Learning style preferences of college students using big data
Learning styles is one of the most studied topics in the field of education and the research results have generated relevant changes in the teaching-learning process. Currently, there are several theoretical models that explain the characterization and development of learning styles from different p...
- Autores:
-
amelec, viloria
Petro González, Ingrid Regina
Pineda Lezama, Omar Bonerge
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2019
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/5986
- Acceso en línea:
- https://hdl.handle.net/11323/5986
https://repositorio.cuc.edu.co/
- Palabra clave:
- Learning styles
College students
Different college careers
Estilos de aprendizaje
Estudiantes universitarios
Diferentes carreras universitarias
- Rights
- openAccess
- License
- CC0 1.0 Universal
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Learning style preferences of college students using big data |
| dc.title.translated.spa.fl_str_mv |
Preferencias de estilo de aprendizaje de estudiantes universitarios que usan big data |
| title |
Learning style preferences of college students using big data |
| spellingShingle |
Learning style preferences of college students using big data Learning styles College students Different college careers Estilos de aprendizaje Estudiantes universitarios Diferentes carreras universitarias |
| title_short |
Learning style preferences of college students using big data |
| title_full |
Learning style preferences of college students using big data |
| title_fullStr |
Learning style preferences of college students using big data |
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Learning style preferences of college students using big data |
| title_sort |
Learning style preferences of college students using big data |
| dc.creator.fl_str_mv |
amelec, viloria Petro González, Ingrid Regina Pineda Lezama, Omar Bonerge |
| dc.contributor.author.spa.fl_str_mv |
amelec, viloria Petro González, Ingrid Regina Pineda Lezama, Omar Bonerge |
| dc.subject.spa.fl_str_mv |
Learning styles College students Different college careers Estilos de aprendizaje Estudiantes universitarios Diferentes carreras universitarias |
| topic |
Learning styles College students Different college careers Estilos de aprendizaje Estudiantes universitarios Diferentes carreras universitarias |
| description |
Learning styles is one of the most studied topics in the field of education and the research results have generated relevant changes in the teaching-learning process. Currently, there are several theoretical models that explain the characterization and development of learning styles from different points of view, some of them share concepts, while others completely differ. The research focuses on the learning styles of higher education students for improving the quality of the educational process at the university. The results allow the recognize the learning style preferences of college students from different careers, and enable teachers to properly guide the learning activities by selecting the best teaching strategies, thus contributing to raise the quality of education. The results are expected to be relevant for further researches. |
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2019 |
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2020-02-05T13:27:58Z |
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2020-02-05T13:27:58Z |
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Corporación Universidad de la Costa |
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eng |
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Ebrahimzadeh, I., Shahraki, A., Shahnaz, A. y Myandoab, A. (2016) Progressing urban development and life quality simultaneously. City, Culture and Society 7, (3), 186-193. 9. Węziak-Białowolska, D. (2016) Quality of life in cities – Empirical evidence in comparative European perspective. Cities, 58, 87-96. 10.Putra, K. y Sitanggang, J. (2016). The Effect of Public Transport Services on Quality of Life in Medan City. Procedia - Social and Behavioral Sciences, 234, 383-389. oinformatics, 2018. Pineda Lezama, O., Gómez Dorta, R.: Techniques of multivariate statistical analysis: An application for the Honduran banking sector. Innovate: Journal of Science and Technology, 5 (2), 61-75 (2017). Viloria A., Lis-Gutierrez JP., Gaitán-Angulo M., Godoy A.R.M., Moreno G.C., Kamatkar S.J.: Methodology for the Design of a Student Pattern Recognition Tool to Facilitate the Teaching - Learning Process Through Knowledge Data Discovery (Big Data). In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, vol 10943. Springer, Cham (2018). A Lee, P Taylor, J Kalpathy-Cramer, A Tufail Machine learning has arrived!. Ophthalmology, 124 (2017), pp. 1726-1728 Yao L (2006). The present situation and development tendency of higher education quality evaluation in Western Countries. Priv. Educ. Beef. (2006). Gregorutti B, Michel B, Saint-Pierre P (2015) Grouped variable importance with random forests and application to multiple functional data analysis. Comput Stat Data Anal 90:15–35. Torres-Samuel, M., Vásquez, C., Viloria, A., Lis-Gutiérrez, J.P., Borrero, T.C., Varela, N.: Web Visibility Profiles of Top100 Latin American Universities. In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, Springer, Cham, vol 10943, 1-12 (2018). Jain, A. K., Mao, J., Mohiuddin, K. M.: Artificial neural networks: a tutorial. IEEE Computer 29 (3), 1- 32 (1996) Lee, S.-Y. (2007). Structural equation modeling: A Bayesian approach. West Sussex, England: John Wiley & Sons, Ltd. Haykin, S.: Neural Networks a Comprehensive Foundation. Second Edition. Macmillan College Publishing, Inc. USA. ISBN 9780023527616 (1999). R. Melero y F. Abad, «Revistas Open Access: Características, modelos económicos y tendencias,» Lámpsakos, pp. 12-23, 2001. M. Pinto, J. C. J. Alonso, V. Fernández, C. García, J. Garía, C. Gómez, F. Zazo y A.-V. Doucet, «Análisis cualitativo de la visibilidad de la investigación en las Universidaes españolas a través de su página Web,» Rev. Esp. Doc., pp. 345-370, 2004. M. Torres-Samuel, C. Vásquez, A. Viloria, L. Hernández-Fernandez y R. Portillo-Medina, «Analysis of patterns in the university Word Rankings Webometrics, Shangai, QS and SIR-Scimago: case Latin American» de Lectur Notes in Computer Science (Including subseries Lectur Notes in Artificial Intelligent and Lectur Notes in Bi |
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amelec, viloriaPetro González, Ingrid ReginaPineda Lezama, Omar Bonerge2020-02-05T13:27:58Z2020-02-05T13:27:58Z201900002010https://hdl.handle.net/11323/5986Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Learning styles is one of the most studied topics in the field of education and the research results have generated relevant changes in the teaching-learning process. Currently, there are several theoretical models that explain the characterization and development of learning styles from different points of view, some of them share concepts, while others completely differ. The research focuses on the learning styles of higher education students for improving the quality of the educational process at the university. The results allow the recognize the learning style preferences of college students from different careers, and enable teachers to properly guide the learning activities by selecting the best teaching strategies, thus contributing to raise the quality of education. The results are expected to be relevant for further researches.Los estilos de aprendizaje son uno de los temas más estudiados en el campo de la educación y los resultados de la investigación han generado cambios relevantes en el proceso de enseñanza-aprendizaje. Actualmente, existen varios modelos teóricos que explican la caracterización y el desarrollo de estilos de aprendizaje desde diferentes puntos de vista, algunos de ellos comparten conceptos, mientras que otros son completamente diferentes. La investigación se centra en los estilos de aprendizaje de los estudiantes de educación superior para mejorar la calidad del proceso educativo en la universidad. Los resultados permiten reconocer las preferencias de estilo de aprendizaje de los estudiantes universitarios de diferentes carreras y permiten a los maestros guiar adecuadamente las actividades de aprendizaje seleccionando las mejores estrategias de enseñanza, contribuyendo así a mejorar la calidad de la educación. Se espera que los resultados sean relevantes para futuras investigaciones.Amelec, Viloria-will be generated-orcid-0000-0003-2673-6350-600Petro González, Ingrid Regina-will be generated-orcid-0000-0003-1540-6081-600Pineda Lezama, Omar BonergeengProcedia Computer ScienceCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Learning stylesCollege studentsDifferent college careersEstilos de aprendizajeEstudiantes universitariosDiferentes carreras universitariasLearning style preferences of college students using big dataPreferencias de estilo de aprendizaje de estudiantes universitarios que usan big dataArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionEbrahimzadeh, I., Shahraki, A., Shahnaz, A. y Myandoab, A. (2016) Progressing urban development and life quality simultaneously. City, Culture and Society 7, (3), 186-193. 9.Węziak-Białowolska, D. (2016) Quality of life in cities – Empirical evidence in comparative European perspective. Cities, 58, 87-96. 10.Putra, K. y Sitanggang, J. (2016). The Effect of Public Transport Services on Quality of Life in Medan City. Procedia - Social and Behavioral Sciences, 234, 383-389. oinformatics, 2018.Pineda Lezama, O., Gómez Dorta, R.: Techniques of multivariate statistical analysis: An application for the Honduran banking sector. Innovate: Journal of Science and Technology, 5 (2), 61-75 (2017).Viloria A., Lis-Gutierrez JP., Gaitán-Angulo M., Godoy A.R.M., Moreno G.C., Kamatkar S.J.: Methodology for the Design of a Student Pattern Recognition Tool to Facilitate the Teaching - Learning Process Through Knowledge Data Discovery (Big Data). In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, vol 10943. Springer, Cham (2018).A Lee, P Taylor, J Kalpathy-Cramer, A Tufail Machine learning has arrived!. Ophthalmology, 124 (2017), pp. 1726-1728Yao L (2006). The present situation and development tendency of higher education quality evaluation in Western Countries. Priv. Educ. Beef. (2006).Gregorutti B, Michel B, Saint-Pierre P (2015) Grouped variable importance with random forests and application to multiple functional data analysis. Comput Stat Data Anal 90:15–35.Torres-Samuel, M., Vásquez, C., Viloria, A., Lis-Gutiérrez, J.P., Borrero, T.C., Varela, N.: Web Visibility Profiles of Top100 Latin American Universities. In: Tan Y., Shi Y., Tang Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science, Springer, Cham, vol 10943, 1-12 (2018).Jain, A. K., Mao, J., Mohiuddin, K. M.: Artificial neural networks: a tutorial. IEEE Computer 29 (3), 1- 32 (1996)Lee, S.-Y. (2007). Structural equation modeling: A Bayesian approach. West Sussex, England: John Wiley & Sons, Ltd.Haykin, S.: Neural Networks a Comprehensive Foundation. Second Edition. Macmillan College Publishing, Inc. USA. ISBN 9780023527616 (1999).R. Melero y F. Abad, «Revistas Open Access: Características, modelos económicos y tendencias,» Lámpsakos, pp. 12-23, 2001.M. Pinto, J. C. J. Alonso, V. Fernández, C. García, J. Garía, C. Gómez, F. Zazo y A.-V. Doucet, «Análisis cualitativo de la visibilidad de la investigación en las Universidaes españolas a través de su página Web,» Rev. Esp. Doc., pp. 345-370, 2004.M. Torres-Samuel, C. Vásquez, A. Viloria, L. Hernández-Fernandez y R. Portillo-Medina, «Analysis of patterns in the university Word Rankings Webometrics, Shangai, QS and SIR-Scimago: case Latin American» de Lectur Notes in Computer Science (Including subseries Lectur Notes in Artificial Intelligent and Lectur Notes in BiPublicationORIGINALLearning Style Preferences of College Students Using Big Data.pdfLearning Style Preferences of College Students Using Big Data.pdfapplication/pdf397098https://repositorio.cuc.edu.co/bitstreams/b5e532cb-7fa5-49d3-b859-5e668c4ea77c/download6cabaceb409810b8e32bd98b8246a289MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8701https://repositorio.cuc.edu.co/bitstreams/80f58cb1-d03e-4414-8c03-947675a3533a/download42fd4ad1e89814f5e4a476b409eb708cMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstreams/25709b80-12fc-4030-9441-7169041afc1e/download8a4605be74aa9ea9d79846c1fba20a33MD53THUMBNAILLearning Style Preferences of College Students Using Big Data.pdf.jpgLearning Style Preferences of College Students Using Big Data.pdf.jpgimage/jpeg46146https://repositorio.cuc.edu.co/bitstreams/458195ae-b936-46d0-87dc-33038c094bb7/download8ef159fde6103426fc68803bd876e00bMD55TEXTLearning Style Preferences of College Students Using Big Data.pdf.txtLearning Style Preferences of College Students Using Big Data.pdf.txttext/plain19363https://repositorio.cuc.edu.co/bitstreams/cf36f96b-b467-4ec8-bde8-98876c634b98/downloaddded0bdae584f1d0d800fb90eabf18d6MD5611323/5986oai:repositorio.cuc.edu.co:11323/59862024-09-17 14:17:55.52http://creativecommons.org/publicdomain/zero/1.0/CC0 1.0 Universalopen.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.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 |