Uso de las técnicas de aprendizaje profundo y árbol de decisión para analizar la incorporación de tecnología en el ámbito educativo.

Autores/as

DOI:

https://doi.org/10.1344/der.2025.46.26-39

Palabras clave:

Tecnología, ICT, Zoom, LMS, COVID-19, Ciencia de datos

Resumen

El objetivo de esta investigación mixta es analizar la percepción de los estudiantes sobre el uso de Zoom y los Sistemas de Gestión de Aprendizaje como Moodle y Google Classroom en el ámbito educativo durante la pandemia de COVID-19 considerado ciencia de datos. En particular, Zoom facilita la comunicación, presentación de contenidos y resolución de dudas. Por otro lado, Moodle y Google Classroom permiten la entrega de tareas, consulta de información y realización de foros de discusión desde cualquier lugar. Los participantes son 128 estudiantes de Psicología (n = 70, 54,69%), Trabajo Social (n = 33, 25,78%) y Geofísica (n = 25, 19,53%) que cursaron las carreras de Método Clínico, Problemas Urbanos y Prospección Electromagnética de la Universidad. Universidad Nacional Autónoma de México durante el ciclo escolar 2020. Los resultados de la técnica de aprendizaje profundo indican que el uso de Zoom y Sistemas de Gestión de Aprendizaje (Moodle y Google Classroom) durante la pandemia de COVID-19 influye positivamente en la asimilación de conocimientos y participación de los estudiantes. La técnica del árbol de decisión identifica 4 modelos predictivos sobre el uso de estas herramientas tecnológicas. Finalmente, Zoom, Moodle y Google Classroom permiten transformar el proceso de enseñanza-aprendizaje y actualizar las actividades escolares durante la pandemia de COVID-19.

Biografía del autor/a

Ricardo-Adán Salas-Rueda, Instituto de Ciencias Aplicadas y Tecnología, Universidad Nacional Autónoma de México

Doctor en Diseño de Nuevas Tecnologías. Investigador de tiempo completo en el Instituto de Ciencias Aplicadas y Tecnología, Universidad Nacional Autónoma de México.

Maestro en Administración e Ingeniero en Sistemas Electrónicos. Investigador nacional SNI nivel 1 (Conacyt) durante el periodo 2019-2021 y Candidato SNI durante el periodo 2016-2018.

Orcid: http://orcid.org/0000-0002-4188-4610

Citas

Adouani, Y., & Khenissi, M. A. (2024). Investigating computer science students' intentions towards the use of an online educational platform using an extended technology acceptance model (e-TAM): An empirical study at a public university in Tunisia. Education and Information Technologies, 29, 14621-14645. https://doi.org/10.1007/s10639-023-12437-6

Altakhayneh, B. H. (2022). Impact of Using Flipped Classroom Strategy in Developing the Mathematical Thinking of Pre-Service Teachers in Open Education Systems in Jordan. International Journal of Emerging Technologies in Learning, 17(3), 228-244. https://doi.org/10.3991/ijet.v17i03.24973

Amjadi, M. F., Kociubuk, J., & Hollnagel, F. (2024). Zoom Improv is accessible and enhances medical student empathy. BMC Medical Education, 24, 1049. https://doi.org/10.1186/s12909-024-06017-6

Aunimo, L., Kauttonen, J., Vahtola, M. (2024). Combining data from a LMS and a student register for exploring factors affecting study duration. Journal of Computing in Higher Education. https://doi.org/10.1007/s12528-024-09414-4

Ayanwale, M. A., Molefi, R. R. & Oyeniran, S. (2024). Analyzing the evolution of machine learning integration in educational research: a bibliometric perspective. Discover Education, 3, 47. https://doi.org/10.1007/s44217-024-00119-5

Badia, A., Martín, D. & Gómez, M. (2019). Teachers’ Perceptions of the Use of Moodle Activities and Their Learning Impact in Secondary Education. Technology, Knowledge and Learning, 24, 483-499. https://doi.org/10.1007/s10758-018-9354-3

Ballejos, M. P., Oglesbee, S., Hettema, J. & Sapien, R. (2018). An equivalence study of interview platform: Does videoconference technology impact medical school acceptance rates of different groups? Advances in Health Sciences Education, 23, 601-610. https://doi.org/10.1007/s10459-018-9817-2

Barelli, E., Lodi, M., Branchetti, L., & Levrini, O. (2024). Epistemic Insights as Design Principles for a Teaching-Learning Module on Artificial Intelligence. Science & Education. https://doi.org/10.1007/s11191-024-00504-4

Castillo-Cuesta, L., Ochoa-Cueva, C., & Cabrera-Solano, P. (2022). Virtual Workspaces for Enhancing Collaborative Work in EFL Learning: A Case Study in Higher Education. International Journal of Emerging Technologies in Learning, 17(2), 4-18. https://doi.org/10.3991/ijet.v17i02.25937

Chang, J. H., Wang, C. J., Zhong, & H. X. (2024). Artificial intelligence learning platform in a visual programming environment: exploring an artificial intelligence learning model. Educational technology research and development, 72, 997-1024. https://doi.org/10.1007/s11423-023-10323-z

Cirigliano, M. M., Guthrie, C. D., & Pusic, M. V. (2020). Click-level Learning Analytics in an Online Medical Education Learning Platform. Teaching and Learning in Medicine, 32(4), 410-421. https://doi.org/10.1080/10401334.2020.1754216

Eiland, L. S. (2018). Student Perceptions of Active-Learning Strategies Utilized in a Drugs in Pregnancy Elective Delivered Synchronously Across Multiple Campuses. TechTrends, 62, 259-265. https://doi.org/10.1007/s11528-018-0260-2

Gamage, S. H., Ayres, J. R., Behrend, M.B., & Smith, E. J. (2019). Optimising Moodle quizzes for online assessments. International Journal of STEM Education, 6, 1-8. https://doi.org/10.1186/s40594-019-0181-4

Gende, D. (2020). Redesigning assessments for remote learning. The Physics Teacher, 58(6), 440-443. https://doi.org/10.1119/10.0001849

Gillingham, K., Eggleton, K., & Goodyear-Smith, F. (2020). Is Reflective Learning Visible in Online Discussion Forums for Medical Students on General Practice Placements? A Qualitative Study. Teaching and Learning in Medicine, 32(4), 434-441. https://doi.org/10.1080/10401334.2020.1730184

Hetherington, L., Hardman, M., Noakes, J., & Wegerif, R. (2018). Making the case for a material-dialogic approach to science education. Studies in Science Education, 54(2), 141-176. https://doi.org/10.1080/03057267.2019.1598036

Heyde, V. V. & Siebrits, A. (2019). Higher-Order e-Assessment for Physics in the Digital Age Using Saka. The Physics Teacher, 57(1), 32-35. https://doi.org/10.1119/1.5084925

Howard, C. D. & Benedicks, R. (2020). An Industry Liaison for Graduate Learning in Instructional Design. TechTrends, 64, 451-459. https://doi.org/10.1007/s11528-019-00465-4

Ibañez, P., Villalonga, C. & Nuere, L. (2020). Exploring Student Activity with Learning Analytics in the Digital Environments of the Nebrija University. Technology, Knowledge and Learning, 25, 769-787. https://doi.org/10.1007/s10758-019-09419-4

Iyamuremye, A., Niyonzima, F. N., & Mukiza, J. (2024). Utilization of artificial intelligence and machine learning in chemistry education: a critical review. Discover Education, 3, 95. https://doi.org/10.1007/s44217-024-00197-5

Jandric, P., Hayes, D., Truelove, I., & Hayes, S. (2020). Teaching in the Age of Covid-19. Postdigital Science and Education, 2, 1069-1230. https://doi.org/10.1007/s42438-020-00169-6

Knapp, N. F. (2018). Increasing Interaction in a Flipped Online Classroom through Video Conferencing. TechTrends, 62, 618-624. https://doi.org/10.1007/s11528-018-0336-z

Li, S., Huang, X., Wang, & T. Zhen, J. (2024). Using text mining and machine learning to predict reasoning activities from think-aloud transcripts in computer assisted learning. Journal of Computing in Higher Education. https://doi.org/10.1007/s12528-024-09404-6

Liu, K., Miller, R., Dickmann, E., & Monday, K. (2018). Virtual Supervision of Student Teachers as a Catalyst of Change for Educational Equity in Rural Areas. Journal of Formative Design in Learning, 2, 8-19. https://doi.org/10.1007/s41686-018-0016-6

Maggio, M. (2020). University teaching practices in the pandemic: from shock to mutation. Campus Virtuales, 9(2), 113-122.

Qin, S., Orchakova, L., Liu, Z. Y., Smirnova, Y., & Tokareva, E. (2022). Using the Learning Management System Modular Object-Oriented Dynamic Learning Environment in Multilingual Education. International Journal of Emerging Technologies in Learning, 17(3), 173-191. https://doi.org/10.3991/ijet.v17i03.25851

Rapanta, C., Botturi, L., Goodyear, P., Guardia, L., & Koole, M. (2020). Online University Teaching During and After the Covid-19 Crisis: Refocusing Teacher Presence and Learning Activity. Postdigital Science and Education, 2, 923-945. https://doi.org/10.1007/s42438-020-00155-y

Ramírez-Montoya, M. S. (2020). Transformación digital e innovación educativa en Latinoamérica en el marco del COVID-19. Campus Virtuales, 9(2), 123-139.

Riopel, M., Nenciovici, L., Potvin, P., Chastenay, P., Charland, P., Sarrasin, J. B., & Masson, S. (2019). Impact of serious games on science learning achievement compared with more conventional instruction: an overview and a meta-analysis. Studies in Science Education, 55(2), 169-214. https://doi.org/10.1080/03057267.2019.1722420

Ruschenpohler, L. & Markic, S. (2019). Self-concept research in science and technology education – theoretical foundation, measurement instruments, and main findings. Studies in Science Education, 55(1), 37-68. https://doi.org/10.1080/03057267.2019.1645533

Salas-Rueda, R. A., Cabrera-Rodríguez, A. E., & Domínguez-Herrera, E. (2024). Use of the flipped classroom and technology in the teaching-learning process about the landscape concept in the High School College. Atelie Geográfico, 18(1), 429-449. https://doi.org/10.5216/ag.v18i1.79052

Shiao, Y. T., Chen, C. H., & Wu, K. F. (2023). Reducing dropout rate through a deep learning model for sustainable education: long-term tracking of learning outcomes of an undergraduate cohort from 2018 to 2021. Smart Learning Environments, 10, 55. https://doi.org/10.1186/s40561-023-00274-6

Westervelt, K. C., Hing, W., McGovern, M. C., Banks, L., Carney, C., Kunker, K., Magoon, A., Sibold, J. & Crane, L. (2018). An online model of international clinical mentoring for novice physical therapists. Journal of Manual & Manipulative Therapy, 26(3), 170-180. https://doi.org/10.1080/10669817.2018.1447789

Wu, D., Guo, Z., & Wang, Y. (2024). Auxiliary analysis of digital platform using internet of things technology in physical education teaching. Education and Information Technologies, 29, 15855-15874. https://doi.org/10.1007/s10639-024-12469-6

Wut, Tm., Shun-mun Wong, H., & Ka-man Sum, C. (2024). Does institution support matter? Blended learning approach in the higher education sector. Education and Information Technologies, 29, 15133–15145. https://doi.org/10.1007/s10639-024-12478-5

Zhai, X., Haudek, K. C., & Ma, W. (2023). Assessing Argumentation Using Machine Learning and Cognitive Diagnostic Modeling. Research in Science Education, 53, 405-424. https://doi.org/10.1007/s11165-022-10062-w

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Publicado

2025-02-03

Número

Núm. 46 (2025): Number 46, January 2025

Sección

Artículos revisados por pares

Licencia

Derechos de autor 2025 Ricardo-Adán Salas-Rueda, Ricardo Castañeda-Martínez, Jesús Ramírez-Ortega, Selene-Marisol Martínez-Ramírez

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