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

Bruce Hilliard

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

Autori

Bruce Hilliard Murdoch University,

DOI:

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

Parole chiave:

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

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.

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