Mostrar el registro sencillo del ítem

Prediction of the quality of university life through data mining techniques

Predicción de la calidad de vida universitaria a través de minería de datos

dc.contributor.authorIbáñez Ramírez, Johan Sebastián
dc.contributor.authorEcheverri Salazar, Tatiana
dc.contributor.authorCastrillón Gómez, Omar Danilo
dc.date.accessioned2023-11-28T18:29:25Z
dc.date.available2023-11-28T18:29:25Z
dc.date.created2021-09-21
dc.identifier.issn1692-3324
dc.identifier.urihttp://hdl.handle.net/11407/8208
dc.descriptionThe objective of this article is to measure through intelligent techniques, the quality of university life in a university population. In this investigation, a dependent variable called quality of university life is taken, as well as 10 independent variables: Academic load, economic resources, relationship with classmates, relationship with professors, curriculum, extracurricular activities, current housing, family relationships, emotional state and university environment. In the samplings of these variables, 127 surveys were carried out on university students of a public university located in the central region of Colombia. Subsequently, the most relevant variables were selected throughout statistical techniques, in order to establish a file to be analyzed through the decision tree classification algorithm J48from the Weka platform. The results show, with over an 80 % effectiveness, that the most influential variables in the quality of life of a university student are: University environment, current housing, emotional state, and relationships with professors. Finding a lot of times that the quality of university life can also depend of external variables to the university such as: Current housing and emotional state. These results are of great importance in the design of new university policies.eng
dc.descriptionEl objetivo de este artículo es medir a través de técnicas inteligentes el nivel de vida universitaria de una población universitaria. En esta investigación, una variable dependiente llamada calidad de vida universitaria se toma en cuenta junto con 10 variables independientes: carga académica, recursos económicos, relación con compañeros de clase, relación con docentes, currículum, actividades extracurriculares, vivienda actual, relaciones familiares, estado emocional y entorno universitario. Para el muestreo de estas variables se llevaron a cabo 127 encuestas a estudiantes de una universidad pública ubicada en la región central del país. Subsecuentemente, las variables más relevantes fueron seleccionadas a través de técnicas estadísticas con el fin de establecer un archivo de análisis desde el algoritmo de clasificación de árbol de decisiones J48 de la plataforma Weka. EL resultado demuestra, con una efectividad de más del 80 % que las variables más influyentes en la calidad de vida universitaria son: entorno universitario, vivienda actual, estado emocional y relación con los docentes, encontrando, varias veces, que la calidad de vida también puede depender de variables externas a la universidad, tales como: vivienda actual y estado emocional. Estos resultados son de gran importancia en el diseño de las políticas universitarias por venir.spa
dc.formatPDF
dc.format.extentp. 1-14
dc.format.mediumElectrónico
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherUniversidad de Medellín
dc.relation.ispartofseriesRevista Ingenierías Universidad de Medellín; Vol. 21 No. 40 (2022)
dc.relation.haspartRevista Ingenierías Universidad de Medellín; Vol. 21 Núm. 40 enero-junio 2022
dc.relation.urihttps://revistas.udem.edu.co/index.php/ingenierias/article/view/3376
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0*
dc.sourceRevista Ingenierías Universidad de Medellín; Vol. 21 No. 40 (2022): (enero-junio); 1-14
dc.subjectQuality of university lifeeng
dc.subjectIntelligent techniqueseng
dc.subjectStatistical techniqueseng
dc.subjectCalidad de vida universitariaspa
dc.subjectTécnicas de vida universitariasspa
dc.subjectTécnicas estadísticasspa
dc.titlePrediction of the quality of university life through data mining techniqueseng
dc.titlePredicción de la calidad de vida universitaria a través de minería de datosspa
dc.typearticle
dc.identifier.doihttps://doi.org/10.22395/rium.v21n40a1
dc.relation.citationvolume21
dc.relation.citationissue40
dc.relation.citationstartpage1
dc.relation.citationendpage14
dc.audienceComunidad Universidad de Medellín
dc.publisher.facultyFacultad de Ingenierías
dc.coverageLat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degreesLong: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees
dc.publisher.placeMedellín
dc.relation.referencesONU, (2012). “ONU examina relación entre felicidad y desarrollo”.Available in: https://news.un.org/es/story/2012/04/1238601.
dc.relation.referencesDatu, J., King, R., and Valdez, J. “The Academic Rewards of Socially-Oriented Happiness: Interdependent Happiness Promotes Academic Engagement”. Journal of School Psychology, vol. 61, pp. 19–31, 2017.
dc.relation.referencesRamírez, P., Fuentes, C. (2013). “Felicidad y Rendimiento Académico: Efecto Moderador de la Felicidad sobre Indicadores de Selección y Rendimiento Académico de Alumnos de Ingeniería Comercial”. Formación Universitaria, vol. 6, no. 3, pp. 21–30. doi: http://dx.doi.org/10.4067/S0718-50062013000300004.
dc.relation.referencesHabibzadeh, S. and Allahvirdiyani, K. (2011). “Effects of economic and non economic factors on happiness on primary school teachers and Urmia University professors”.,vol. 30, pp. 2050–2051. doi: https://doi.org/10.1016/j.sbspro.2011.10.397.
dc.relation.referencesKamthan, S., et al. (2019). “Happiness among second year MBBS students and its correlates using Oxford Happiness Questionnaire”, Journal of Oral Biology and Craniofacial Research, vol. 9, pp. 190–192. doi: https://doi.org/10.1016/j.jobcr.2018.06.003.
dc.relation.referencesTalebzadeh, F. and Samkan M. (2011). “Happiness for our kids in schools: A conceptual model”, Procedia - Social and Behavioral Sciences, vol. 29, pp. 1462–1471. doi: https://doi.org/10.1016/j.sbspro.2011.11.386.
dc.relation.referencesChan G., Miller, P. and Tcha, M. (2005). “Happiness In University Education”. International Review of Economics Education, vol. 4, pp. 20–45. doi: https://doi.org/10.1016/S1477-3880(15)30139-0.
dc.relation.referencesVigneswaran Applasamy, V., et al. (2014). “Measuring Happiness in Academic Environment: A Case Study of the School Of Engineering at Taylor’s University (Malaysia)”. Procedia -Social and Behavioral Sciences, vol. 123, pp. 106–112. doi: 10.1016/j.sbspro.2014.01.1403.
dc.relation.referencesAziz. R., et al. (2014). “Personality and happiness among academicians in Malaysia”. Procedia - Social and Behavioral Sciences, vol. 116, pp. 4209–4212. doi: https://doi.org/10.1016/j.sbspro.2014.01.
dc.relation.referencesÖztürk A. and Mutlu, T. (2010). “The relationship between attachment style, subjectivewell-being, happiness and social anxiety among university students’”. Procedia Social and Behavioral Sciences. vol. 9, pp. 1772–1776. doi: https://doi.org/10.1016/j.sbspro.2010.12.398.
dc.relation.referencesMoeinaddini, M., et al. (2020). “Proposing a New Score to Measure Personal Happiness by Identifying the Contributing Factors”. Measurement, vol. 151, 107-115.doi: https://doi.org/10.1016/j.measurement.2019.107115.
dc.relation.referencesMangaraj, B.K. and Aparajita, U. (2020). “Constructing a generalized model of the human development index”. Socio-Economic Planning Sciencesvol. 70, 100778. doi: https://doi.org/10.1016/j.seps.2019.100778.
dc.relation.referencesKaragiannis, R. and Karagiannis, G. (2020). “Constructing composite indicators with Shannon entropy: The case of Human Development Index”. Socio-Economic Planning Sciences, vol. 70, 100701. doi: https://doi.org/10.1016/j.seps.2019.03.007.
dc.relation.referencesPinar M., Stengos, T. and Topaloglou, N. (2017). “Testing for the implicit weights of the dimensions of the Human Development Index using stochastic dominance”. Economics Letters. vol. 161, pp. 38–42. doi: https://doi.org/10.1016/j.econlet.2017.09.023.
dc.relation.referencesChen l., Cai, W., and Ma, M. (2020) “Decoupling or delusion? Mapping carbon emission percapita based on the human development index in Southwest China”. Science of The Total Environment. vol. 741, 138722. doi: https://doi.org/10.1016/j.scitotenv.2020.138722.
dc.relation.referencesRiahi M., et al. (2018). “Diarrhea deaths in children among countries with different levels of the human development index”. Data in Brief, vol. 17, pp. 954–960. doi: https://doi.org/10.1016/j.dib.2018.02.019.
dc.relation.referencesSarkodie, S.A., and Adams, S. (2020). “Electricity access, human development index,governance and income inequality in Sub-Saharan Africa”. Energy Reports, vol. 6, pp.455–466.doi: https://doi.org/10.1016/j.egyr.2020.02.009.
dc.relation.referencesMartínez-Mesa J.,et al. (2017). “Exploring disparities in incidence and mortality rates of breast and gynecologic cancers according to the Human Development Index in the Pan-American region”. Public Health, vol. 149, pp. 81–88. doi: http://dx.doi.org/10.1016/j.puhe.2017.04.017.
dc.relation.referencesVeisani, Y., et al. (2018). “Global incidence and mortality rates in pancreatic cancer and the association with the Human Development Index: decomposition approach”. Public Health. vol. 156, pp. 87–91. doi: https://doi.org/10.1016/j.puhe.2017.12.015.
dc.relation.referencesHwang, Y-H, and Hsiao, C-K, Lin, P-W. (2019). “Globally temporal transitions of blood lead levels of preschool children across countries of different categories of Human Development Index”. Science of the Total Environment, vol. 659, pp. 1395–1402. doi: https://doi.org/10.1016/j.scitotenv.2018.12.436.
dc.relation.referencesWang, Z., et al. (2018). “Renewable energy consumption, economic growth and human development index in Pakistan: Evidence form simultaneous equation model”. Journal of Cleaner Production, vol. 184, pp. 1081–1090.doi: https://doi.org/10.1016/j.jclepro.2018.02.260.
dc.relation.referencesMartínez-Guido, S., González-Campos, J., and Ponce-Ortega, J. (2019). “Strategic planning to improve the Human Development Index in disenfranchised communities through satisfying food, water and energy needs”. Food and Bioproducts Processing, vol. 117, pp. 14–29. doi: https://doi.org/10.1016/j.fbp.2019.06.007.
dc.relation.referencesKhazaei, S., et al. (2017). “Suicide rate in relation to the Human Development Index and other health related factors: A global ecological study from 91 countries”. Journal of Epidemiologyand Global Health, vol. 7, pp. 131–134. doi: http://dx.doi.org/10.1016/j.jegh.2016.12.002.
dc.relation.referencesLong, X., et al. (2020). “Sustainability evaluation based on the Three-dimensional Ecological Footprint and Human Development Index: A case study on the four island regions in China”.Journal of Environmental Management, vol. 265, 110509. doi: https://doi.org/10.1016/j.jenvman.2020.110509.
dc.relation.referencesYue, S., Shen, Y., and Yuan, J. (2019). “Sustainable total factor productivity growth for 55 states: An application of the new malmquist index considering ecological footprint and human development index”. Resources, Conservation & Recycling. vol. 146, pp. 475–483.doi: https://doi.org/10.1016/j.resconrec.2019.03.035.
dc.relation.referencesHickel, J. (2020). “The sustainable development index: Measuring the ecological efficiency of human development in the anthropocene”. Ecological Economics, vol. 167, 106331. doi: https://doi.org/10.1016/j.ecolecon.2019.05.011.
dc.relation.referencesBiggeri, M. and Mauro, V. (2018). “Towards a more ´Sustainable’ Human Development Index: Integrating the environment and freedom”. Ecological Indicators. vol. 91, pp. 220–231. doi: https://doi.org/10.1016/j.ecolind.2018.03.045.
dc.relation.referencesZhang, X. and P. Luo. (2021). “Analysis of psychological education factors based on computer software and hardware collaboration and data mining”. Microprocessors and Microsystems, vol. 81, 103744. doi: https://doi.org/10.1016/j.micpro.2020.
dc.relation.referencesRong, L. (2021). “Remote case teaching mode based on computer FPGA platform and data mining.” Microprocessors and Microsystems, vol. 83, 103986. doi: https://doi.org/10.1016/j.micpro.2021.
dc.relation.referencesLemay, D., C. Baek. and T. “Doleck, Comparison of learning analytics and educational data mining: A topic modeling approach”. Computers and Education: Artificial Intelligence, vol. 2, 100016. doi: https://doi.org/10.1016/j.caeai.2021.
dc.relation.referencesOmrani, H., Alizadeh, A. and Amini M. (2020). “A new approach based on BWM and MULTIMOORA methods for calculating semi-human development index: An application for provinces of Iran”. Socio-Economic Planning Sciences. vol. 70, 100689. doi: https://doi.org/10.1016/j.seps.2019.02.004.
dc.relation.references“Weka 3: Machine Learning Software in Java”. cs.waikato.ac.nz/. Available: https://www.cs.waikato.ac.nz/ml/weka/
dc.relation.referencesCastrillón O., W. Sarache and S. Ruiz. “Predicción del Rendimiento Académico por medio de Técnicas de Inteligencia Artificial”. Formación Universitaria, vol. 13, pp. 93–102, 2020.
dc.relation.referencesValdivieso, C.E., R. Valdivieso and O.A. Valdivieso. (2011). “Determinación del tamaño muestral mediante el uso de árboles de decisión”. UPB - Investigación & Desarrollo, vol.11, pp. 148–176. doi: 10.23881/idupbo.011.1-4e.
dc.relation.referencesValencia, M., J. Correa and F. Díaz. (2015). “Métodos estadísticos clásicos y bayesianos para el pronóstico de demanda. Un análisis comparativo”. Revista Facultad de Ciencias Universidad Nacional de Colombia, vol. 4, pp. 52–67. doi: https://doi.org/10.15446/rev.fac.cienc.v4n1.49775.
dc.rights.creativecommonsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.identifier.eissn2248-4094
dc.type.coarhttp://purl.org/coar/resource_type/c_6501
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.type.localArtículo científico
dc.type.driverinfo:eu-repo/semantics/article
dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellín
dc.identifier.repourlrepourl:https://repository.udem.edu.co/
dc.identifier.instnameinstname:Universidad de Medellín


Ficheros en el ítem

Thumbnail
Nombre:
Revista_Ingenierias_UdeM_424.pdf
Tamaño:
421.7Kb
Formato:
PDF
Ver/

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem

Attribution-NonCommercial-NoDerivatives 4.0 International
Excepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 International