Learning science in a virtual reality application: The impacts of animated-virtual actors' visual complexity

  • Authors:
  • Iwan Kartiko;Manolya Kavakli;Ken Cheng

  • Affiliations:
  • Department of Computing, Macquarie University, North Ryde, Sydney, NSW 2109, Australia;Department of Computing, Macquarie University, North Ryde, Sydney, NSW 2109, Australia;Department of Brain, Behaviour and Evolution, Macquarie University, North Ryde, Sydney, NSW 2109, Australia

  • Venue:
  • Computers & Education
  • Year:
  • 2010

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Abstract

As the technology in computer graphics advances, Animated-Virtual Actors (AVAs) in Virtual Reality (VR) applications become increasingly rich and complex. Cognitive Theory of Multimedia Learning (CTML) suggests that complex visual materials could hinder novice learners from attending to the lesson properly. On the other hand, previous studies have shown that visual complexity correlates with presence and may increase the perceived affective quality of the virtual world, towards an optimal experience or flow. Increasing these in VR applications may promote enjoyment and higher cognitive engagement for better learning outcomes. While visually complex materials could be motivating and pleasing to attend to, would they affect learning adversely? We developed a series of VR presentations to teach second-year psychology students about the navigational behaviour of Cataglyphis ants with flat, cartoon, or lifelike AVAs. To assess learning outcomes, we used Program Ratings, which measured perception of learning and perceived difficulty, and retention and transfer tests. The results from 200 students did not reveal any significant differences in presence, perceived affective quality, or learning outcomes as a function of the AVA's visual complexity. While the results showed positive correlations between presence, perceived affective quality and perception of learning, none of these correlates with perceived difficulty, retention, or transfer scores. Nevertheless, our simulation produced significant improvements on retention and transfer scores in all conditions. We discuss possible explanations and future research directions.