Aprendizaje conceptual en grupos de profesorado en formación mediante una intervención basada en Minería de Textos

Autores/as

DOI:

https://doi.org/10.5944/educxx1.38256

Palabras clave:

análisis de texto, análisis de contenido, formación del concepto, aprendizaje social, aprendizaje visual, tecnología de la educación, enseñanza superior, formación de profesores

Resumen

La adquisición de conceptos es un aspecto fundamental en la formación del profesorado, pero representa un desafío persistente, especialmente en contextos grupales donde las estrategias de enseñanza tradicionales a menudo no logran transmitir las nociones complejas de forma eficaz. Este estudio explora el potencial de la analítica del aprendizaje basada en minería de textos (MT) como herramienta didáctica para mejorar el aprendizaje conceptual del profesorado en formación. El objetivo principal fue analizar el impacto de la analítica del aprendizaje basada con MT en la adquisición de conceptos educativos abstractos y complejos, en comparación con estrategias de enseñanza tradicionales como la elaboración de proyectos individuales o la asistencia a clases magistrales. Para ello, se llevó a cabo un estudio cuasiexperimental pre y postest con 81 estudiantes de máster de un programa de formación a distancia en una universidad española. El análisis se centró en los corpus textuales generados a partir de las definiciones de conceptos educativos intangibles por parte de tres grupos no equivalentes (Grupos A, B y C, respectivamente). Mediante técnicas de MT, se analizaron 1017 tokens pretest y 1133 postest del Grupo A, 1127 tokens pretest y 1111 postest del Grupo B, y 1101 tokens pretest y 1173 postest del Grupo C. Los resultados evidenciaron que la analítica de aprendizaje basada en MT mejoró significativamente la adquisición de conceptos, tanto en la selección de palabras clave (tYuen = –6.37, p < .001, δR AKP = –1.03, IC95% = –2.10, –.74) como en la asociación de términos relevantes (valores de Jaccard postest de .217 a .917) en las definiciones formuladas por los estudiantes, superando otros enfoques de enseñanza. Este estudio proporciona evidencia empírica del valor pedagógico de la analítica del aprendizaje basada en MT, demostrando su eficacia para mejorar el aprendizaje de conceptos abstractos en la formación del profesorado. Los resultados destacan el potencial de la tecnología educativa basada en MT para optimizar el aprendizaje conceptual y la eficiencia de los recursos en contextos grupales de educación superior.

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Aguilar, J., Buendia, O., Pinto, A., & Gutiérrez, J. (2022). Social learning analytics for determining learning styles in a smart classroom. Interactive Learning Environments, 30(2), 245–261. https://doi.org/10.1080/10494820.2019.1651745

Atkinson, M. B., Krishnan, S., McNeil, L. A., Luft, J. A., & Pienta, N. J. (2020). Constructing Explanations in an Active Learning Preparatory Chemistry Course. Journal of Chemical Education, 97(3), 626–634. https://doi.org/10.1021/acs.jchemed.9b00901

Ausubel, D. P., Novak, J. D., & Hanesian, H. (1968). Educational psychology: a cognitive view. Holt, Rinehart and Winston.

Azadi, G., Biria, R., & Nasri, M. (2018). Operationalising the Concept of Mediation in L2 Teacher Education. Journal of Language Teaching and Research, 9(2), 132–140. https://doi.org/10.17507/jltr.0901.17

Babaahmadi, A., Maraghi, E., Moradi, S., & Younespour, S. (2021). Comparison Between Peer Learning and Conventional Methods in Biostatistics Course Among Postgraduate Nursing Students’ Final Score, Statistics and Test Anxiety: A Quasi-experimental Study with a Control Group. Shiraz E-Medical Journal, 22(11), 1–8. https://doi.org/10.5812/semj.111984

Begusic, D., Pintar, D., Skopljanac-Macina, F., & Vranic, M. (2018). Annotating Exam Questions Through Automatic Learning Concept Classification. 2018 26th International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2018, 176–180. https://doi.org/10.23919/SOFTCOM.2018.8555784

Borghi, A. M., Barca, L., Binkofski, F., Castelfranchi, C., Pezzulo, G., & Tummolini, L. (2019). Words as social tools: Language, sociality and inner grounding in abstract concepts. Physics of Life Reviews, 29, 120–153. https://doi.org/10.1016/j.plrev.2018.12.001

Breivik, J. (2020). Argumentative patterns in students’ online discussions in an introductory philosophy course: Micro-and acrostructures of argumentation as analytic tools. Nordic Journal of Digital Literacy, 15(1), 8–23. https://doi.org/10.18261/ISSN.1891-943X-2020-01-02

Bruner, J. S., Goodnow, J. J., & Austin, G. A. (1956). A study of thinking. Wiley.

Casanoves, M., Solé-Llussà, A., Haro, J., Gericke, N., y Valls, C. (2022). Assessment of the ability of game-based science learning to enhance genetic understanding. Research in Science & Technological Education, 1–23. https://doi.org/10.1080/02635143.2022.2044301

Cortes, D. M. G., Rodríguez, C. M. O., & Alejo, V. V. (2019). Learning object for contextualization of matrix operations in digital image processing through programming. Proceedings of the Seventh International Conference on Technological Ecosystems for Enhancing Multiculturality, 92–98. https://doi.org/10.1145/3362789.3362876

Costa, A. P. M., Reategui, E. B., Epstein, D., Meyer, D. D., Lima, E. G., & Silva, K. H. da. (2017). Emprego de um software baseado em mineração de texto e apresentação gráfica multirrepresentacional como apoio à aprendizagem de conceitos científicos a partir de textos no Ensino Fundamental. Ciência & Educação (Bauru), 23(1), 91–109. https://doi.org/10.1590/1516-731320170010006

De Lin, O., Gottipati, S., Ling, L. S., & Shankararaman, V. (2021). Mining Informal & Short Student Self-Reflections for Detecting Challenging Topics – A Learning Outcomes Insight Dashboard. 2021 IEEE Frontiers in Education Conference (FIE), Oct 2021, 1–9. https://doi.org/10.1109/FIE49875.2021.9637181

Erkens, M., Bodemer, D., & Hoppe, H. U. (2016). Improving collaborative learning in the classroom: Text mining based grouping and representing. International Journal of Computer-Supported Collaborative Learning, 11(4), 387–415. https://doi.org/10.1007/s11412-016-9243-5

Finkenstaedt-Quinn, S. A., Polakowski, N., Gunderson, B., Shultz, G. V., & Gere, A. R. (2021). Utilizing Peer Review and Revision in STEM to Support the Development of Conceptual Knowledge Through Writing. Written Communication, 38(3), 351–379. https://doi.org/10.1177/07410883211006038

Freeman, D. (2018). Arguing for a knowledge-base in language teacher education, then (1998) and now (2018). Language Teaching Research, 24(1), 5–16. https://doi.org/10.1177/1362168818777534

Gaglo, K., Degboe, B. M., Kossingou, G. M., & Ouya, S. (2022). Proposal of conversational chatbots for educational remediation in the context of covid-19. 2022 24th International Conference on Advanced Communication Technology (ICACT), Feb 2022, 354–358. https://doi.org/10.23919/ICACT53585.2022.9728860

Gagné, R. M. (1985). The conditions of learning and theory of instruction (4th ed.). Holt, Rinehart and Winston.

Gao, R., & Lloyd, J. (2020). Precision and Accuracy: Knowledge Transformation through Conceptual Learning and Inquiry-Based Practices in Introductory and Advanced Chemistry Laboratories. Journal of Chemical Education, 97(2), 368–373. https://doi.org/10.1021/acs.jchemed.9b00563

Ghanizadeh, A., Tabeie, M., & Pourtousi, Z. (2024). The role of university instructor’s narrative in students’ sustained attention, emotional involvement and cognitive learning. Journal of Applied Research in Higher Education, 16(1), 195–207. https://doi.org/10.1108/JARHE-09-2022-0278

Greco, P., & Piaget, J. (1959). Apprentissage et connaissance. P.U.F.

Guerrettaz, A. M., Zahler, T., Sotirovska, V., & Boyd, A. S. (2020). ‘We acted like ELLs’: A pedagogy of embodiment in preservice teacher education. Language Teaching Research, 1–25. https://doi.org/10.1177/1362168820909980

Hernández-de-Menéndez, M., Vallejo Guevara, A., Tudón Martínez, J. C., Hernández Alcántara, D., & Morales-Menendez, R. (2019). Active learning in engineering education. A review of fundamentals, best practices and experiences. International Journal on Interactive Design and Manufacturing, 13(3), 909–922. https://doi.org/10.1007/S12008-019-00557-8/FIGURES/2

Hernández-Lara, A. B., Perera-Lluna, A., & Serradell-López, E. (2021). Game learning analytics of instant messaging and online discussion forums in higher education. Education and Training, 63(9), 1288–1308. https://doi.org/10.1108/ET-11-2020-0334

Hutmacher, F. (2019). Why Is There So Much More Research on Vision Than on Any Other Sensory Modality? Frontiers in Psychology, 10, 2246. https://doi.org/10.3389/fpsyg.2019.02246

Inada, Y. (2018). Collaborative learning in entrepreneurship education in a Japanese business school. Proceedings of the European Conference on Innovation and Entrepreneurship, ECIE, Sep 2018, 319–327.

Itti, L., & Koch, C. (2001). Computational modelling of visual attention. Nature Reviews Neuroscience, 2(3), 194–203. https://doi.org/10.1038/35058500

Jeong, A., & Chiu, M. M. (2020). Production blocking in brainstorming arguments in online group debates and asynchronous threaded discussions. Educational Technology Research and Development, 68, 3097–3114. https://doi.org/10.1007/s11423-020-09845-7

Kanwisher, N., & Wojciulik, E. (2000). Visual attention: Insights from brain imaging. Nature Reviews Neuroscience, 1(2), 91–100. https://doi.org/10.1038/35039043

Khong, I., Aprila Yusuf, N., Nuriman, A., & Bayu Yadila, A. (2023). Exploring the Impact of Data Quality on Decision-Making Processes in Information Intensive Organizations. APTISI Transactions on Management (ATM), 7(3), 253–260.

https://doi.org/10.33050/atm.v7i3.2138

Kong, S.-C., Kwok, W.-Y., & Poon, C.-W. (2021). Evaluating a learning trail for academic integrity development in higher education using bilingual text mining. Technology, Pedagogy and Education, 30(2), 305–322. https://doi.org/10.1080/1475939X.2021.1899041

Koong, C.-S., Lin, H.-C., Wu, C.-C., Chen, C.-H., Lee, P.-H., & Wang, H.-C. (2021). Design and Implementation of an iOS APP: Multimedia Interactive System and Items for Woodworking Teaching. En M. M. T. Rodrigo, S. Iyer, A. Mitrovic, H. N. H. Cheng, D. Kohen-Vacs, C. Matuk, A. Palalas, R. Rajenran, K. Seta, y J. Wang (Eds.), 29th International Conference on Computers in Education Conference, ICCE 2021 - Proceedings (Vol. 2, pp. 310–316). Asia-Pacific Society for Computers in Education.

Kortemeyer, G., Anderson, D., Desrochers, A. M., Hackbardt, A., Hoekstra, K., Holt, A., Iftekhar, A., Kabaker, T., Keller, N., Korzecke, Z., Gogonis, A., Manson, Q., McNeill, G., Mookerjee, D., Nguyen, S., Person, B., Stafford, M., Takamoribraganca, L., Yu, Z., … Ratan, R. (2019). Using a computer game to teach circuit concepts. European Journal of Physics, 40(5), 1–16. https://doi.org/10.1088/1361-6404/ab2a1d

Liao, A. Y. H. (2022). An APP-Based E-Learning Platform for Artificial Intelligence Cross-Domain Application Practices. En L. Barolli, K. Yim, y H. C. Chen (Eds.), Innovative Mobile and Internet Services in Ubiquitous Computing. IMIS 2021. Lecture Notes in Networks and Systems (Vol. 279, pp. 341–351). Springer. https://doi.org/10.1007/978-3-030-79728-7_34

Magana, A. J., Serrano, M. I., & Rebello, N. S. (2019). A sequenced multimodal learning approach to support students’ development of conceptual learning. Journal of Computer Assisted Learning, 35(4), 516–528. https://doi.org/10.1111/jcal.12356

Nguyen, K. A., Borrego, M., Finelli, C. J., DeMonbrun, M., Crockett, C., Tharayil, S., Shekhar, P., Waters, C., & Rosenberg, R. (2021). Instructor strategies to aid implementation of active learning: a systematic literature review. International Journal of STEM Education, 8(1), 1–18. https://doi.org/10.1186/S40594-021-00270-7/TABLES/2

Nobre, A. C. (Kia), & Kastner, S. (Eds.). (2014). The Oxford Handbook of Attention (Vol. 1). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199675111.001.0001

Pardo, A., & San Martín, R. (2010). Metodología de las Ciencias del Comportamiento y de la Salud II. Síntesis.

Pillutla, V. S., Tawfik, A. A., & Giabbanelli, P. J. (2020). Detecting the Depth and Progression of Learning in Massive Open Online Courses by Mining Discussion Data. Technology, Knowledge and Learning, 25(4), 881–898. https://doi.org/10.1007/s10758-020-09434-w

Pintar, D., Begušić, D., Škopljanac-Mačina, F., & Vranić, M. (2018). Automatic extraction of learning concepts from exam query repositories. Journal of Communications Software and Systems, 14(4), 312–319. https://doi.org/10.24138/jcomss.v14i4.605

Reategui, E., Costa, A. P. M., Epstein, D., & Carniato, M. (2019). Learning Scientific Concepts with Text Mining Support (pp. 97–105). https://doi.org/10.1007/978-3-319-98872-6_12

Redondo López, J. M. (2021). Improving Concept Learning Through Specialized Digital Fanzines. 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET), 134–143. https://doi.org/10.1109/ICSE-SEET52601.2021.00023

Reyes-Santías, F., Rivo-López, E., Villanueva-Villar, M., & Míguez-Álvarez, C. (2021). Movie clips for teaching business management: Step by step. Journal of Education for Business, 1–12. https://doi.org/10.1080/08832323.2021.1991258

Reynolds, J. A., Cai, V., Choi, J., Faller, S., Hu, M., Kozhumam, A., Schwartzman, J., & Vohra, A. (2020). Teaching during a pandemic: Using high‐impact writing assignments to balance rigor, engagement, flexibility, and workload. Ecology and Evolution, 10(22), 12573–12580. https://doi.org/10.1002/ece3.6776

Rodriguez, M., & Potvin, G. (2021). Frequent small group interactions improve student learning gains in physics: Results from a nationally representative prepost study of four-year colleges. Physical Review Physics Education Research, 17(2), 1–11. https://doi.org/10.1103/PhysRevPhysEducRes.17.020131

Shwartz, V. (2021). Dissertation Abstract: Learning High Precision Lexical Inferences. KI - Künstliche Intelligenz, 35(3–4), 377–383. https://doi.org/10.1007/s13218-021-00709-7

Taga, M., Onishi, T., & Hirokawa, S. (2018). Automated Evaluation of Students Comments Regarding Correct Concepts and Misconceptions of Convex Lenses. Proceedings - 2018 7th International Congress on Advanced Applied Informatics, IIAI-AAI 2018, 273–277. https://doi.org/10.1109/IIAI-AAI.2018.00059

Tsai, M.-J., Wu, A.-H., & Wang, C.-Y. (2022). Pre-training and cueing effects on students’ visual behavior and task outcomes in game-based learning. Computers in Human Behavior Reports, 6, 1–9. https://doi.org/10.1016/j.chbr.2022.100188

Turner, R. L. (1975). An Overview of Research in Teacher Education. Teachers College Record: The Voice of Scholarship in Education, 76(6), 87–110. https://doi.org/10.1177/016146817507600605

Turner, S. A., Pérez-Quiñones, M. A., & Edwards, S. H. (2018). Peer Review in CS2: Conceptual Learning and High-Level Thinking. ACM Transactions on Computing Education, 18(3), 1–37. https://doi.org/10.1145/3152715

Volkwyn, T. S., Gregorcic, B., Airey, J., & Linder, C. (2020). Learning to use Cartesian coordinate systems to solve physics problems: the case of ‘movability.’ European Journal of Physics, 41(4), 1–15. https://doi.org/10.1088/1361-6404/ab8b54

Wittek, A. L. (2018). Processes of Writing as Mediational Tool in Higher Education. Scandinavian Journal of Educational Research, 62(3), 444–460. https://doi.org/10.1080/00313831.2016.1258664

Ye, L., Eichler, J. F., Gilewski, A., Talbert, L. E., Mallory, E., Litvak, M., M. Rigsby, E., Henbest, G., Mortezaei, K., & Guregyan, C. (2020). The impact of coupling assessments on conceptual understanding and connection-making in chemical equilibrium and acid-base chemistry. Chemistry Education Research and Practice, 21(3), 1000–1012. https://doi.org/10.1039/d0rp00038h

Publicado

2025-06-20 — Actualizado el 2025-06-30

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García-García, F. J., Mollà-Esparza, C., & López-Francés, I. (2025). Aprendizaje conceptual en grupos de profesorado en formación mediante una intervención basada en Minería de Textos. Educación XX1, 28(2), 17–43. https://doi.org/10.5944/educxx1.38256 (Original work published 20 de junio de 2025)

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