John Sweller’s research while affiliated with UNSW Sydney and other places

The spacing effect occurs when learning with rest periods is superior to learning without rest periods. Cognitive load theory has explained this superiority by working memory resource depletion, under which resources are depleted during cognitive activity but restored with rest. In a series of four experiments involving 341 participants, we explored the relationships between the spacing effect, depletion of working memory resources, and mental rehearsal, particularly focusing on how these dynamics are influenced by task complexity as defined by element interactivity. Experiment 1 showed that materials with higher element interactivity had a greater impact on working memory resource depletion. In Experiment 2, using materials low in element interactivity, a spacing effect was obtained with no evidence of working memory resource depletion. Instead, results suggested that the effect might be due to mental rehearsal occurring during rest periods. Experiment 3, using more complex information, obtained both the spacing and working memory resource depletion effects for less knowledgeable learners for whom the information was high in element interactivity. In Experiment 4, testing more knowledgeable learners for whom the same information was lower in element interactivity, both effects disappeared. The results indicated that working memory resource depletion and recovery may be more sensitive to materials high in element interactivity and suggest that it is only one of multiple causes of the spacing effect.

The use of investigations in science teaching is both common and commonly advocated for in science education literature. We suggest that the use of investigations should differ depending on the complexity of the subject matter. That complexity can vary depending on both the nature of the information and students’ expertise levels. The present study used Cognitive Load Theory and tested a hypothesis that the sequential order of having investigations first followed by explicit instruction only is more effective than that of having explicit instruction first when students have acquired sufficiently high levels of knowledge. This hypothesis was tested with 85 middle school students. Participants were randomly assigned to one of the two sequences. The results indicated that for sufficiently knowledgeable students, a dis-ordinal knowledge level by sequence interaction was obtained. There was an advantage to the explicit instruction first approach for the less knowledgeable students for whom element interactivity was high but an advantage to the investigation first approach for the more knowledgeable students for whom element interactivity was lower. The results were discussed in light of a recent debate between the authors and De Jong et al. (Educational Research Review, 39, 1-14, 2023) on the role of investigations and explicit instruction in science education.

The mechanisms that govern biological evolution and human cognition are analogous, as both follow the same principles of natural information processing systems. In this article, we describe the following five principles that provide an analogy between biological evolution and human cognition: (a) Randomness as Genesis Principle and (b) Borrowing and Reorganizing Principle, which indicate how natural information processing systems obtain information; (c) Narrow Limits of Change Principle and (d) Information Store Principle, which indicate how information is processed and stored; and (e) Environmental Organizing and Linking Principle, which indicate how stored information is used to generate actions appropriate to an environment. In human cognition, these analogs only apply to cognitive processes associated with biologically secondary knowledge, the knowledge typically taught in educational institutions. Based on these five principles, cognitive load theory researchers have provided diverse prescriptions to optimize instructional activities and materials. We conclude by discussing general instructional implications and future research directions based on this analogy.

The interleaving effect indicates that students learn better from multiple areas that are interleaved rather than blocked. Two experiments tested the hypothesis that the effect is because interleaving facilitates comparisons between areas and is a variation of the variability effect that increases intrinsic cognitive load. Experiment 1 used an interleaved design with two obviously different topics and found no interleaving effect. Experiment 2 used a similar design but used topics that were more difficult to discriminate between, resulting in a clear advantage for the interleaved group associated with an increase in cognitive load. These results support the hypothesis that the interleaving and variability effects are closely related.

Cognitive load theory has been in development since the 1980s. Much of the impetus for that development has come from firstly, replication failures using randomised controlled trials and secondly, from the incorporation of other theories into cognitive load theory. Both have led to theory expansion. The immediate cause of the so-called “replication crisis” in psychology and other disciplines is a failure to replicate previous empirical findings. Using cognitive load theory as an example, I argue that the appearance of contradictory evidence does not necessarily derive from a failure to properly collect data. Rather, it can be caused by initially insufficiently detailed theories, with increasing detail often revealing the reason for a failure to replicate. For cognitive load theory, each failure to replicate, rather than being a negative, contributed to the further development of the theory. In addition, the theory has developed over many years by closely incorporating other theories associated with human cognitive architecture and evolutionary psychology. In this paper, I discuss some of the developmental milestones associated with cognitive load theory and how they were informed by replication failures and theory integration.

Educational researchers have been confronted with a multitude of definitions of task complexity and a lack of consensus on how to measure it. Using a cognitive load theory-based perspective, we argue that the task complexity that learners experience is based on element interactivity. Element interactivity can be determined by simultaneously considering the structure of the information being processed and the knowledge held in long-term memory of the person processing the information. Although the structure of information in a learning task can easily be quantified by counting the number of interacting information elements, knowledge held in long-term memory can only be estimated using teacher judgment or knowledge tests. In this paper, we describe the different perspectives on task complexity and present some concrete examples from cognitive load research on how to estimate the levels of element interactivity determining intrinsic and extraneous cognitive load. The theoretical and practical implications of the cognitive load perspective of task complexity for instructional design are discussed.