Arias, M. D. Arango Serna, J. W. Branch Bedoya, and D. Burgos, “Digital Transformation in Higher Education Institutions: A Systematic Literature Review,” Sensors 2020, Vol. 20, Page 3291, vol. 20, no. 11, p. 3291, Jun. 2020, doi: 10.3390/S20113291. M. Akour and M. Alenezi, “Higher Education Future in the Era of Digital Transformation,” Education Sciences 2022, Vol. 12, Page 784, vol. 12, no. 11, p. 784, Nov. 2022, doi: 10.3390/EDUCSCI12110784. P. Arcia, “VISIÓN PROSPECTIVA DE LA COMPLEJIDAD DEL PROCESO ADMINISTRATIVO EN LA GERENCIA EDUCACIONAL,” 2020. S. He, X. Li, and J. Chen, “Application of Data Mining in Predicting College Graduates Employment,” in 2021 4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021, Institute of Electrical and Electronics Engineers Inc., May 2021, pp. 65– 69. doi: 10.1109/ICAIBD51990.2021.9459039. C. Guan, J. Mou, and Z. Jiang, “Artificial intelligence innovation in education: A twenty-year data-driven historical analysis,” International Journal of Innovation Studies, vol. 4, no. 4, pp. 134–147, Dec. 2020, doi: 10.1016/j.ijis.2020.09.001. T. Lan and M. Li, “Design of college digital enrollment System based on big data platform in digital communication era,” in Proceedings - 2022 6th International Conference on Wireless Communications and Applications, ICWCAPP 2022, Institute of Electrical and Electronics Engineers Inc., 2022, pp. 196–200. doi: 10.1109/ICWCAPP57292.2022.00055. J. Lei and G. Huang, “Smart Management System of Employment in Universities Based on Big Data Collection and Intelligent Analysis,” in Proceedings of the 5th International Conference on Trends in Electronics and Informatics, ICOEI 2021, Institute of Electrical and Electronics Engineers Inc., Jun. 2021, pp. 1110–1113. doi: 10.1109/ICOEI51242.2021.9453076. Y. Si and B. Wu, “Construction and Management Method of University Information Platform Based on Big Data Technology,” Mobile Information Systems, vol. 2022, 2022, doi: 10.1155/2022/7674573. C. Gürkut, A. Elçi, and M. Nat, “An enriched decision-making satisfaction model for student information management systems,” International Journal of Information Management Data Insights, vol. 3, no. 2, Nov. 2023, doi: 10.1016/j.jjimei.2023.100195. J. Zhu, “AI ethics with Chinese characteristics? Concerns and preferred solutions in Chinese academia,” AI Soc, vol. 39, no. 3, pp. 1261–1274, Jun. 2024, doi: 10.1007/s00146- 022-01578-w. J. Zhu, “Innovative Exploration of the Integration Path of Artificial Intelligence Ethics and College Students’ Ideological and Political Education,” Applied Mathematics and Nonlinear Sciences, vol. 9, no. 1, Jan. 2024, doi: 10.2478/amns-2024-2280. M. J. Page et al., “The PRISMA 2020 statement: an updated guideline for reporting systematic reviews,” BMJ, vol. 372, Mar. 2021, doi: 10.1136/BMJ.N71. Charles Sturt University, “Systematic literature reviews - Literature Review - Library Guides at Charles Sturt University.” Accessed: Oct. 22, 2024. [Online]. Available: https://libguides.csu.edu.au/review/Systematic. M. Barrett et al., “Using Artificial Intelligence to Enhance Educational Opportunities and Student Services in Higher Education,” Inquiry: The Journal of the Virginia Community Colleges, vol. 22, no. 1, Jul. 2019, Accessed: Nov. 05, 2024. [Online]. Available: https://commons.vccs.edu/inquiry/vol22/iss1/11 K. Akrami, M. Akrami, F. Akrami, and M. Hakimi, “Investigating the Integration of Big Data Technologies in Higher Education Settings,” Indonesian Journal of Multidisciplinary on Social and Technology, vol. 2, no. 2, pp. 1–12, Jun. 2024, doi: 10.31004/ijmst.v2i2.296. N. R. Haddaway, L. A. McGuinness, C. C. Pritchard, and M. J. Page, “PRISMA Flow Diagram.” Accessed: Oct. 27, 2024. [Online]. Available: https://estech.shinyapps.io/prisma_flowdiagram/ Y. Yang, “Construction of Monitoring System for Student Growth Evaluation under the Background of Big Data,” in Proceedings - 2022 International Conference on Information System, Computing and Educational Technology, ICISCET 2022, Institute of Electrical and Electronics Engineers Inc., 2022, pp. 98–101. doi: 10.1109/ICISCET56785.2022.00033. H. Zhai, “Innovation and Practice of Educational Management Path Building in Colleges and Universities in the Context of Big Data,” Applied Mathematics and 15 Nonlinear Sciences, vol. 9, no. 1, Jan. 2024, doi: 10.2478/amns.2023.2.01180. T. N. De Oliveira, F. Bernardini, and J. Viterbo, “An Overview on the Use of Educational Data Mining for Constructing Recommendation Systems to Mitigate Retention in Higher Education,” in Proceedings - Frontiers in Education Conference, FIE, Institute of Electrical and Electronics Engineers Inc., 2021. doi: 10.1109/FIE49875.2021.9637207. K. Gupta, K. Gupta, P. Dwivedi, and M. Chaudhry, “Binary Classification of Students’ Dropout Behaviour in Universities using Machine Learning Algorithms,” IEEE, 2024. N. Ndou, R. Ajoodha, and A. Jadhav, “Educational Data-mining to Determine Student Success at Higher Education Institutions,” in 2020 2nd International Multidisciplinary Information Technology and Engineering Conference, IMITEC 2020, Institute of Electrical and Electronics Engineers Inc., Nov. 2020. doi: 10.1109/IMITEC50163.2020.9334139. B. Assiri, M. Bashraheel, and A. Alsuri, “Improve the Accuracy of Students Admission at Universities Using Machine Learning Techniques,” in Proceedings - 2022 7th International Conference on Data Science and Machine Learning Applications, CDMA 2022, Institute of Electrical and Electronics Engineers Inc., 2022, pp. 127–132. doi: 10.1109/CDMA54072.2022.00026. Y. Bao, Y. Sun, and L. He, “Research on the Design of Intelligent Enrollment System for Open Universities,” in Proceedings - 2023 7th International Symposium on Computer Science and Intelligent Control, ISCSIC 2023, Institute of Electrical and Electronics Engineers Inc., 2023, pp. 401–403. doi: 10.1109/ISCSIC60498.2023.00088. T. Zhang and Q. Liu, “Student Achievement Analysis and Prediction Based on Educational Data,” in Proceedings - 2022 4th International Conference on Intelligent Information Processing, IIP 2022, Institute of Electrical and Electronics Engineers Inc., 2022, pp. 245–249. doi: 10.1109/IIP57348.2022.00057. H. Zeineddine, U. Braendle, and A. Farah, “Enhancing prediction of student success: Automated machine learning approach,” Computers and Electrical Engineering, vol. 89, Jan. 2021, doi: 10.1016/j.compeleceng.2020.106903. N. Sghir, A. Adadi, Z. A. El Mouden, and M. Lahmer, “Using Learning Analytics to Improve Students’ Enrollments in Higher Education,” in 2022 2nd International Conference on Innovative Research in Applied Science, Engineering and Technology, IRASET 2022, Institute of Electrical and Electronics Engineers Inc., 2022. doi: 10.1109/IRASET52964.2022.9737993. B. Ujkani, D. Minkovska, and L. Stoyanova, “A Machine Learning Approach for Predicting Student Enrollment in the University,” in 2021 30th International Scientific Conference Electronics, ET 2021 - Proceedings, Institute of Electrical and Electronics Engineers Inc., Sep. 2021. doi: 10.1109/ET52713.2021.9579795. J. Domingo-Alejo, “AI Integrated Administration tool design with ML Technology for Smart Education System,” in 2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2024, Institute of Electrical and Electronics Engineers Inc., 2024, pp. 1423–1428. doi: 10.1109/ICACITE60783.2024.10616455. A. Kalakova, Y. Amanbek, R. Kairgeldin, and G. Kalakova, “Classification and prediction of Student’s Enrollment to Kazakhstanis Universities Using Characteristics of Applicant and Testing Results,” in SIST 2021 - 2021 IEEE International Conference on Smart Information Systems and Technologies, Institute of Electrical and Electronics Engineers Inc., Apr. 2021. doi: 10.1109/SIST50301.2021.9465929. B. Huang, “Construction and Application of a Modern Comprehensive Education 16 Management System in Universities Aimed at Fostering Virtue Through Education,” International Journal of Cognitive Informatics and Natural Intelligence, vol. 18, no. 1, 2024, doi: 10.4018/IJCINI.343630. M. V. Martins, L. Baptista, J. Machado, and V. Realinho, “Multi-Class Phased Prediction of Academic Performance and Dropout in Higher Education,” Applied Sciences (Switzerland), vol. 13, no. 8, Apr. 2023, doi: 10.3390/app13084702. “VOSviewer - Visualizing scientific landscapes.” Accessed: Oct. 27, 2024. [Online]. Available: https://www.vosviewer.com/ T. Wang et al., “Exploring the Potential Impact of Artificial Intelligence (AI) on International Students in Higher Education: Generative AI, Chatbots, Analytics, and International Student Success,” Applied Sciences 2023, Vol. 13, Page 6716, vol. 13, no. 11, p. 6716, May 2023, doi: 10.3390/APP13116716. M. E. Barzola, “Migración semiautomática de sistemas Legacy hacia arquitecturas orientadas a servicios,” 2017, Accessed: Oct. 27, 2024. [Online]. Available: http://sedici.unlp.edu.ar/handle/10915/82154 G. Mohamed et al., “Streamlining Student Support: Enhancing Administrative Assistance and Interaction Through a Chatbot Solution,” pp. 69–80, 2024, doi: 10.1007/978-3-031-50300-9_4. IBM, “¿Qué es un chatbot? \| IBM.” Accessed: Oct. 07, 2024. [Online]. Available: https://www.ibm.com/es-es/topics/chatbots A. S. AL-Malaise AL-Ghamdi, M. Ragab, and M. F. S. Sabir, “Enhanced artificial intelligence-based cybersecurity intrusion detection for higher education institutions,” Computers, Materials and Continua, vol. 72, no. 2, pp. 2895–2907, 2022, doi: 10.32604/cmc.2022.026405. S. Molina Gonzáles, “Mecanismos de Seguridad para el Diseño de Desarrollo Web,” 2024. S. Ordoñez Tumbo, K. Márceles Villalba, and S. 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Rodzi et al., “Unraveling the Complexity: A DEMATEL Analysis of the Negative Impact of Artificial Intelligence (AI) Adoption among Students in Higher Education,” Journal of Intelligent Systems and Internet of Things, vol. 11, no. 2, pp. 30–41, 2024, doi: 10.54216/JISIoT.110203. N. Segovia-García, “Optimizing Student Support: A Review of the Use of AI Chatbots in Higher Education,” European Public and Social Innovation Review, vol. 9, Jun. 2024, doi: 10.31637/epsir-2024-324. P. S. Venkateswaran, F. T. M. Ayasrah, V. K. Nomula, P. Paramasivan, P. Anand, and K. Bogeshwaran, “Applications of Artificial Intelligence Tools in Higher Education,” https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-2193-5.ch008, pp. 124–136, Jan. 2024, doi: 10.4018/979-8-3693-2193-5.CH008 “Ciberseguridad en la Eduacación: Discute los desafíos de seguridad que enfrentan las instituciones eduactivas y cómo pueden proteger la información confidencial de estudiantes y personal. - Revista Enred - Noticias de Tecnología y Negocios Ecuador.” Accessed: Nov. 09, 2024. [Online]. Available: https://www.enred.ec/ciberseguridad-enla-eduacacion-discute-los-desafios-de-seguridad-que-enfrentan-las-institucioneseduactivas-y-como-pueden-proteger-la-informacion-confidencial-de-estudiantes-ypersonal/ M. Sinha, “Balancing Education and Cybersecurity: Addressing Data Privacy Challenges in Schools and Higher Education,” International Journal of Engineering Fields, ISSN: 3078-4425, vol. 2, no. 2, pp. 43–49, Apr. 2024, Accessed: Nov. 09, 2024. [Online]. Available: https://journalofengineering.org/index.php/ijef/article/view/17
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spelling	Botello Herrera, Antony ReynelMoreno Cardozo, Santiago NicolásUniversidad Santo Tomás2025-01-20T16:32:34Z2025-01-20T16:32:34ZMoreno Cardozo, S. N. (2024). Big data e inteligencia artificial, dos herramientas clave en procesos administrativos para instituciones de educación superior. [Trabajo de Grado, Universidad Santo Tomás]. Repositorio Institucional.http://hdl.handle.net/11634/59101reponame:Repositorio Institucional Universidad Santo Tomásinstname:Universidad Santo Tomásrepourl:https://repository.usta.edu.coapplication/pdfspaUniversidad Santo TomásIngeniería InformáticaFacultad de Ingeniería de SistemasAtribución-NoComercial-SinDerivadas 2.5 ColombiaAtribución-NoComercial-SinDerivadas 2.5 Colombiahttp://creativecommons.org/licenses/by-nc-nd/2.5/co/Abierto (Texto Completo)info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Big data e inteligencia artificial, dos herramientas clave en procesos administrativos para instituciones de educación superiorIngeniero InformáticoPregradoBig DataArtificial IntelligenceAdministrative processesStudent enrollmentEnrollment processesBig DataInteligencia ArtificialProcesos administrativosMatriculación de estudiantesprocesos de matrículaTrabajo de gradoinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_7a1finfo:eu-repo/semantics/bachelorThesisCRAI-USTA TunjaL. M. Castro Benavides, J. A. Tamayo Arias, M. D. Arango Serna, J. W. Branch Bedoya, and D. Burgos, “Digital Transformation in Higher Education Institutions: A Systematic Literature Review,” Sensors 2020, Vol. 20, Page 3291, vol. 20, no. 11, p. 3291, Jun. 2020, doi: 10.3390/S20113291.M. Akour and M. Alenezi, “Higher Education Future in the Era of Digital Transformation,” Education Sciences 2022, Vol. 12, Page 784, vol. 12, no. 11, p. 784, Nov. 2022, doi: 10.3390/EDUCSCI12110784.P. Arcia, “VISIÓN PROSPECTIVA DE LA COMPLEJIDAD DEL PROCESO ADMINISTRATIVO EN LA GERENCIA EDUCACIONAL,” 2020.S. He, X. Li, and J. Chen, “Application of Data Mining in Predicting College Graduates Employment,” in 2021 4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021, Institute of Electrical and Electronics Engineers Inc., May 2021, pp. 65– 69. doi: 10.1109/ICAIBD51990.2021.9459039.C. Guan, J. Mou, and Z. Jiang, “Artificial intelligence innovation in education: A twenty-year data-driven historical analysis,” International Journal of Innovation Studies, vol. 4, no. 4, pp. 134–147, Dec. 2020, doi: 10.1016/j.ijis.2020.09.001.T. Lan and M. Li, “Design of college digital enrollment System based on big data platform in digital communication era,” in Proceedings - 2022 6th International Conference on Wireless Communications and Applications, ICWCAPP 2022, Institute of Electrical and Electronics Engineers Inc., 2022, pp. 196–200. doi: 10.1109/ICWCAPP57292.2022.00055.J. Lei and G. Huang, “Smart Management System of Employment in Universities Based on Big Data Collection and Intelligent Analysis,” in Proceedings of the 5th International Conference on Trends in Electronics and Informatics, ICOEI 2021, Institute of Electrical and Electronics Engineers Inc., Jun. 2021, pp. 1110–1113. doi: 10.1109/ICOEI51242.2021.9453076.Y. Si and B. Wu, “Construction and Management Method of University Information Platform Based on Big Data Technology,” Mobile Information Systems, vol. 2022, 2022, doi: 10.1155/2022/7674573.C. Gürkut, A. Elçi, and M. Nat, “An enriched decision-making satisfaction model for student information management systems,” International Journal of Information Management Data Insights, vol. 3, no. 2, Nov. 2023, doi: 10.1016/j.jjimei.2023.100195.J. Zhu, “AI ethics with Chinese characteristics? Concerns and preferred solutions in Chinese academia,” AI Soc, vol. 39, no. 3, pp. 1261–1274, Jun. 2024, doi: 10.1007/s00146- 022-01578-w.J. Zhu, “Innovative Exploration of the Integration Path of Artificial Intelligence Ethics and College Students’ Ideological and Political Education,” Applied Mathematics and Nonlinear Sciences, vol. 9, no. 1, Jan. 2024, doi: 10.2478/amns-2024-2280.M. J. Page et al., “The PRISMA 2020 statement: an updated guideline for reporting systematic reviews,” BMJ, vol. 372, Mar. 2021, doi: 10.1136/BMJ.N71.Charles Sturt University, “Systematic literature reviews - Literature Review - Library Guides at Charles Sturt University.” Accessed: Oct. 22, 2024. [Online]. Available: https://libguides.csu.edu.au/review/Systematic.M. Barrett et al., “Using Artificial Intelligence to Enhance Educational Opportunities and Student Services in Higher Education,” Inquiry: The Journal of the Virginia Community Colleges, vol. 22, no. 1, Jul. 2019, Accessed: Nov. 05, 2024. [Online]. Available: https://commons.vccs.edu/inquiry/vol22/iss1/11K. Akrami, M. Akrami, F. Akrami, and M. Hakimi, “Investigating the Integration of Big Data Technologies in Higher Education Settings,” Indonesian Journal of Multidisciplinary on Social and Technology, vol. 2, no. 2, pp. 1–12, Jun. 2024, doi: 10.31004/ijmst.v2i2.296.N. R. Haddaway, L. A. McGuinness, C. C. Pritchard, and M. J. Page, “PRISMA Flow Diagram.” Accessed: Oct. 27, 2024. [Online]. Available: https://estech.shinyapps.io/prisma_flowdiagram/Y. Yang, “Construction of Monitoring System for Student Growth Evaluation under the Background of Big Data,” in Proceedings - 2022 International Conference on Information System, Computing and Educational Technology, ICISCET 2022, Institute of Electrical and Electronics Engineers Inc., 2022, pp. 98–101. doi: 10.1109/ICISCET56785.2022.00033.H. Zhai, “Innovation and Practice of Educational Management Path Building in Colleges and Universities in the Context of Big Data,” Applied Mathematics and 15 Nonlinear Sciences, vol. 9, no. 1, Jan. 2024, doi: 10.2478/amns.2023.2.01180.T. N. De Oliveira, F. Bernardini, and J. Viterbo, “An Overview on the Use of Educational Data Mining for Constructing Recommendation Systems to Mitigate Retention in Higher Education,” in Proceedings - Frontiers in Education Conference, FIE, Institute of Electrical and Electronics Engineers Inc., 2021. doi: 10.1109/FIE49875.2021.9637207.K. Gupta, K. Gupta, P. Dwivedi, and M. Chaudhry, “Binary Classification of Students’ Dropout Behaviour in Universities using Machine Learning Algorithms,” IEEE, 2024.N. Ndou, R. Ajoodha, and A. Jadhav, “Educational Data-mining to Determine Student Success at Higher Education Institutions,” in 2020 2nd International Multidisciplinary Information Technology and Engineering Conference, IMITEC 2020, Institute of Electrical and Electronics Engineers Inc., Nov. 2020. doi: 10.1109/IMITEC50163.2020.9334139.B. Assiri, M. Bashraheel, and A. 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Big data e inteligencia artificial, dos herramientas clave en procesos administrativos para instituciones de educación superior

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