Modelización e Innovación Situada en Ciencias: Una Ruta Pedagógica para Aulas Diversas
Palabras clave:
Enseñanza de las ciencias, Innovación pedagógica, Tecnología educativa, Educación inclusiva, Formación de docentesResumen
Este artículo propone una ruta pedagógica para fortalecer la enseñanza de las ciencias en aulas con alta diversidad y condiciones tecnológicas desiguales. A partir de una revisión teórica integradora, se analizaron aportes recientes sobre modelización, TPACK, aprendizaje móvil, Diseño Universal para el Aprendizaje, evaluación formativa e innovación responsable. La síntesis muestra que la mejora de la práctica no depende de añadir recursos digitales, sino de organizar experiencias en las que el estudiantado construya, use, contraste y revise modelos con evidencias. Como aporte se plantea la ruta de Práctica Pedagógica Innovadora, PPI, que articula fenómeno cercano, mediación tecnológica situada, accesibilidad epistémica y evaluación con trazas verificables. El texto ofrece matrices, criterios y una rúbrica breve para orientar diseños transferibles a contextos latinoamericanos. Se concluye que innovar en ciencias exige menos improvisación y más documentación pedagógica, sin perder cercanía con el aula real.
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Acher, A., Arcà, M., & Sanmartí, N. (2007). Modeling as a teaching learning process for understanding materials: A case study in primary education. Science Education, 91(3), 398-418. https://doi.org/10.1002/sce.20196
Bang, M., Brown, B., Calabrese Barton, A., Rosebery, A., & Warren, B. (2017). Toward more equitable learning in science. Science Education, 101(4), 597-607. https://doi.org/10.1002/sce.21286
Berland, L. K., & Reiser, B. J. (2009). Making sense of argumentation and explanation. Science Education, 93(1), 26-55. https://doi.org/10.1002/sce.20286
Boude, O. R., & Jiménez, J. A. (2013). El aprendizaje móvil como estrategia didáctica en la educación superior. Revista de Universidad y Sociedad del Conocimiento, 10(1), 152-166. https://doi.org/10.7238/rusc.v10i1.1579
Carroll, G., & Park, S. (2024). Towards expansive model-based teaching: A systematic synthesis of modelling pedagogies in science education literature. Studies in Science Education. https://doi.org/10.1080/03057267.2024.2417157
CAST. (2024). Universal Design for Learning Guidelines version 3.0. CAST. https://udlguidelines.cast.org/
Crompton, H., & Burke, D. (2018). The use of mobile learning in higher education: A systematic review. Computers & Education, 123, 53-64. https://doi.org/10.1016/j.compedu.2018.04.007
De Jong, T., Linn, M. C., & Zacharia, Z. C. (2013). Physical and virtual laboratories in science and engineering education. Science, 340(6130), 305-308. https://doi.org/10.1126/science.1230579
Furtak, E. M., Seidel, T., Iverson, H., & Briggs, D. C. (2012). Experimental and quasi-experimental studies of inquiry-based science teaching: A meta-analysis. Review of Educational Research, 82(3), 300-329. https://doi.org/10.3102/0034654312457206
Gilbert, J. K., & Justi, R. (2016). Modelling-based teaching in science education. Springer. https://doi.org/10.1007/978-3-319-29039-3
Hodson, D. (2014). Learning science, learning about science, doing science: Different goals demand different learning methods. International Journal of Science Education, 36(15), 2534-2553. https://doi.org/10.1080/09500693.2014.899722
International Federation of Library Associations and Institutions. (2012). Moscow declaration on media and information literacy. IFLA. https://www.ifla.org/publications/moscow-declaration-on-media-and-information-literacy/
López, J. P., Vera, F., & Parodi, T. A. (2026). Ethical opportunities and challenges of AI in mental health in Latin America. Transformar, 7(1), 21-33. https://revistatransformar.cl/index.php/transformar/article/view/212
Louca, L. T., & Zacharia, Z. C. (2012). Modeling-based learning in science education: Cognitive, metacognitive, social, material and epistemological contributions. Educational Review, 64(4), 471-492. https://doi.org/10.1080/00131911.2011.628748
Marino, M. T. (2024). Innovation configuration: Universal Design for Learning. CEEDAR Center. https://ceedar.education.ufl.edu/
Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
Nasri, N. M., Roslan, S., Sekuan, M. I., & Bakar, K. A. (2021). Inclusive science education through Universal Design for Learning. Journal of Research in Science Teaching, 58(6), 805-829.
National Academies of Sciences, Engineering, and Medicine. (2018). How people learn II: Learners, contexts, and cultures. The National Academies Press. https://doi.org/10.17226/24783
NGSS Lead States. (2013). Next generation science standards: For states, by states. The National Academies Press. https://www.nextgenscience.org/
OECD. (2023). PISA 2022 results, volume I: The state of learning and equity in education. OECD Publishing. https://doi.org/10.1787/53f23881-en
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., ... Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, Article n71. https://doi.org/10.1136/bmj.n71
Parodi Camaño, T. A., Hernández Euge, P. A., Martinez Vargas, J. L., Ayala-Ruiz, O., & Chalapud Narváez, E. D. (2025). La Inteligencia Artificial en salud como escenario de aprendizaje: Retos, avances y perspectivas. Transformar, 6(2), 5-12. https://revistatransformar.cl/index.php/transformar/article/view/170
Parodi Camaño, T. A., Vidal Durango, J. V., & Portnoy, I. (2026). CEO narcissism and its influence on innovation capabilities of micro, small, and medium-sized enterprises: An empirical study in the Colombian context. PLOS ONE. https://doi.org/10.1371/journal.pone.0341491
Quellmalz, E. S., Timms, M. J., Silberglitt, M. D., & Buckley, B. C. (2012). Science assessments for all: Integrating science simulations into balanced state science assessment systems. Journal of Research in Science Teaching, 49(3), 363-393. https://doi.org/10.1002/tea.21005
Reiser, B. J., Berland, L. K., & Kenyon, L. (2012). Engaging estudiantes in the scientific practices of explanation and argumentation. Science Scope, 35(8), 6-11.
Schmid, M., Brianza, E., Mok, S. Y., & Petko, D. (2024). Running in circles: A systematic review of reviews on technological pedagogical content knowledge (TPACK). Computers & Education, 214, Article 105024. https://doi.org/10.1016/j.compedu.2024.105024
Schwarz, C. V., Reiser, B. J., Davis, E. A., Kenyon, L., Achér, A., Fortus, D., Shwartz, Y., Hug, B., & Krajcik, J. (2009). Developing a learning progression for scientific modeling: Making scientific modeling accessible and meaningful for learners. Journal of Research in Science Teaching, 46(6), 632-654. https://doi.org/10.1002/tea.20311
Shuler, C., Winters, N., & West, M. (2013). The future of mobile learning: Implications for policy makers and planners. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000219637
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333-339. https://doi.org/10.1016/j.jbusres.2019.07.039
Torraco, R. J. (2016). Writing integrative literature reviews: Using the past and present to explore the future. Human Resource Development Review, 15(4), 404-428. https://doi.org/10.1177/1534484316671606
UNESCO. (2019). International technical guidance on sexuality education: An evidence-informed approach. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000260770
UNESCO. (2023a). Global education monitoring report 2023: Technology in education: A tool on whose terms? UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000385723
UNESCO. (2023b). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693
Uparela-Barragán, H., Gaspar-López, J., Salas Álvarez, D., & Parodi-Camaño, T. (2025). Automatización inteligente para PYMEs mediante chatbots con IA generativa. Transformar, 6(4), 22-32. https://revistatransformar.cl/index.php/transformar/article/view/200
Valeeva, R. A., Kalimullin, A. M., & Khodyreva, E. A. (2023). Impact of modeling in science education: A systematic review. European Journal of Mathematics and Science Technology Education, 19(3), Article em2246. https://doi.org/10.29333/ejmste/13268
Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., Liu, J. B., Yuan, J., & Li, Y. (2021). A review of artificial intelligence in education from 2010 to 2020. Complexity, 2021, Article 8812542. https://doi.org/10.1155/2021/8812542









