Over the last few weeks, I have been intrigued by the concept of optimising learning by limited cognitive overload. While this concept is not new, it was a great opportunity to reread some of the evidence base and look for areas of my own practice that could be honed.
Educators play a crucial role in shaping the learning experiences of their students. One key aspect of effective teaching is understanding the concept of cognitive load and its impact on learning. Cognitive load theory (CLT) provides a framework for educators to design instruction that minimises mental distraction and maximises student learning. In this post, I will explore the different types of cognitive load, the phenomenon of cognitive overload, and practical strategies for optimising learning in the classroom.
As educators, our goal is to facilitate learning and help students reach what they can achieve. To attain this, we must understand how the human mind processes information. We realise the human brain is a remarkable learning machine, but it has its limits. Our own ability to process and retain information is constrained by the capacity of our working memory, a temporary storage system for conscious thought (Baddeley, 2000; Sweller, 2011). This could be likened to a computer's random access memory or RAM which holds pieces of data that the device immediately requires for short amounts of time otherwise, it is stored on the hard drive for longer term use.
As adults, we regularly face experiences of cognitive overload. When this happens we mentally struggle to focus, make decisions, or remember things (Sweller, 2011). This can lead to frustration, anxiety, and even withdrawal. Physically, headaches and fatigue might arise. Chronic overload can lead to chronic stress and burnout (van der Vleuten & Driessen, 2014).
Now consider the nuanced effects when applied to children that do not have a developed cerebral cortex. While the core effects of cognitive overload may mirror adults (trouble focusing, frustration, withdrawal), the nuances lie in their developing brains (Diamond, 2000). Limited awareness of their own mental state can lead to intense emotional responses and difficulty communicating overload. Their still-forming working memory makes them especially vulnerable, hindering learning, skill development, and motivation (Gathercole, Pickering, Knight & Stegmann, 2004). Children who are neurodiverse or have learning disabilities may be even more susceptible and unable to recognise, communicate or regulate their understandings, feelings or emotions (Honeybourne, 2018). Therefore, we as educators play a vital role in creating supportive environments with clear structures, manageable tasks, and reduced distractions to prevent overload and promote healthy development.
Cognitive Load
Cognitive load theory (CLT), developed by John Sweller (1988), proposes that instructional design should consider these limitations to optimise learning. Cognitive load refers to the total amount of mental effort required to process information. CLT identifies three main types of cognitive load:
Intrinsic Load: This load is inherent in the complexity of the learning material itself. Some subjects, like advanced mathematics, are inherently more demanding on working memory than others (Sweller, 1988; Paas, Renkl & Sweller, 2003).
Extraneous Load: This load arises from factors unrelated to the essential content, such as poorly designed instruction, confusing visuals, or background noise. Extraneous load competes for valuable working memory space, hindering learning (Sweller, 1988; Mayer, 2005).
Germane Load: This load represents the cognitive effort invested in actively building schemas, or mental frameworks, for understanding new information. This is the desirable load, as it facilitates the transfer of knowledge into long-term memory (Sweller, 1988; Leppink, Paas, Van Gog, Van Der Vleuten & Van Merriënboer, 2014).
For most of us, our short term memory can only focus on seven plus or minus two pieces of information at any given time (Cowan, 2001). Generally, for the developing brain this is even lower.
Implications of Cognitive Overload
Now imagine a student trying to juggle too many balls at once. Each ball represents a piece of information they need to process, understand, and potentially remember. Working memory, the brain's temporary storage space for conscious thought, acts like the student's hands. When the teacher throws too many balls (information) at once, the student's working memory becomes overloaded. They struggle to keep track of everything, some balls (information) get dropped (forgotten), and it becomes impossible to effectively juggle (learn). This is cognitive overload in action.
Cognitive overload isn't just about dropping the occasional piece of information. When the total cognitive load consistently exceeds working memory capacity, a cascade of negative consequences unfolds (Baddeley, 2000). Students grapple with processing new information, they might miss key points entirely or misunderstand instructions (Van Merrienboer, Schuurman, de Croock & Paas, 2002). Making connections between new and existing knowledge becomes a herculean task. Retention suffers as well, with information failing to solidify in long-term memory. The frustration of not being able to grasp the material can lead to disengagement and a negative association with learning (Pintrich & Zusho, 2002). This can ultimately hinder academic achievement, creating a cycle of struggle and discouragement.
The impact of cognitive overload extends beyond test scores and grades. Negative learning experiences can leave students feeling demoralised and apprehensive about future learning endeavours. Imagine the student who dreads maths because they constantly feel overwhelmed by complex equations and procedures. Cognitive overload can chip away at a student's intrinsic motivation to learn and explore new ideas. By understanding and mitigating cognitive overload, educators can create a learning environment that fosters not just academic success, but also a lifelong love of learning.
Educating for Understanding
By understanding CLT, educators can become architects of instruction that minimises mental clutter. They can achieve this by eliminating unnecessary information and distractions (extraneous load) that compete for valuable working memory space. Instead, they can focus on crafting learning experiences that directly target the essential content (germane load). This might involve breaking down complex topics into manageable chunks, using visuals to enhance understanding, and providing opportunities for active learning and practice. By prioritising germane load, educators can ensure students are devoting their cognitive resources to building strong schemas, not fighting mental overload.
A Multifaceted Approach Fostering Deeper Learning
When educators present demands that exceed this working memory capacity, students experience cognitive overload (Baddeley, 2000). This overload hinders their ability to absorb new information, make connections between ideas, and retain knowledge in the long term. To address this challenge, the following strategies leverage CLT principles. By implementing them, educators can create learning environments that minimise overload and foster deeper understanding.
Chunking for Mastery
A core principle of CLT involves chunking complex information into manageable segments. By breaking down topics into smaller, focused units, educators reduce the cognitive effort required for initial processing. This allows students to devote their working memory to mastering a specific concept before moving on. Targeted practice within each chunk fosters deeper understanding and reduces the likelihood of cognitive overload.
Differentiation and Personalised Learning
Students enter the classroom with varying prior knowledge and learning paces. A one-size-fits-all approach can quickly lead to overload for some students who struggle to grasp concepts, while others might become bored if the pace is too slow. Personalised learning focusing on skill mastery has shown benefits in reducing cognitive overload as it addresses these individual needs through rich and differentiated instruction (Tomlinson, 2001; Pashler, Bain, Ericsson & McDaniel, 2007). Educators can identify areas where students might be experiencing overload and adjust instructional strategies accordingly. This targeted support ensures students grasp a concept before progressing, reducing the overall cognitive load and preventing them from feeling lost or overwhelmed.
Formative Assessment and Feedback
Regular formative assessments throughout the learning process serve as a valuable tool for identifying early signs of cognitive overload (Black & Wiliam, 1998). These checks for understanding allow educators to address student misconceptions before they snowball and contribute to overload. By providing timely and specific feedback, educators can help students adjust their learning strategies and ensure a solid foundation is built without the burden of accumulated confusion. This not only reduces overload but also empowers students to take ownership of their learning.
Spaced Repetition
Spaced repetition, where students revisit information through various activities and assessments at strategic intervals is a critical strategy in the CLT framework (Pashler, Bain, Ericsson & McDaniel, 2007). This spaced practice strengthens neural connections and promotes long-term memory, reducing the need for constant relearning and freeing up working memory space for new concepts (Dempster, 1989). This fosters a sense of accomplishment, confidence and self-efficacy in students as they successfully conquer smaller chunks of information and receive positive reinforcement. This not only reduces anxiety, a known contributor to overload, but also cultivates a growth mindset that fosters a more positive and productive learning experience.
Beyond Core CLT Principles
In addition to the core CLT principles discussed above, educators can employ a range of additional strategies to further optimise learning environments. These include:
Reducing Redundancy: Eliminate unnecessary information and clutter from explicit teacher directed presentations and learning materials to focus on key concepts or what the students need to know, understand and do (Wiggins & McTighe, 2005). This avoids overwhelming students with extraneous details.
Utilising Scaffolding: Provide guided practice and support through worked examples, prompts, or collaborative activities to help students grapple with new concepts and lead them through the inquiry (Desoete, 2004).
Promoting Active Learning: Move beyond passive instruction and encourage student engagement through discussions, rich inquiry, problem-solving tasks, and self-explanation exercises, all of which promote curiosity, deeper understanding and schema building (Darling-Hammond, Flook, Cook-Harvey, Barron & Osher, 2020).. Utilise a variety of instructional methods, such as visual aids, hands-on activities, and verbal explanations, which can reduce the intrinsic cognitive load associated with processing information in a single modality.
Minimising Distractions: Create a calm and organised classroom environment with managed noise levels, limited multitasking opportunities, and clear instructions (Tomlinson, 2014). This includes patterns of predictable behaviours, what the intended learning is and what success at this looks like, and the roles and routines in the classroom that support the learning community.
Metacognitive Strategies: Teach students how to monitor and regulate their cognitive processes. This empowers them to become more aware of their cognitive load and develop strategies to manage it effectively, such as applying thinking routines, defining key vocabulary or using mnemonic devices (Meltzer, 2010).
Ultimately, creating a learning environment that minimises cognitive load is not just about academic achievement. By fostering a sense of accomplishment, self-efficacy, and a growth mindset, educators can cultivate a love of learning that extends far beyond the classroom walls. As students develop metacognitive skills and learn to manage their cognitive load effectively, they become empowered to tackle future learning challenges with confidence and a thirst for knowledge. This sets the stage for them to become lifelong learners, ever curious and eager to explore the vast world of information.
Stay the Course!
References
Baddeley, A. D. (2000). Short-term and working memory. The Oxford handbook of memory, 4, 77-92.
Black, P., & Wiliam, D. (1998). Inside the black box: Raising standards through classroom assessment. Granada Learning.
Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and brain sciences, 24(1), 87-114.
Darling-Hammond, L., Flook, L., Cook-Harvey, C., Barron, B., & Osher, D. (2020). Implications for educational practice of the science of learning and development. Applied developmental science, 24(2), 97-140.
Dempster, F. N. (1989). Spacing effects and their implications for theory and practice. Educational Psychology Review, 1, 309-330.
Desoete, A. (2004). Scaffolding and interactivity in computer-assisted language learning: Towards a research agenda. Language Learning & Technology, 8(3), 36-46.
Diamond, A. (2000). Close interrelation of motor development and cognitive development and of the cerebellum and prefrontal cortex. Child development, 71(1), 44-56.
Gathercole, S. E., Pickering, S. J., Knight, C., & Stegmann, Z. (2004). Working memory skills and educational attainment: Evidence from national curriculum assessments at 7 and 14 years of age. Applied Cognitive Psychology: The Official Journal of the Society for Applied Research in Memory and Cognition, 18(1), 1-16.
Honeybourne, V. (2018). The neurodiverse classroom: A teacher's guide to individual learning needs and how to meet them. Jessica Kingsley Publishers.
Leppink, J., Paas, F., Van Gog, T., Van Der Vleuten, C. P., & Van Merriënboer, J. J. (2014). Effects of pairs of problems and examples on task performance and different types of cognitive load. Learning and Instruction, 30, 32-42.
Mayer, R. E. (2005). Cognitive theory of multimedia learning. The Cambridge handbook of multimedia learning, 31(2), 31-48.
Meltzer, L. (2010). Promoting executive function in the classroom. Guilford Press.
Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational psychologist, 38(1), 1-4.
Pashler, H., Bain, P., Ericsson, K., & McDaniel, M. (2007). Enhancing learning and retention: Spaced repetition and the power of feedback. Educational Psychologist, 42(1), 1-9.
Pintrich, P. R., & Zusho, A. (2002). The development of academic self-regulation: The role of cognitive and motivational factors. In Development of achievement motivation (pp. 249-284). Academic Press.
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive science, 12(2), 257-285.
Sweller, J. (2011). Cognitive load theory. Psychology of learning and motivation, 55, 37-76.
Tomlinson, C. A. (2001). How to differentiate instruction in mixed-ability classrooms. Alexandria, VA: ASCD.
Tomlinson, C. A. (2014). The differentiated classroom: Responding to the needs of all learners. Ascd.
Van Merrienboer, J. J., Schuurman, J. G., de Croock, M. B., & Paas, F. G. W. C. (2002). Redirecting learners' attention during training: Effects on cognitive load, transfer test performance and training efficiency. Learning and instruction, 12(1), 11-37.
van der Vleuten, C. P., & Driessen, E. W. (2014). What would happen to education if we take education evidence seriously?. Perspectives on medical education, 3, 222-232.
Wiggins, G. P., & McTighe, J. (2005). Understanding by design. ASCD.
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