Evidencias sobre los beneficios y dificultades del uso e implementación del aprendizaje profundo en la universidad
| dc.book.title | Innovación docente e investigación en educación: nuevas tendencias para el cambio en la enseñanza superior | |
| dc.contributor.author | Fontana Abad, Mónica | |
| dc.contributor.author | Camilli Trujillo, Celia Rosa | |
| dc.contributor.author | Martín Martín, Margarita Carmen | |
| dc.contributor.author | Bueno Álvarez, José Antonio | |
| dc.contributor.editor | Martos Martínez, África | |
| dc.contributor.editor | Simón Márquez, María del Mar | |
| dc.contributor.editor | Gázquez Linares, José Jesús | |
| dc.contributor.editor | Molina Moreno, Pablo | |
| dc.contributor.editor | Fernández Gea, Silvia | |
| dc.date.accessioned | 2024-11-08T08:25:49Z | |
| dc.date.available | 2024-11-08T08:25:49Z | |
| dc.date.issued | 2023 | |
| dc.description | Referecnias bibliográficas: • Aguiar-Castillo, L., Clavijo-Rodriguez, A., Hernández-López, L., De Saa-Pérez, P. y PérezJiménez, R. (2021). Gamification and deep learning approaches in higher education. Journal of Hospitality, Leisure, Sport and Tourism Education, 29, 1-14. doi: 10.1016/j.jhlste.2020.100290 • Akgül, Y. y Osman, A. (2022). Facebook/Meta usage in higher education: A deep learningbased dual-stage SEM-ANN analysis. Education and Information Technologies, 27, 9821-9855. doi: 10.1007/s10639-022-11012-9 • Bhardwaj, P., Gupta, P. K., Panwar, H., Khubeb, M., Morales-Menendez, R. y Bhaik, A. (2021). Application of Higher Education Management in Colleges and Universities by Deep Learning. Computers and Electrical Engineering, 93, 1-11. doi: 10.1016/j.compeleceng.2021.107277 • Biggs, J. B. (1978). Individual and group differences in study processes. British Journal of Educational Psychology, 48(3), 266–279. doi: 10.1111/j.2044-8279.1978.tb03013.x • Bruning, R. H., Schraw, G. J., y Norby, M. M. (2012). Psicología cognitiva y de la instrucción (5ª ed.). Pearson. • Cirkony, C., Rickinson, M., Walsh, L., Gleeson, J., Salisbury, M. y Cutler, B. (2022). Reflections on conducting rapid reviews of educational research. Educational Research, 64(4), 371–390. doi: 10.1080/00131881.2022.2120514 • Doleck, T.; Lemay, D. J.; Basnet, R. B., y Bazelais, P. (2020). Predictive analytics in education: A comparison of deep learning frameworks. Education and Information Technologies., 25, 1951–1963. doi: s10639-019-10068-4 • Dolmans, D. H., Loyens, S. M., Marcq, H., y Gijbels, D. (2016). Deep and surface learning in problem-based learning: A review of the literature. Advances in Health Sciences Education, 21, 1087–1112. doi: 10.1007/s10459-015-9645-6 • Fernández, M. (2016). La escuela en la encrucijada. Fundación Santillana. King, V. J., Stevens, A., Nussbaumer-Streit, B., Kamel, C. y Garritty, C. (2022). Paper 2: Performing rapid reviews. Systematic Reviews, 11, 151. doi: 10.1186/s13643-022-02011-5 • Leilei, W., Rajendiran, S. y Gayathri, K. (2021). An emergency response system created to combat injuries during physical education training in a university using deep learning. The Electronic Library, 39(4), 505-525. doi: 10.1108/EL-07-2020-0175 • Li, S. y Liu, T. (2021). Performance Prediction for Higher Education Students Using Deep Learning. Complexity. doi: 10.1155/2021/9958203 • Li, Y., Zhang, L., Tian, Y. y Qi, W. (2022). Research on Teaching Practice of Blended Higher Education Based on Deep Learning Route. Computational Intelligence and Neuroscience, 3, 1- 8. doi: 10.1155/2022/5906335 • Meng, H. (2022). Analysis of the Relationship between Transformational Leadership and Educational Management in Higher Education Based on Deep Learning. Computational Intelligence and Neuroscience. doi: 10.1155/2022/5287922 • Ngwira, B., Gobin-Rahimbux, B. y Gooda, N. (2023). A Deep-Learning Framework for Analysing Students' Review in Higher Education. Computational Intelligence and Neuroscience. doi: 10.1155/2023/8462575 • Pnevmatikos, D., Christodoulou, P., Georgiadou, T., Lithoxoidou, A., Dimitriadou, A., Payan Carreira, R., Simões, M., Ferreira, D., Rebelo, H., Sebastião, L., et al. (2021). Think4jobs Training: Critical Thinking Training Packages for Higher Education Instructors and Labour Market Tutors. University of Western Macedonia. Recuperado de: https://shorturl.at/cipsD • Segú, M. I. (2023). Autoethnography as a Tool for the Achievement of Deep Learning of University Students in Service-Learning Experiences. Social Sciences, 12(395), 1-12. doi: 10.3390/socsci12070395 • Simón, N., Del Valle, S., Rioja, N. y Cuadrado, J. (2023). Metacognitive and self-determined deep learning assessment in university students. Retos, 48, 861-872. doi: 10.47197/RETOS.V48.93421 • Tang, Y. y Liu, L. (2022). A Novel Deep Learning Technique for Higher Education System. Mathematical Problems in Engineering. doi: /10.1155/2022/4588263 • Thien, L. M., Leong, M.C., y Por, F. P. (2022). Factors contributing to Gen Z's deep learning: investigating undergraduates' course experience in Malaysian private higher education institutions. Journal of Applied Research in Higher Education, 14(4), 1637-1655. doi: 10.1108/JARHE-01-2021-0005 • Tian, Y., Sun, Y., Zhang, L. y Qi, W. (2022). Research on MOOC Teaching Mode in Higher Education Based on Deep Learning. Computational Intelligence and Neuroscience. ID 8031602. doi:10.1155/2022/8031602 • Tricco, A. C., Antony, J., Zarin, W., Strifler, L.; Ghassemi, M., Ivory, J., Perrier, L., Hutton, B., Moher, D., y Straus, S. E. (2015). A scoping- review of rapid review methods. BMC Med, 13, 224. doi: 10.1186/s12916-015-0465-6 • UCM. (2022). Manual de apoyo a la incorporación de la agenda 2030 a los contenidos docentes. El autor. • Wu, H. (2022). Higher Education Environment Monitoring and Quality Assessment Model Using Big Data Analysis and Deep Learning. Journal of Environmental and Public Health, doi: 10.1155/2022/7281278 • Zhang, X. y Cao, Z. (2021). A Framework of an Intelligent Education System for Higher Education Based on Deep Learning. International Journal of Emerging Technologies in Learning, 16(7), 233-248. doi: 10.3991/ijet.v16i07.22123 • Zhao, A. y Ma, Y. (2022). Research on Recommendation of Big Data for Higher Education Based on Deep Learning. Scientific Programming, 1-8. doi: 10.1155/2022/5448442 • Zhong, L., Qi, C., y Gao, Y. (2022). Deep Learning-Assisted Performance Evaluation System for Teaching SCM in the Higher Education System: Performance Evaluation of Teaching Management. Information Resources Management Journal, 35(3), 1-22. doi: 10.4018/IRMJ.30445 • Zuo, M. y Wang, J. (2021). Higher Education Curriculum Evaluation Method Based on Deep Learning Model. Computational Intelligence and Neuroscience, 1-15. doi: 10.1155/2021/9036550 | |
| dc.description.abstract | Aunque se ha avanzado mucho en el aprendizaje profundo, falta una investigación organizada y objetiva sobre su empleo en el contexto educativo, y muy especialmente en la universidad, donde estas destrezas se tornan especialmente necesarias y relevantes para alcanzar los logros académicos requeridos por las diferentes titulaciones. De hecho, no existen revisiones sistemáticas en relación a esta materia en el contexto universitario, lo que hace necesario llevar a cabo un análisis en profundidad. Por ello, el objetivo de esta investigación es la exploración de los beneficios y dificultades de la implementación/uso del pensamiento profundo en la universidad a través de una revisión rápida de la literatura. | |
| dc.description.department | Depto. de Investigación y Psicología en Educación | |
| dc.description.faculty | Fac. de Educación | |
| dc.description.refereed | TRUE | |
| dc.description.status | pub | |
| dc.identifier.citation | Fontana Abad, M., Camilli Trujillo, C. R., Martín Martín, M., & Bueno Álvarez, J. A. (2023). Evidencias sobre los beneficios y dificultades del uso e implementación del aprendizaje profundo en la universidad. En Innovación docente e investigación en educación: nuevas tendencias para el cambio en la enseñanza superior (pp. 689-700). Dykinson. | |
| dc.identifier.isbn | 978-84-1170-864-7 | |
| dc.identifier.relatedurl | https://produccioncientifica.ucm.es/documentos/660d9e371f324b0dfb9f2ee9 | |
| dc.identifier.relatedurl | https://dialnet.unirioja.es/servlet/articulo?codigo=9402108 | |
| dc.identifier.relatedurl | https://dialnet.unirioja.es/servlet/libro?codigo=954312 | |
| dc.identifier.relatedurl | https://www.dykinson.com/libros/innovacion-docente-e-investigacion-en-educacion-nuevas-tendencias-para-el-cambio-en-la-ensenanza-superior/9788411708647/ | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14352/110273 | |
| dc.language.iso | spa | |
| dc.page.final | 700 | |
| dc.page.initial | 689 | |
| dc.publication.place | Madrid | |
| dc.publisher | Dykinson | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | en |
| dc.rights.accessRights | restricted access | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject.cdu | 159.953.5 | |
| dc.subject.cdu | 378 | |
| dc.subject.cdu | 37.015.4 | |
| dc.subject.cdu | 371.3 | |
| dc.subject.cdu | 37.012 | |
| dc.subject.ucm | Enseñanza universitaria | |
| dc.subject.ucm | Aprendizaje | |
| dc.subject.ucm | Métodos de investigación en educación | |
| dc.subject.ucm | Métodos de enseñanza | |
| dc.subject.ucm | Psicología de la educación (Educación) | |
| dc.subject.unesco | 5801.05 Pedagogía Experimental | |
| dc.subject.unesco | 5801.07 Métodos Pedagógicos | |
| dc.title | Evidencias sobre los beneficios y dificultades del uso e implementación del aprendizaje profundo en la universidad | |
| dc.type | book part | |
| dc.type.hasVersion | VoR | |
| dspace.entity.type | Publication | |
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| relation.isAuthorOfPublication.latestForDiscovery | 0d09d86f-581c-4f70-929b-b0044c9a2817 |
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