Gramática cinematográfica y animación 3D para la divulgación de la ciencia

  1. Amador García, Esteban Manuel 1
  2. Díaz Alemán, Manuel Drago
  3. de la Torre Cantero, Jorge 2
  1. 1 Departamento de Bellas Artes, Universidad de La Laguna
  2. 2 Departamento de Proyectos y Técnicas en Ingeniería y Arquitectura de la Universidad de La Laguna
Revista:
Fotocinema: revista científica de cine y fotografía

ISSN: 2172-0150

Año de publicación: 2023

Título del ejemplar: Comunicación, divulgación y representación mediática de la ciencia

Número: 27

Páginas: 33-56

Tipo: Artículo

DOI: 10.24310/FOTOCINEMA.2023.VI27.16510 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Otras publicaciones en: Fotocinema: revista científica de cine y fotografía

Resumen

Prestar especial atención al lenguaje audiovisual empleado en las producciones destinadas a la difusión del conocimiento científico, juega un papel importante en los procesos de transferencia del conocimiento y es crucial para despertar el interés por la ciencia. En la actualidad, nuestra cultura visual está fuertemente influenciada por el material audiovisual creado a través de la industria del entretenimiento, entre las que se encuentran la potente industria del videojuego y el Cine, actores de un proceso de influencias mutuas repletas de afecciones recíprocas. En este trabajo se aborda la realización de material audiovisual destinado a la  divulgación de contenido científico, haciendo uso de tecnologías gráficas avanzadas como el modelado y la animación 3D. El uso de esta tecnología se pone al servicio de una gramática visual heredada de la industria cinematográfica. La conjunción de ambos elementos se ejemplifica haciendo un análisis de la producción audiovisual de divulgación científica titulada “La célula. Unidad de vida”.

Referencias bibliográficas

  • Citas Ainsworth, S. (2008). How do animations influence learning. Current perspectives on cognition, learning, and instruction: Recent innovations in educational technology that facilitate student learning, 37-67.
  • Anderson, J., Barnes, E., y Shackleton, E. (2011). The art of medicine: over 2,000 years of images and imagination. University of Chicago Press.
  • Bayo, I., Menéndez, O., Fuertes, I., Milán, M., y Mecha, R. (2019). La Comunidad Científica ante las Redes Sociales. Guía de Actuación para Divulgar Ciencia a través de ellas. DIVULGA.
  • Barr, M. (2017). Video games can develop graduate skills in higher education students: A randomised trial. Computers & Education, 113, 86-97.
  • Berney, S., y Bétrancourt, M. (2016). Does animation enhance learning? A meta-analysis. Computers & Education, 101, 150-167.
  • Berney, S., y Bétrancourt, M. (2017). Learning three-dimensional anatomical structures with animation: Effect of orientation references and learners’ spatial ability. Learning from Dynamic Visualization: Innovations in Research and Application, 279-303.
  • Blanz, V., Vetter, T., Bülthoff, H. H., y Tarr, M. J. (1995, August). What object attributes determine canonical views?. In 18th European Conference on Visual Perception (ECVP 1995) (pp. 119-120). Pion Ltd..
  • Boon, T. (2008). Films of fact: a history of science in documentary films and television. Wallflower Press.
  • Botsis, T., Fairman, J. E., Moran, M. B., y Anagnostou, V. (2020). Visual storytelling enhances knowledge dissemination in biomedical science. Journal of biomedical informatics, 107, 103458.
  • Carroll, N., y Seeley, W. P., (2013). Cognitivism, psychology, and neuroscience: Movies as attentional engines.
  • Castro-Alonso, J. C., Ayres, P., y Paas, F. (2016). Comparing apples and oranges? A critical look at research on learning from statics versus animations. Computers & Education, 102, 234-243.
  • Cutting, J. E. (2005). Perceiving scenes in film and in the world. Moving image theory: Ecological considerations, 9-27.
  • Davis, L. S., y León, B. (2018). New and old narratives: Changing narratives of science documentary in the digital environment. In Communicating Science and Technology through Online Video (pp. 55-63). Routledge.
  • de Koning, B. B., y Jarodzka, H. (2017). Attention guidance strategies for supporting learning from dynamic visualizations. Learning from dynamic visualization: Innovations in research and application, 255-278.
  • Diwadkar, V. A., y McNamara, T. P. (1997). Viewpoint dependence in scene recognition. Psychological science, 8(4), 302-307.
  • Emhardt, S. N., Jarodzka, H., Brand-Gruwel, S., Drumm, C., Niehorster, D. C., y van Gog, T. (2022). What is my teacher talking about? Effects of displaying the teacher’s gaze and mouse cursor cues in video lectures on students’ learning. Journal of Cognitive Psychology, 34(7), 846-864.
  • Frank, S. (2003). Reel reality: Science consultants in Hollywood. Science as Culture, 12(4), 427-469.
  • Garsoffky, B., Schwan, S., y Huff, M. (2009). Canonical views of dynamic scenes. Journal of Experimental Psychology: Human Perception and Performance, 35(1), 17.
  • Gouyon, J. B. (2016). Science and film-making. Public Understanding of Science, 25(1), 17-30.
  • Hegarty, M. (2004). Dynamic visualizations and learning: Getting to the difficult questions. Learning and Instruction, 14(3), 343-351.
  • Huk, T. (2006). Who benefits from learning with 3D models? The case of spatial ability. Journal of computer assisted learning, 22(6), 392-404.
  • Iwasa, J. H. (2016). The scientist as illustrator. Trends in immunology, 37(4), 247-250.
  • Jenkinson, J., y McGill, G. (2012). Visualizing protein interactions and dynamics: evolving a visual language for molecular animation. CBE—Life Sciences Education, 11(1), 103-110.
  • Jenkinson, J. (2017). The role of craft-based knowledge in the design of dynamic visualizations. Learning from dynamic visualization: Innovations in research and application, 93-117.
  • Khooshabeh, P., y Hegarty, M. (2010, March). Representations of shape during mental rotation. In AAAI Spring symposium: Cognitive shape processing (pp. 15-20).
  • Latour, B. (1990). Technology is society made durable. The sociological review, 38(1_suppl), 103-131.
  • Lowe, R. K., y Schnotz, W. (2014). Animation principles in multimedia learning. The Cambridge handbook of multimedia learning, 2, 513-546.
  • Lowe, R., y Ploetzner, R. (2017). Learning from dynamic visualization. Cham, Switzerland: Springer.
  • Lowe, R., y Boucheix, J. M. (2017). A composition approach to design of educational animations. Learning from dynamic visualization: Innovations in research and application, 5-30.
  • Loschky, L. C., Larson, A. M., Smith, T. J., y Magliano, J. P. (2020). The scene perception & event comprehension theory (SPECT) applied to visual narratives. Topics in cognitive science, 12(1), 311-351.
  • Macedo, B., y de Montevideo, U. O. (2016). Educación científica.
  • Maddock, D. (2019). Reframing cinematography. Media Practice and Education, 20(1), 44-66.
  • Malkiewicz, K., y Mullen, M. D. (2009). Cinematography. Simon and Schuster.
  • Mascelli, J. V. (1965). The five C's of cinematography (Vol. 1). Hollywood: Grafic Publications.
  • Mayer, R. E., y Moreno, R. (2002). Animation as an aid to multimedia learning. Educational psychology review, 14, 87-99.
  • Mayer, R. E. (2017). Using multimedia for e?learning. Journal of computer assisted learning, 33(5), 403-423.
  • McGill, G. G. (2017). Designing instructional science visualizations in the trenches: Where research meets production reality. Learning from dynamic visualization: Innovations in research and application, 119-150.
  • McGill, G. G. (2022). Knowledge synthesis through scientific visualization. Nature Microbiology, 7(2), 185-185.
  • Mital, P. K., Smith, T. J., Hill, R. L., y Henderson, J. M. (2011). Clustering of gaze during dynamic scene viewing is predicted by motion. Cognitive computation, 3, 5-24.
  • National Research Council. (1996). National science education standards. National Academies Press.
  • Ploetzner, R., Berney, S., y Bétrancourt, M. (2021). When learning from animations is more successful than learning from static pictures: learning the specifics of change. Instructional Science, 49(4), 497-514.
  • Sanchez, C. A., y Wiley, J. (2017). Dynamic visuospatial ability and learning from dynamic visualizations. Learning from dynamic visualization: Innovations in research and application, 155-176.
  • Schwan, S. (2013). The art of simplifying events.
  • Schnotz, W., y Lowe, R. K. (2008). A unified view of learning from animated and static graphics. Learning with animation: Research implications for design, 304-356.
  • Smith, T. J., Levin, D., y Cutting, J. E. (2012). A window on reality: Perceiving edited moving images. Current Directions in Psychological Science, 21(2), 107-113.
  • Tarr, M. J. (1995). Rotating objects to recognize them: A case study on the role of viewpoint dependency in the recognition of three-dimensional objects. Psychonomic Bulletin & Review, 2, 55-82.
  • Teplá, M., Teplý, P., y Šmejkal, P. (2022). Influence of 3D models and animations on students in natural subjects. International Journal of STEM Education, 9(1), 65.
  • Tversky, B., Heiser, J., Mackenzie, R., Lozano, S., y Morrison, J. (2008).+Enriching animations. Learning with animation: Research implications for design, 263-285.
  • Van Dijck, J. (2006). Picturizing science: The science documentary as multimedia spectacle. International Journal of Cultural Studies, 9(1), 5-24.
  • Winston, B. (2012). The documentary film as scientific inscription. In Theorizing documentary (pp. 37-57). Routledge.