Métricas alternativas
Palabras clave
Biología celular
Tecnologías de la Información y la Comunicación;
Desarrollo de capacidades
Cómo citar
Resumen
En el presente artículo se presenta una secuencia de enseñanza y aprendizaje sobre la división celular mitótica para estudiantes de educación secundaria, la cual contiene como apoyo tecnológico una aplicación móvil de realidad aumentada (RA). El objetivo fue promover la visualización del proceso de la división mitótica y con ello promover explicaciones más robustas y complejas evaluadas mediante una clave de niveles de representación. Las actividades propuestas tuvieron por objeto que los participantes fueran capaces de describir, relacionar, explicar e interpretar las diferentes fases de la división celular mitótica. La metodología se sustenta en un diseño preexperimental. Los datos recolectados (n= 162) corresponden a las producciones de los estudiantes (dibujos), que forman parte de las actividades de la secuencia, los cuales son comparados con una matriz de niveles de representación. Los resultados parecen indicar que, a lo largo de la secuencia, las producciones elaboradas por los participantes transitan desde representaciones iniciales que se corresponden con una descripción icónica del proceso hacia representaciones que contienen una mayor carga semántica y semiótica.
Citas
Ainsworth, S. (1999). The functions of multiple representations. Computers in Education, 33(2/3), 131–152. https://doi.org/10.1016/S0360-1315(99)00029-9
Akçayır, M., & Akçayır, G. (2017). Advantages and challenges associated with augmented reality for education: A systematic review of the literature. Educational Research Review, 20, 1–11. https://doi.org/10.1016/j.edurev.2016.11.002
Alexander, B., Ashford-Rowe, K., Barajas-Murphy N., Dobbin, G., Knott J., McCormack, M., Pomerantz, J. Seilhamer R., & Weber, N. (2019). EDUCAUSE Horizon Report: 2019 Higher Education Edition. EDUCAUSE. https://bit.ly/2M9Qv3j
Arici, F., Yildirim, P., Caliklara, Ş., Yilmaz, R. M. (2019). Research trends in the use of augmented reality in science education: Content and bibliometric mapping analysis. Computers & Education, 142. 163647. https://doi.org/10.1016/j.compedu.2019.103647.
Azuma, R., Baillot, Y., Behringer, R., Feiner, S., Julier, S., & MacIntyre, B. (2001). Recent advances in augmented reality. IEEE Computer Graphics and Applications, 21(6), 34-47. https://doi.org/10.1109/38.963459
Barroso-Osuna, J., Cabero, J., & Valencia, R. (2018). Uso educativo de la RA: experiencias en España y México. Enseñanza & Teaching: Revista interuniversitaria de didáctica, 36(2), 7-29. http://dx.doi.org/10.14201/et2018362729
Beveridge, M., & Parkins, E. (1987). Visual representation in analogical problem solving. Memory & Cognition. 15, 230-237. https://doi.org/10.3758/BF03197721
Brooks, M. (2009). Drawing, visualization and young children’s exploration of ‘big ideas. International Journal of Science Education, 31(3), 319–41. https://doi.org/10.1080/09500690802595771
Cabero, J., Barroso, J., & Llorente, C. (2019). Augmented reality in university education. REDU. Revista de Docencia Universitaria, 17(1), 105-118. https://doi.org/10.4995/redu.2019.11256
De Vries, M. S. (1994). Evaluations using nonparametric statistics. Quality and Quantity, 28(1), 1–20. https://doi.org/10.1007/BF01098724
Eilam, B. (2013). Possible constraints of visualization in biology: Challenges in learning with multiple representations. In D. F. Treagust & C. Y. Tsui (eds.), Multiple representations in biological education (pp. 55-73). Springer. https://doi.org/10.1007/978-94-007-4192-8_4
Fabri, D., Falsetti, C., Lezzi, A., Ramazzotti, S., Viola, S., & Leo, T. (2008). Reality virtual and augmented. In A. Adelsberger, J. Kinshuk, J. Pawlowski & D. Sampson (eds.), Handbook on Information Technologies for Education and Training (pp. 113–132). Springer. https://doi.org/10.1007/978-3-540-74155-8_7
Galindo, A. A. G. (2009). Estudio de los seres vivos en la educación básica: Enseñanza del sistema nervioso desde un enfoque para la evolución de los modelos escolares. Universidad Autónoma de Nuevo León.
Garzón, J., Pavón, J. & Baldiris, S. (2019). Systematic review and meta-analysis of augmented reality in educational settings. Virtual Reality 23, 447-459. https://doi.org/10.1007/s10055-019-00379-9
Gilbert, J., & Boulter, C. (1998). Learning Science through Models and Modelling. In B. Fraser & T. Kenneth (eds.), International Handbook of Science Education (pp. 53–66). Kluwer Academic Publishers.
Gilbert, J., Boulter, C., & Rutherford, M. (1998a). Models in explanations, Part 1: Horses for Courses? International Journal of Science Education, 20(1), 83–97. https://doi.org/10.1080/0950069980200106.
Gilbert, J., Boulter, C., & Rutherford, M. (1998b). Models in Explanations, Part 2: Whose Voice? Whose Ears? International Journal of Science Education, 20(2), 187–203. https://doi.org/10.1080/0950069980200205.
Gilbert J. K. (2005). Visualization: A Metacognitive Skill in Science and Science Education. In J. K. Gilbert (ed.), Visualization in Science Education. Models and Modeling in Science Education, vol 1 (pp. 9-27). Springer. https://doi.org/10.1007/1-4020-3613-2_2
Gilbert, J. (2008). Visualization: An emergent field of practice and enquiry in science education. In J. K. Gilbert, M. Reiner & Nakleh M. (eds.), Visualization: Theory and Practice in Science Education (pp. 3-24). Springer. https://doi.org/10.1007/978-1-4020-5267-5_1
Gilbert, J., & Justi, R. (2016). Modelling-based teaching in science education (Vol. 9). Springer International Publishing. https://doi.org/10.1007/978-3-319-29039-3
Gonzalez, A. A., Lizana, P. A., Pino, S., Miller, B. G., & Merino, C. (2020). Augmented reality-based learning for the comprehension of cardiac physiology in undergraduate biomedical students. Advances in Physiology Education, 44(3), 314–322. https://doi.org/10.1152/advan.00137.2019
Guidoni, P. (1985). The natural thinking. European Journal of Science Education, 7(2), 133-140
Izquierdo, M. (2007). Enseñar ciencias, una nueva ciencia. Enseñanza de las Ciencias Sociales, 6, 125-138.
Jones, M. G., Gardner, G., Taylor, A., Wiebe, E., & Forrester, J. (2011). Conceptualizing magnification and scale: The roles of spatial visualization and logical thinking. Research in Science Education, 41(3), 357-368. https://doi.org/10.1007/s11165-010-9169-2
Justi, R. (2006). La enseñanza de ciencias basada en la elaboración de modelos. Enseñanza de las Ciencias, 24(2), 173–184.
Jorba, J., & Sanmartí, N. (1996). Enseñar, aprender y evaluar: un proceso de regulación continua. Propuesta didáctica para las áreas de ciencias de la naturaleza y las matemáticas. Ministerio de Educación y Cultura. https://bit.ly/2M9B6zY
Krajcik, J., Simmons, P., & Lunetta, V. (1988). A research strategy for the dynamic study of students’ concepts and problem-solving strategies using science software. Journal of Research in Science Teaching, 25(2), 147–55. https://doi.org/10.1002/tea.3660250206.
Kozma, R., & Russell, J. (2005). Students becoming chemists: developing representation competence. In J. K. Gilbert (ed.), Visualization in Science Education (pp. 121–145). Springer Netherlands. https://doi.org/10.1007/1-4020-3613-2_8
Lemke, J. (1997). Aprender hablar ciencias. Lenguaje, aprendizaje y valores. Paidós.
Madden, L. (2011). Professional Augmented Reality Browsers for Smartphones: Programming for Junaio, Layar & Wikitude. Wiley Publishing, Inc.
Mathai, S., & Ramadas, J. (2009). Visuals and visualization of human body systems. International Journal of Science Education, 31(3), 439-58. https://doi.org/10.1080/09500690802595821
Mayer, R. E. (1997). Multimedia learning: are we asking the right questions? Educational Psychologist, 32, 1–19. https://doi.org/10.1080/09500690500060417
Merino, C., & García, Á. (2019). Incorporation of augmented reality for the development of visualization capabilities. A study of high school students understanding of the atomic model. Pensamiento Educativo, 56(2), 1–23. https://doi.org/10.7764/PEL.56.2.2019.6
Merino, C., Pino, S., Meyer, E., Garrido, J. M., & Gallardo, F. (2015). Realidad aumentada para el diseño de secuencias de enseñanza-aprendizaje en química. Educación Química, 26(2), 94–99. https://doi.org/10.1016/j.eq.2015.04.004
Munford, D., & Teles, A. P. S. S. (2015). Argumentação e a construção de oportunidades de aprendizagem em aulas de ciências. Ensaio Pesquisa Em Educação Em Ciências (Belo Horizonte), 17(spe), 161–185. https://doi.org/10.1590/1983-2117201517s09
Pedaste, M., Mitt, G., & Jürivete, T. (2020). What is the effect of using mobile augmented reality in K12 inquiry-based learning? Education Science, 10(4), 94. https://doi.org/10.3390/educsci10040094
Polya, G. (1957). Matemáticas y Razonamiento Plausible. Tecnos.
Órdenes R., Arellano, M., Jara, R. & Merino, C. (2014). Representaciones macroscópicas, submicroscópicas y simbólicas sobre la materia. Educación Química, 25(1), 46-55. https://bit.ly/2YdUezt
Renström, L., Andersson, B., & Marton, F. (1990). Students' conceptions of matter. Journal of Educational Psychology, 82(3), 555-569. https://doi.org/10.1037/0022-0663.82.3.555
Robles Garrote, P., & Rojas, M. del C. (2015). La validación por juicio de expertos: dos investigaciones cualitativas en Lingüística aplicada. Revista Nebrija de Lingüística Aplicada 18, 1-16. https://bit.ly/3ojvdxn
Rundgren, C., Hirsch, R., Chang, S., & Tibell, L (2012). Students’ communicative resources in relation to their conceptual understanding the role of non-conventionalized expressions in making sense of visualizations of protein function. Research in Science Education, 42(5), 891–913. https://doi.org/10.1007/s11165-011-9229-2.
Safar A. H. (2017) The effectiveness of using augmented reality apps in teaching the English alphabet to kindergarten children: a case study in the state of Kuwait. Eurasia Journal of Mathematics, Science and Technology Education, 13(2), 417-440. https://doi.org/10.12973/eurasia.2017.00624a
Selley, N. (2000). Students’ spontaneous use of a particulate model for dissolution. Research in Science Education, 30(4), 389-402. https://doi.org/10.1007/BF02461558
Spinelli, B., Morales, C., Merino, C., & Quiroz, W. (2016). Realist ontology and natural processes: a semantic tool to analyze the presentation of the osmosis concept in science texts. Chemistry Education Research and Practice, 17(4), 646–655. https://doi.org/10.1039/C5RP00219B
StataCorp. (2019). Stata Statistical Software: Release 16. StataCorp LLC.
Taber, K. S. (2018). The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education. Research in Science Education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2
Tang, K. S., Cheng, D. L., Mi, E., & Greenberg, P. B. (2020). Augmented reality in medical education: a systematic review. Canadian Medical Education Journal, 11(1), e81–e96. https://doi.org/10.36834/cmej.61705
Tsui, C. Y., & Treagust, D. F. (2013). Introduction to multiple representations: Their importance in biology and biological education. In D. Y. Treagust & C. Y. Tsui (eds.), Multiple representations in biological education (pp. 3-18). Springer. https://doi.org/10.1007 / 978-94-007-4192-8_1
Yu, D., Jin, J. S., Luo, S., Lai, W., & Huang, Q. (2009). A useful visualization technique: a literature review for augmented reality and its application, limitation; future direction. In M. L. Huang, Q. V. Nguyen & K. Zhang (eds.), Visual Information Communication (pp. 311-337). Springer US. https://doi.org/10.1007/978-1-4419-0312-9_21
Winterbottom M. (2017). Teaching and Learning Biology. In Taber K. S. & B. Akpan (eds.), Science Education. New Directions in Mathematics and Science Education. Sense Publishers. https://doi.org/10.1007/978-94-6300-749-8_25
Esta obra está bajo licencia internacional Creative Commons Reconocimiento-NoComercial-SinObrasDerivadas 4.0.