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.

Depletion of limited working memory resources may occur following extensive mental effort resulting in decreased performance compared to conditions requiring less extensive mental effort. This “depletion effect” can be incorporated into cognitive load theory that is concerned with using the properties of human cognitive architecture, especially working memory, when designing instruction. Two experiments were carried out on the spacing effect that occurs when learning that is spaced by temporal gaps between learning episodes is superior to identical, massed learning with no gaps between learning episodes. Using primary school students learning mathematics, it was found that students obtained lower scores on a working memory capacity test (Experiments 1 and 2) and higher ratings of cognitive load (Experiment 2) after massed than after spaced practice. The reduction in working memory capacity may be attributed to working memory resource depletion following the relatively prolonged mental effort associated with massed compared to spaced practice. An expansion of cognitive load theory to incorporate working memory resource depletion along with instructional design implications, including the spacing effect, is discussed.

The contradiction between the worked example effect that occurs when learners presented with more instructional guidance learn more than learners presented with less guidance and the generation effect that occurs when the reverse result is obtained can be resolved by the suggestion that the worked example effect is obtained using materials high in element interactivity, whereas simpler, low element interactivity materials result in the generation effect. A 2 (guidance: low vs. high) × 2 (element interactivity: low vs. high) × 2 (expertise: low vs. high) experiment investigated this hypothesis with high school trigonometry learners. On an immediate test, high guidance reflecting a worked example effect was found for novices, but a generation effect was obtained for more knowledgeable learners. In contrast, on a delayed test, a three-way interaction between guidance, element interactivity and expertise was found. This interaction was caused by a worked example effect for material high in element interactivity and a generation effect for material low in element interactivity for novices while for more knowledgeable learners, a generation effect was obtained for both low and high element interactivity materials. These results suggest firstly, that both the worked example and generation effects may be more likely on delayed than immediate tests and secondly, that the worked example effect relies on high element interactivity material while the generation effect relies on low element interactivity material

Background and Aims: The long‐standing aim of cognitive load theory (CLT) has been to generate instructional design principles that show teachers how to instruct students effectively, based on knowledge of the intricacies of human cognitive architecture. Historically, the focus of CLT has been on identifying cognitive processes related to learning and instruction. However, the theory has become more multidisciplinary over time, drawing on theoretical perspectives both within, and beyond, educational psychology. Results: This Editorial presents a brief historical overview of key developments in CLT and seven key themes that are pertinent to research on CLT. These themes are as follows: Level of Expertise, Cognitive Load Measurement, Embodied Cognition, Self‐Regulated Learning, Emotion Induction, Replenishment of Working Memory, and Two Subprocessors of Working Memory. Summaries of the nine empirical contributions to the special issue are presented and discussed in relation to how they provide insight into one or more of these themes. Conclusions: Understanding the variables that impact student learning and instruction has always represented the core aim of CLT. The growing multidisciplinary features of CLT should provide researchers and practitioners with more holistic perspectives of the factors that predict student learning and, in turn, guide instructional design.