In cognitive load theory (CLT), learning is the development of cognitive schemas in a long-term memory with no known limits and can happen only if our limited working memory can process new information presented and the amount of information that does not contribute to learning is low. According to this theory, learning is optimal when instructional support is decreased going from worked examples via completion problem to autonomous problem solving and learners do not benefit from practicing retrieval with complex content. However, studies on productive failure and retrieval practice have provided clear evidence against these two guidelines. In this article, issues with CLT and research inspired by this theory, which remain largely ignored among cognitive load theorists but have likely contributed to these contradictory findings, are discussed. This article concludes that these issues should make us question the usefulness of CLT in health science education, medical education and other complex domains, and presents recommendations for both educational practice and future research on the matter.

According to cognitive load theory (CLT), the limitations of working memory (WM) in the learning of new tasks together with its ability to cooperate with an unlimited long-term memory (LTM) for familiar tasks enable human beings to deal effectively with complex problems and acquire highly complex knowledge and skills. With regard to WM, CLT has focused to a large extent on learning task characteristics, and to a lesser extent on learner characteristics to manage WM load and optimize learning through instructional design. With regard to LTM, explanations of human learning and cognition have mainly focused on domain-general skills, instead of domain-specific knowledge held in LTM. The contributions to this special issue provide a broader cognitive load view on the role of memory in learning and education by presenting the historical roots and conceptual development of the concept of WM, as well as the theoretical and practical implications of current debates about WM mechanisms (Cowan 2014), by presenting an updated model of cognitive load in which the physical learning environment is considered a distinct causal factor for WM load (Choi et al. 2014), by an experimental demonstration of the effects of persistent pain on the available WM resources for learning (Smith and Ayres 2014), and by using aspects of evolutionary educational psychology to argue for the primacy of domain-specific knowledge in human cognition (Tricot and Sweller 2014).

Cognitive load theory has traditionally been associated with individual learning. Based on evolutionary educational psychology and our knowledge of human cognition, particularly the relations between working memory and long-term memory, the theory has been used to generate a variety of instructional effects. Though these instructional effects also influence the efficiency and effectiveness of collaborative learning, be it computer supported or face-to-face, they are often not considered either when designing collaborative learning situations/environments or researching collaborative learning. One reason for this omission is that cognitive load theory has only sporadically concerned itself with certain particulars of collaborative learning such as the concept of a collective working memory when collaborating along with issues associated with transactive activities and their concomitant costs which are inherent to collaboration. We illustrate how and why cognitive load theory, by adding these concepts, can throw light on collaborative learning and generate principles specific to the design and study of collaborative learning.

This study explores how Cognitive Load Theory (CLT) impacts microlearning effectiveness in the Indian educational context. CLT, introduced by John Sweller in the late 1980s, suggests that cognitive capacity influences information processing. The research aims to assess cognitive load in microlearning, gauge its perceived effectiveness, examine the relationship between cognitive load and effectiveness, and explore demographic influences. A structured survey, conducted over 4 weeks with 300 participants from educational institutions and online platforms in India, revealed moderate intrinsic and extraneous cognitive load, with higher germane load. Microlearning modules were highly effective, improving knowledge retention, engagement, and learning outcomes. The study emphasizes managing cognitive engagement and minimizing extraneous load. Demographic factors, such as prior microlearning experience, also influence effectiveness. These findings underscore the importance of balanced instructional design aligned with cognitive load principles, with microlearning emerging as a potent tool for efficient learning.

Research on cognitive load theory (CLT) has focused primarily on identifying the mechanisms and strategies that enhance cognitive learning outcomes. However, CLT researchers have given less attention to the ways in which cognitive load may interact with the motivational and emotional aspects of learning. Motivational beliefs have typically been assumed to be merely a precursor to the cognitive process. This view provides an incomplete picture of the dynamic relationship between cognitive load and motivational beliefs. In this review, we synthesize previous scholarly efforts concerning the motivational effects of anticipated investment of mental effort, new developments in the expectancy-value theory of motivation, and recent findings implicating cognitive load in the formulation of motivational beliefs. By conceptualizing cognitive load as motivational cost, we argue that motivational beliefs are an important outcome that results from instruction. We examine recent empirical evidence supporting this proposition and consider the implications for the further development of both CLT and motivational theories through their integration.

This study explores a new item-writing framework for improving the validity of math assessment items. The authors transfer insights from Cognitive Load Theory (CLT), traditionally used in instructional design, to educational measurement. Fifteen, multiple-choice math assessment items were modified using research-based strategies for reducing extraneous cognitive load. An experimental design with 222 middle-school students tested the effects of the reduced cognitive load items on student performance and anxiety. Significant findings confirm the main research hypothesis that reducing the cognitive load of math assessment items improves student performance. Three load-reducing item modifications are identified as particularly effective for reducing item difficulty: signalling important information, aesthetic item organization, and removing extraneous content. Load reduction was not shown to impact student anxiety. Implications for classroom assessment and future research are discussed.

Cognitive load theory (2011) by John Sweller, Paul Ayres, and Slava Kalyuga presents the state-of-the art form of cognitive load theory (CLT) including instructional guidelines produced by the theory so far. The book achieves this in a precise, detailed and well-organized manner thereby being very informative from the very beginning to the very end. For instance, even the preface provides an ample amount of information about CLT after stating the main premise of this theory: “Without knowledge of human cognitive processes, instructional design is blind.” (p. v). As stated in the book, CLT is that sort of a theory that informs instructional design from a cognitive perspective or on the basis of how human cognition works.

The Cognitive Load Theory (CLT) aims to foster learning productively under optimal cognitive loads. Students across all ages and stages of learning have limited capacity due to the human brain’s functionality. Therefore, an effective learning design allows for knowledge acquisition that will minimize the loading effect on the working memory and foster the transition of knowledge to unlimited long-term memory. This article introduces the Cognitive Load Theory effects within Kinesiology instructional settings. In specific, the authors share examples of three cognitive load effects: (a) goal-free effect, (b) split attention effect, and (c) redundancy effect; and its implementations within the strength and conditioning for educators’ course in higher education settings.

In the traditional framework of cognitive load theory, it is assumed that the acquisition of domain-specific knowledge structures (or schemas) is the only instructional goal, and therefore, the theory is applicable to any instructional task. Accordingly, the basic concepts of intrinsic (productive) and extraneous (unproductive) types of cognitive load were defined based on the relevance (or irrelevance) of the corresponding cognitive processes that impose the load to achieving this universal instructional goal, and the instructional methods advocated by this theory are aimed at enhancing the acquisition of domain-specific schemas. The paper suggests considering this goal within the whole variety of possible specific goals of different learner activities that could be involved in complex learning. This would result in narrowing down of boundaries of cognitive load theory and have implications for distinguishing types of cognitive load, sequencing different goals and instructional tasks, considering the role of learner expertise, and other aspects of complex learning. One of the consequences of this reconceptualization is abandoning the rigid explicit instruction versus minimal guidance dichotomy and replacing it with a more flexible approach based on differentiating specific goals of various learner activities in complex learning. In particular, it may allow reconciling seemingly contradictory results from studies of the effectiveness of worked examples in cognitive load theory (supporting the initial fully guided explicit instruction for novice learners) and studies within the frameworks of productive failure and invention learning that have reportedly demonstrated that minimally guided tasks provided prior to explicit instruction might benefit novice learners.

INTRODUCTION:To design instructions in health sciences education, it is highly relevant to heed the working memory and the approaches for managing cognitive load. In this article, we tried to mention the implications of cognitive load theory (CLT) for optimizing teaching-learning in health sciences education and discussing cognitive load from the perspective of cognitive neurosciences as brain-aware medical education.MATERIALS AND METHODS:We searched databases of Pubmed, Proquest, SCOPUS, and ISI Web of Science for relevant literature in September 1, 2018.RESULTS:The 27 articles out of a total of 46 records, along with 23 papers from snowballing and hand searching were included in this study. Main items encompassed; “Various types of cognitive loads,” “Aim of cognitive load theory,” “Strategies to managing Cognitive Load,” “Cognitive Load Theory in novice and experienced learners and “expertise reversal effect,” Medical and Health Sciences Curriculums and Cognitive Load Theory,” “Challenges of Cognitive Load Theory.”CONCLUSIONS:We discussed six important themes for CLT in health sciences education according to the literature. Mental imagery (visualization) as one of the useful techniques to optimize germane load was suggested, as it processes further gain access to neural circuits that are engaged in sensory, motor, executive, and decision-making pathways in the brain.