Paul Ayres is an Emeritus Professor of Educational Psychology at the University of New South Wales, Australia. He has conducted research into cognitive load theory for 35 years, and made a number of contributions to the findings associated with the goal-free effect, worked examples, the expertise reversal effect, split-attention, isolating elements, multimedia effects, the transient information effect, and general problem-solving strategies. He is also interested in mathematics education and effective classroom teaching.
In cognitive load theory (CLT), it is generally accepted that learning through problem solving is difficult for novices due to extraneous cognitive load, which can be eliminated by using worked examples. In contrast, for more expert learners worked examples generate extraneous cognitive load, and therefore problem solving is a superior approach. The current presentation argues that some assumptions underpinning these findings and other CLT effects are too simplistic and need further refinement. Hence, some basic definitions of cognitive load are challenged, leading to some suggestions for updating CLT learning models. Furthermore, some general problem solving, and generative learning strategies are examined in terms of developing transfer, motivation, collaboration and ‘21st century skills’.
Maria Opfermann is a postdoctoral researcher and lecturer at the University of Wuppertal. Her activities are focused on multimedia learning, self-regulation and, surprisingly, cognitive load. She has contributed to research on cognitive load measurement (especially the question, when cognitive load should be assessed), generative learning activities such as drawing and the role of decorative pictures for learning. As part of the elementary school department, she is now especially interested in ways to optimize learning and cognitive load for very young learners.
During the latest two decades, a vast amount of great research has dealt with the question of how cognitive load and learning can be optimized when we encourage or stimulate generative learning activities. For instance, the benefits of drawing have attracted much attention. However, much of this research has focused on high school or university students, and the few studies in elementary school reveal mixed results at best, which seems surprising given that drawing in general is among the favorite activities of children. This keynote will go into more detail with the question of how drawing and other generative learning activities can be used to enhance children’s learning, reduce their cognitive load and keep their enthusiasm about the knowledge they are about to gain.
Juan C. Castro-Alonso (Cris Castro) is Associate Researcher at the Center for Advanced Research in Education, Universidad de Chile. He is a Biochemist, Masters in Communication and Education, and PhD in Education. His interests are visuospatial processing and spatial ability, cognitive load theory, STEM and biology education, gender differences, and multimedia learning. He is leading an investigation on how cognitive load and learners’ characteristics affect performance on visuospatial processing.
An innovative development of cognitive load theory suggests that human cognition operates like evolution, as both are biological information systems that follow five principles. This development of cognitive load theory has notable potential, as evolution is a robust theory that can inspire analogies to explain phenomena of human cognition and learning. But despite this possibility of enriching cognitive load theory, the analogy between human cognition and evolution has not been given enough attention. This presentation will describe likely explanations for this relative apathy, including that the analogy is not straightforward. Simpler and novel analogical links will be provided, ideally inspiring cognitive load theory researchers to mirror evolution phenomena into human cognition and learning.