Marco inteligente para el aprendizaje combinado

La personalización de la educación influye en la motivación de los estudiantes y mejora los resultados de las evaluaciones. Algunas herramientas informáticas han sido propuestas para automatizar la personalización tales como los tutores inteligentes de aprendizaje con excelentes resultados. Sin emba...

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Autores:: Ordóñez, Armando
Giraldo G., Martha
Muñoz, Freddy
Ordoñez, Hugo
Rosero, Yeni

Tipo de recurso:: Trabajo de grado de pregrado

Fecha de publicación:: 2018

Institución:: Universidad Autónoma de Bucaramanga - UNAB

Repositorio:: Repositorio UNAB

Idioma:: eng
spa

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dc.title.spa.fl_str_mv	Marco inteligente para el aprendizaje combinado
dc.title.translated.end.fl_str_mv	An Intelligent framework for Blended Learning
title	Marco inteligente para el aprendizaje combinado
spellingShingle	Marco inteligente para el aprendizaje combinado Intelligent Tutoring Framework Blended Learning Intelligent Tutoring Sistemas Desarrollo de tecnología Innovaciones tecnológicas Tutores inteligentes Framework Blended learning
title_short	Marco inteligente para el aprendizaje combinado
title_full	Marco inteligente para el aprendizaje combinado
title_fullStr	Marco inteligente para el aprendizaje combinado
title_full_unstemmed	Marco inteligente para el aprendizaje combinado
title_sort	Marco inteligente para el aprendizaje combinado
dc.creator.fl_str_mv	Ordóñez, Armando Giraldo G., Martha Muñoz, Freddy Ordoñez, Hugo Rosero, Yeni
dc.contributor.author.spa.fl_str_mv	Ordóñez, Armando Giraldo G., Martha Muñoz, Freddy Ordoñez, Hugo Rosero, Yeni
dc.subject.keywords.eng.fl_str_mv	Intelligent Tutoring Framework Blended Learning Intelligent Tutoring
topic	Intelligent Tutoring Framework Blended Learning Intelligent Tutoring Sistemas Desarrollo de tecnología Innovaciones tecnológicas Tutores inteligentes Framework Blended learning
dc.subject.lemb.spa.fl_str_mv	Sistemas Desarrollo de tecnología Innovaciones tecnológicas
dc.subject.proposal.spa.fl_str_mv	Tutores inteligentes Framework Blended learning
description	La personalización de la educación influye en la motivación de los estudiantes y mejora los resultados de las evaluaciones. Algunas herramientas informáticas han sido propuestas para automatizar la personalización tales como los tutores inteligentes de aprendizaje con excelentes resultados. Sin embargo, la mayoría de los trabajos existentes se centran en los estudiantes y dejan de lado a los docentes. En este trabajo, se presenta un framework de código abierto basado en un sistema de tutor inteligente. El framework busca reducir los costos de implantación y la complejidad de las interfaces. Igualmente, el framework considera la participación tanto de estudiantes como de docentes. El framework fue utilizado para construir un curso de matemática en primaria. El framework desarrollado servirá como base para modelar el aprendizaje en un curso SPOC.
publishDate	2018
dc.date.issued.none.fl_str_mv	2018-12-01
dc.date.accessioned.none.fl_str_mv	2020-10-27T00:20:00Z
dc.date.available.none.fl_str_mv	2020-10-27T00:20:00Z
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dc.relation.none.fl_str_mv	https://revistas.unab.edu.co/index.php/rcc/article/view/3441/2900 Https://revistas.unab.edu.co/index.php/rcc/article/view/3441/2892 /ref/Álvarez, A., Martín, M., Fernández-Castro, I., & Urretavizcaya, M. (2013). Blending traditional teaching methods with learning environments: Experience, cyclical evaluation process and impact with MAgAdI. Computers & Education, 68, 129–140. /ref/Castillo, S. (2008). Propuesta pedagógica basada en el constructivismo para el uso óptimo de las TIC en la enseñanza y el aprendizaje de la matemática. Revista Latinoamericana de Investigación En Matemática Educativa, 11(2), 171–194. /ref/Conde, D. C. R., & Soto, Á. P. G. (2012). Modelo de acción docente con medios informáticos y telemáticos. Pixel-Bit: Revista de Medios y Educación, (40), 151–170. /ref/Cook, R., Kay, J., & Kummerfeld, B. (2015). MOOClm: User Modelling for MOOCs (pp. 80–91). Springer, Cham. https://doi.org/10.1007/978-3-319-20267-9_7 /ref/Dolenc, K., & Aberšek, B. (2015). TECH8 intelligent and adaptive e-learning system: Integration into Technology and Science classrooms in lower secondary schools. Computers & Education, 82, 354–365. https://doi.org/10.1016/j.compedu.2014.12.010 /ref/Han, G., Lin, M., Li, C., & Ju, J. (2017). Flipped classroom teaching design based on SPOC in ordinary undergraduate college. In 2017 12th International Conference on Computer Science and Education (ICCSE) (pp. 617–620). IEEE. https://doi.org/10.1109/ICCSE.2017.8085566 /ref/Herder, E., Sosnovsky, S., & Dimitrova, V. (2017). Adaptive Intelligent Learning Environments. In Technology Enhanced Learning (pp. 109–114). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-02600-8_10 /ref/Hwang, G.-J., Sung, H.-Y., Hung, C.-M., Huang, I., & Tsai, C.-C. (2012). Development of a personalized educational computer game based on students’ learning styles. Educational Technology Research and Development, 60(4), 623–638. https://doi.org/10.1007/s11423-012-9241-x /ref/Kozma, R. B., & Vota, W. S. (2014). ICT in Developing Countries: Policies, Implementation, and Impact. In Handbook of Research on Educational Communications and Technology (pp. 885–894). New York, NY: Springer New York. https://doi.org/10.1007/978-1-4614-3185-5_72 /ref/Lane, H. C., Yacef, K., Mostow, J., & Pavlik, P. (Eds.). (2013). Artificial Intelligence in Education. Memphis: Springer. /ref/Laverde, A. C., Cifuentes, Y. S., & Rincón Rodríguez, H. Y. (2007). Toward an instructional design model based on learning objects. Educational Technology Research and Development, 55(6), 671–681. https://doi.org/https://doi.org/10.1007/s11423-007-9059-0 /ref/Nye, B. D. (2014). Barriers to ITS Adoption: A Systematic Mapping Study. In Intelligent Tutoring Systems (pp. 583–590). /ref/Nye, B. D. (2015). Intelligent Tutoring Systems by and for the Developing World: A Review of Trends and Approaches for Educational Technology in a Global Context. International Journal of Artificial Intelligence in Education, 25(2), 177–203. https://doi.org/10.1007/s40593-014-0028-6 /ref/Olney, A. M., D’Mello, S., Person, N., Cade, W., Hays, P., Williams, C., … Graesser, A. (2012). Guru: A computer tutor that models expert human tutors. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7315 LNCS, 256–261. https://doi.org/10.1007/978-3-642-30950-2_32 /ref/Perry, W. E. (2007). Effective Methods for Software Testing: Includes Complete Guidelines, Checklists, and Templates. John Wiley & Sons. /ref/Sottilare, R. A. (2012). Considerations in the development of an ontology for a generalized intelligent framework for tutoring. U.S. Army Research Laboratory - Human Research & Engineering Directorate, 19–25. /ref/Sottilare, R. A. (2018). A Comprehensive Review of Design Goals and Emerging Solutions for Adaptive Instructional Systems. Technology, Instruction, Cognition & Learning, 11(1), 5–38. /ref/Sottilare, R. A., Brawner, K. W., Goldberg, B. S., & Holden, H. K. (2012). The Generalized Intelligent Framework for Tutoring (GIFT). Orlando, FL: US Army Research Laboratory--Human Research \& Engineering Directorate (ARL-HRED), (October), 1–12. /ref/Sottilare, R. A., & Holden, H. K. (2013). Recommendations for Authoring , Instructional Strategies and Analysis for Intelligent Tutoring Systems ( ITS ): Towards the Development of a Generalized Intelligent Framework for Tutoring ( GIFT ). AIED 2013 Workshops Proceedings, 7, 150. /ref/Steenbergen-Hu, S., & Cooper, H. (2013). A meta-analysis of the effectiveness of intelligent tutoring systems on college students’ academic learning. Journal of Educational Psychology, 105(4), 970–987. https://doi.org/10.1037/a0032447 /ref/VanLehn, K. (2011). The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems. Educational Psychologist, 46(4), 197–221. https://doi.org/10.1080/00461520.2011.611369 /ref/Walkington, C., & Hayata, C. A. (2017). Designing learning personalized to students’ interests: balancing rich experiences with mathematical goals. ZDM, 49(4), 519–530. https://doi.org/10.1007/s11858-017-0842-z /ref/Wentzel, K. R., & Brophy, J. E. (2014). Motivating Students to Learn. Taylor and Francis.
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dc.publisher.none.fl_str_mv	Universidad Autónoma de Bucaramanga UNAB
publisher.none.fl_str_mv	Universidad Autónoma de Bucaramanga UNAB
dc.source.none.fl_str_mv	Revista Colombiana de Computación; Vol. 19 Núm. 2 (2018): Revista Colombiana de Computación; 37-45
institution	Universidad Autónoma de Bucaramanga - UNAB
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spelling	Ordóñez, Armando2e50e6fa-3c3c-488d-944b-6cb36c686033Giraldo G., Martha7e3e60a5-885d-4864-9cbd-6e40272dfab1Muñoz, Freddy6db42f5b-e871-4180-9523-666c0194d328Ordoñez, Hugo59723b6d-a099-4a8f-a247-46039c769f69Rosero, Yenid61265f1-f886-4141-94aa-90431b4392ef2020-10-27T00:20:00Z2020-10-27T00:20:00Z2018-12-012539-21151657-2831http://hdl.handle.net/20.500.12749/8838instname:Universidad Autónoma de Bucaramanga UNABrepourl:https://repository.unab.edu.co10.29375/25392115.3441La personalización de la educación influye en la motivación de los estudiantes y mejora los resultados de las evaluaciones. Algunas herramientas informáticas han sido propuestas para automatizar la personalización tales como los tutores inteligentes de aprendizaje con excelentes resultados. Sin embargo, la mayoría de los trabajos existentes se centran en los estudiantes y dejan de lado a los docentes. En este trabajo, se presenta un framework de código abierto basado en un sistema de tutor inteligente. El framework busca reducir los costos de implantación y la complejidad de las interfaces. Igualmente, el framework considera la participación tanto de estudiantes como de docentes. El framework fue utilizado para construir un curso de matemática en primaria. El framework desarrollado servirá como base para modelar el aprendizaje en un curso SPOC.Personalized education contributes to the motivation of the students and improves student performance. Some tools such as the Intelligent Tutoring Systems have been proposed to this purpose with excellent results. However, most of the existing works have given little attention to the role of the teachers. In this article, an open source framework based on a standard intelligent tutoring system is presented. The framework aims at reducing the implementation costs and the complexity of the interfaces, in addition, the framework considers the participation of teachers. The framework was used to create a math course for an elementary school student, and will be used as a basis for the personalization of a Small Private Online Course.application/pdfText/htmlengspaUniversidad Autónoma de Bucaramanga UNABhttps://revistas.unab.edu.co/index.php/rcc/article/view/3441/2900Https://revistas.unab.edu.co/index.php/rcc/article/view/3441/2892/ref/Álvarez, A., Martín, M., Fernández-Castro, I., & Urretavizcaya, M. (2013). Blending traditional teaching methods with learning environments: Experience, cyclical evaluation process and impact with MAgAdI. Computers & Education, 68, 129–140./ref/Castillo, S. (2008). Propuesta pedagógica basada en el constructivismo para el uso óptimo de las TIC en la enseñanza y el aprendizaje de la matemática. Revista Latinoamericana de Investigación En Matemática Educativa, 11(2), 171–194./ref/Conde, D. C. R., & Soto, Á. P. G. (2012). Modelo de acción docente con medios informáticos y telemáticos. Pixel-Bit: Revista de Medios y Educación, (40), 151–170./ref/Cook, R., Kay, J., & Kummerfeld, B. (2015). MOOClm: User Modelling for MOOCs (pp. 80–91). Springer, Cham. https://doi.org/10.1007/978-3-319-20267-9_7/ref/Dolenc, K., & Aberšek, B. (2015). TECH8 intelligent and adaptive e-learning system: Integration into Technology and Science classrooms in lower secondary schools. Computers & Education, 82, 354–365. https://doi.org/10.1016/j.compedu.2014.12.010/ref/Han, G., Lin, M., Li, C., & Ju, J. (2017). Flipped classroom teaching design based on SPOC in ordinary undergraduate college. In 2017 12th International Conference on Computer Science and Education (ICCSE) (pp. 617–620). IEEE. https://doi.org/10.1109/ICCSE.2017.8085566/ref/Herder, E., Sosnovsky, S., & Dimitrova, V. (2017). Adaptive Intelligent Learning Environments. In Technology Enhanced Learning (pp. 109–114). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-02600-8_10/ref/Hwang, G.-J., Sung, H.-Y., Hung, C.-M., Huang, I., & Tsai, C.-C. (2012). Development of a personalized educational computer game based on students’ learning styles. Educational Technology Research and Development, 60(4), 623–638. https://doi.org/10.1007/s11423-012-9241-x/ref/Kozma, R. B., & Vota, W. S. (2014). ICT in Developing Countries: Policies, Implementation, and Impact. In Handbook of Research on Educational Communications and Technology (pp. 885–894). New York, NY: Springer New York. https://doi.org/10.1007/978-1-4614-3185-5_72/ref/Lane, H. C., Yacef, K., Mostow, J., & Pavlik, P. (Eds.). (2013). Artificial Intelligence in Education. Memphis: Springer./ref/Laverde, A. C., Cifuentes, Y. S., & Rincón Rodríguez, H. Y. (2007). Toward an instructional design model based on learning objects. Educational Technology Research and Development, 55(6), 671–681. https://doi.org/https://doi.org/10.1007/s11423-007-9059-0/ref/Nye, B. D. (2014). Barriers to ITS Adoption: A Systematic Mapping Study. In Intelligent Tutoring Systems (pp. 583–590)./ref/Nye, B. D. (2015). Intelligent Tutoring Systems by and for the Developing World: A Review of Trends and Approaches for Educational Technology in a Global Context. International Journal of Artificial Intelligence in Education, 25(2), 177–203. https://doi.org/10.1007/s40593-014-0028-6/ref/Olney, A. M., D’Mello, S., Person, N., Cade, W., Hays, P., Williams, C., … Graesser, A. (2012). Guru: A computer tutor that models expert human tutors. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7315 LNCS, 256–261. https://doi.org/10.1007/978-3-642-30950-2_32/ref/Perry, W. E. (2007). Effective Methods for Software Testing: Includes Complete Guidelines, Checklists, and Templates. John Wiley & Sons./ref/Sottilare, R. A. (2012). Considerations in the development of an ontology for a generalized intelligent framework for tutoring. U.S. Army Research Laboratory - Human Research & Engineering Directorate, 19–25./ref/Sottilare, R. A. (2018). A Comprehensive Review of Design Goals and Emerging Solutions for Adaptive Instructional Systems. Technology, Instruction, Cognition & Learning, 11(1), 5–38./ref/Sottilare, R. A., Brawner, K. W., Goldberg, B. S., & Holden, H. K. (2012). The Generalized Intelligent Framework for Tutoring (GIFT). Orlando, FL: US Army Research Laboratory--Human Research \& Engineering Directorate (ARL-HRED), (October), 1–12./ref/Sottilare, R. A., & Holden, H. K. (2013). Recommendations for Authoring , Instructional Strategies and Analysis for Intelligent Tutoring Systems ( ITS ): Towards the Development of a Generalized Intelligent Framework for Tutoring ( GIFT ). AIED 2013 Workshops Proceedings, 7, 150./ref/Steenbergen-Hu, S., & Cooper, H. (2013). A meta-analysis of the effectiveness of intelligent tutoring systems on college students’ academic learning. Journal of Educational Psychology, 105(4), 970–987. https://doi.org/10.1037/a0032447/ref/VanLehn, K. (2011). The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems. Educational Psychologist, 46(4), 197–221. https://doi.org/10.1080/00461520.2011.611369/ref/Walkington, C., & Hayata, C. A. (2017). Designing learning personalized to students’ interests: balancing rich experiences with mathematical goals. ZDM, 49(4), 519–530. https://doi.org/10.1007/s11858-017-0842-z/ref/Wentzel, K. R., & Brophy, J. E. (2014). Motivating Students to Learn. Taylor and Francis.https://revistas.unab.edu.co/index.php/rcc/article/view/3441Derechos de autor 2018 Revista Colombiana de Computaciónhttp://creativecommons.org/licenses/by-nc-sa/4.0/http://creativecommons.org/licenses/by-nc-nd/2.5/co/Atribución-NoComercial-SinDerivadas 2.5 Colombiahttp://purl.org/coar/access_right/c_abf2Revista Colombiana de Computación; Vol. 19 Núm. 2 (2018): Revista Colombiana de Computación; 37-45Marco inteligente para el aprendizaje combinadoAn Intelligent framework for Blended Learninginfo:eu-repo/semantics/articleArtículohttp://purl.org/coar/resource_type/c_7a1fhttp://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/redcol/resource_type/CJournalArticlehttp://purl.org/coar/version/c_970fb48d4fbd8a85IntelligentTutoringFrameworkBlended LearningIntelligentTutoringSistemasDesarrollo de tecnologíaInnovaciones tecnológicasTutores inteligentesFrameworkBlended learningORIGINAL2018_Marco_inteligente_para_el_aprendizaje.pdf2018_Marco_inteligente_para_el_aprendizaje.pdfArtículoapplication/pdf828718https://repository.unab.edu.co/bitstream/20.500.12749/8838/1/2018_Marco_inteligente_para_el_aprendizaje.pdfe9adc78687eabf48e7de7a6c11defe04MD51open accessTHUMBNAIL2018_Marco_inteligente_para_el_aprendizaje.pdf.jpg2018_Marco_inteligente_para_el_aprendizaje.pdf.jpgIM Thumbnailimage/jpeg13138https://repository.unab.edu.co/bitstream/20.500.12749/8838/2/2018_Marco_inteligente_para_el_aprendizaje.pdf.jpg7533d05f3f9ce73881bd0773b4cc24dbMD52open access20.500.12749/8838oai:repository.unab.edu.co:20.500.12749/88382022-11-30 22:00:18.616open accessRepositorio Institucional \| Universidad Autónoma de Bucaramanga - UNABrepositorio@unab.edu.co

Marco inteligente para el aprendizaje combinado

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