Optimizando la complejidad para mejorar el aprendizaje = Optimising Complexity to Improve Learning

Autores/as

  • Bruce Hilliard Murdoch University,

DOI:

https://doi.org/10.18002/tele(in)2j.v1i0.5145

Palabras clave:

Education, Learning Design, Psychology, Psychophysics, Cognitive Load Theory, Cognitive Science, Educación, Diseño de aprendizaje, psicología, psicofísica, Teoría cognitiva de carga, Ciencia Cognitiva

Resumen

Abstract


This paper addresses a key element of design, which relates to the level of complexity in the visual material, and its effect on viewer comprehension and impressions. To help quantify this effect, an indicative Complexity Curve modelwas developed from previous research on the topic. This Complexity Curve showed that moderate complexity was mostlikely to produce optimal learning outcomes. To test this model, a series of Control Presentations were created, which applied moderate complexity. Variants of these presentations were then developed, so the only difference between the control and variant presentations was the application of specific changes in the complexity of the visualisation. These
included the use of incongruent pictures, providing very low complexity content, and increasing the complexity by
adding extraneous animations. Comprehension and impressions data was then collected through a formal experimental process. This collected data indicated that the developed Complexity Curve appeared to have validity. These results hold important implications for learning design and all forms of computer-based visual design.

Resumen

Este estudio trata sobre un elemento clave de diseño, relacionado con el nivel de complejidad del material visual, y su efecto sobre la comprensión e impresiones sobre la audiencia. Para cuantificar este efecto, se ha desarrollado un modelo indicativo de la curva de complejidad, basándose en investigaciones previas sobre este tema. Esta curva de complejidad ha mostrado que una complejidad moderada, tiende a producir resultados óptimos de aprendizaje. Para probar este modelo, se crearon una serie de presentaciones control, con la aplicación de complejidad moderada. Después, se desarrollaron variaciones de estas presentaciones. La única diferencia entre las presentaciones control y las variaciones fue la aplicación de cambios específicos en la complejidad de los elementos visuales. Los cambios incluyeron el uso de imágenes incongruentes, que tenían contenido de muy baja complejidad y se fue aumentando la complejidad con la adición de animaciones superfluas. Los datos sobre la comprensión y las impresiones fue recopilada a través de un proceso experimental formal. Los datos recogidos indican que la curva de complejidad desarrollada a partir de estos datos, es válida. Estos resultados tienen implicaciones importantes para el diseño del aprendizaje y todas las formas de diseño
visual basado en ordenador.

 

Descargas

Los datos de descargas todavía no están disponibles.

Citas

Balfanz, R., Herzog, L., & Mac Iver, D. (2007). Preventing student disengagement and keeping students on the graduation path in urban middle-grades schools: Early identification and effective interventions. Ecological Psychology, 42(4), 223-235.

Bennett, K. B., Toms, M. L., & Woods, D. D. (1993). Emergent reatures and graphical elements: Designing more effective configural displays. Human Factors: The Journal of the Human Factors and Ergonomics Society, 35(1), 71-97.

Berlyne, D. E. (1963). Complexity and incongruity variables as determinants of exploratory choice and evaluative ratings. Canadian Journal of Psychology, 17(3), 274-290.

Berlyne, D. E. (1970). Novelty, complexity and hedonic value. Perception and Psychophysics, 8(5A), 279-286.

Brünken, R., Plass, J. L., & Leutner, D. (2004). Assessment of cognitive load in multimedia learning with dual-task methodology: Auditory load and modality effects. Instructional Science, 32, 115-132.

Butcher, K. R. (2003). Effects of diagram complexity on comprehension processes and learning outcomes. (3113068 Ph.D.), University of Colorado at Boulder, Colorado, USA. ProQuest Dissertations & Theses Full Text database.

Cohen, J. (1988). Statistical power analysis for the behavioral Sciences ( 2nd ed.). Hillsdale, New Jersey, USA: Erlbaum.

Cummings, M. L., & Tsonis, C. G. (2006). Partitioning complexity in air traffic management tasks. The International Journal of Aviation Psychology, 16(3), 277-295. doi:10.1207/s15327108ijap1603 3

Day, H. (1967). Evaluations of subjective complexity, pleasingness and interestingness for a series of random polygons varying in complexity. Perception and Psychophysics, 2(7),281-286.

De Westelinck, K., Valcke, M., De Craene, B., & Kirschner, P. (2005). Multimedia learning in social sciences: Limitations of external graphical representations. Computers in Human Behavior, 21(4), 555-573.

Donderi, D. C. (2006). Visual complexity: A review. Psychological Bulletin, 132(1), 73-97. doi:10.1037/0033-2909.132.1.73

Duarte, N. (2008). slide:ology. Sebastopol, California, USA: O’Reilly Media.

Geissler, G. L., Zinkhan, G. M., & Watson, R. T. (2006). The influence of home page complexity on consumer attention, attitudes and purchase intent. Journal of Advertising, 35(2), 69-80.

Granger, B. P. (2012). Enhancing training outcomes in the context of e-Learning: The impact of objective learner control, training content complexity, cognitive load, learning goal orientation, and metacognitive strategies. (3545794 Ph.D.), University of South Florida, Florida, USA.

Green, R. (1981). Remembering ideas from text: The effect of modality of presentation. British Journal of Educational Psychology, 51(1), 83-89. doi:10.1111/j.2044-8279.1981.tb02458.x

Hilliard, B. A. (2016). Optimising viewer comprehension and shaping impressions and attention: through the formatting of content in tools like Microsoft PowerPoint. (PhD), Murdoch University, Perth, Western Australia.

Hillyard, A. L. (1979). Stimulus complexity during original learning and generalization. (0353229 Ph.D.), University of Alberta (Canada), Alberta, Canada.

Huff, M., & Schwan, S. (2011). Integrating information from two pictorial animations: Complexity and cognitive prerequisites influence performance. Applied Cognitive Psychology, 25(6), 878-886. doi:10.1002/acp.1762

Makaramanee, R. (1985). Pictorial stimulus complexity in texbooks (Design, Visual Aids, Grades 1-12 Analysis). (8528347 Ph.D.), Texas A&M University, College Station, Texas, USA.

Marks, H. M. (2000). Student engagement in instructional activity: Patterns in the elementary, middle and high school years. American Educational Research Journal, 37(1), 153-184.

McNamara, D. S., Kintsch, E., Songer, N. B., & Kintsch,W.(1996). Are good texts always better? Interactions of text coherence, background knowledge, and levels of understanding in learning from text. Cognition and Instruction, 14(1), 1-43. doi:10.2307/3233687

Mineo, B. A., Peischl, D., & Pennington, C. (2008). Moving targets: The effect of animation on identification of action word representations. AAC: Augmentative & Alternative Communication, 24(2), 162-173.

Moreno, R., & Mayer, R. E. (1999). Cognitive principles of multimedia learning - The role of modality and contiguity. Journal of Educational Psychology, 91(2), 358-358.

Paas, F., van Gog, T., & Sweller, J. (2010). Cognitive Load Theory: New conceptualisations, specifications, and integrated research perspectives. Educational Psychology Review, 22, 115-121.

Pathiavadi, C. S. (2009). Exploring efficient design approaches for display of multidimensional data to facilitate interpretation of information. (3420611 Ph.D.), University of South Florida, Florida, USA.

Rauterberg, M. (1994). About the relationship between incongruity, complexity and information: design implications for man-machine systems. In W. Rauch, F. Strohmeier, H. Hiller, & C. Schl¨ogl (Eds.), Mehrwert von Information - Professionalisierung der Informationsarbeit. Konstanz, Switzerland: Universitätsverlag.

Rayner, K., Reichle, E. D., Stroud, M. J., Williams, C. C., & Pollatsek, A. (2006). The effect of word frequency, word predictability, and font difficulty on the eye movements of young and older readers. Psychology and Aging, 21(3), 448-448.

Roberts, M. N. (2007). Complexity and aesthetic preference for diverse visual stimuli. (Doctoral), Universitat de les Illes Balears, Palma, Spain.

Rosenthal, J. A. (1996). Qualitative descriptors of strength of association and effect size. Journal of social service Research, 21(4), 37-59.

Schnotz, W., & Kurschner, C. (2007). A reconsideration of Cognitive Load Theory. Educational Psychology Review, 19, 469-508.

Schnotz, W., & Rasch, T. (2005). Enabling, facilitating, and inhibiting effects of animations in multimedia learning:Why reduction of cognitive load can have negative results on learning. Educational Technology, Research and Development, 53(3), 47-58.

Surenda, N. S., Nikunj, D., & Spears, N. (2005). Understanding web home page perception. European Journal of Information Systems (14), 288-302.

Terwilliger, R. F. (1963). Pattern complexity and affective arousal. Perceptual and Motor Skills, 17(2), 387-395. doi:10.2466/pms.1963.17.2.387

Thorson, E., Reeves, B., & Schleuder, J. (1985). Message complexity and attention to television. Communication Research, 12(4), 427-454.

Tuch, A. N., Bargas-Avila, J. A., Opwis, K., & Wilhelm, F. H. (2009). Visual complexity of websites: Effects on users’experience, physiology, performance, and memory. International Journal of Human-Computer Studies, 67(9), 703-715.

Tufte, E. R. (1990). Envisioning information. Cheshire, Connecticut, USA: Graphics Press.

Tufte, E. R. (1997). Visual explanations: Images and quantities, evidence and narrative. Cheshire, Connecticut, USA: Graphic Press.

Tufte, E. R. (2001). The visual display of quantitative information. Cheshire, Connecticut, USA: Graphic Press.

Vitz, P. C. (1966). Preference for different amounts of visual complexity. Psychology / Social Sciences (General), 11(2), 105-114.

Wang, Q., Yang, S., Liu, M., Cao, Z., & Ma, Q. (2014). An eye-tracking study of website complexity from cognitive load perspective. Decision Support Systems, 62, 1-10.

Wu, O., Hu, W., & Shi, L. (2013). Measuring the visual complexities of web pages. ACM Trans. Web, 7(1), 1-34.doi:10.1145/2435215.2435216

Descargas

Publicado

2017-10-04

Cómo citar

Hilliard, B. (2017). Optimizando la complejidad para mejorar el aprendizaje = Optimising Complexity to Improve Learning. Teaching & Learning Innovation Journal = Revista de Innovación en la Enseñanza y el Aprendizaje, 1, 1–8. https://doi.org/10.18002/tele(in)2j.v1i0.5145

Número

Sección

Artículos