Our story begins in the 1980s with an Australian educational psychologist named John Sweller. While observing how people solved problems, he noticed something rather important: our working memory – that part of our brain responsible for holding and processing new information – has a rather limited capacity (Sweller, 1988). This wasn't entirely a new thought; George A. Miller had famously posited in the 1950s that our working memory could only juggle about seven, plus or minus two, "chunks" of information at a time (Miller, 1956).
Sweller and his colleagues took this foundational idea and applied it directly to instruction, aiming to design learning materials that respect these cognitive limitations. The goal? To ensure that information can smoothly transition from our fleeting working memory into the vast, more permanent storage of our long-term memory (Clark et al., 2012).
In essence, CLT seeks to help us design learning that makes the most of our brain's processing power without overwhelming it.
To truly grasp CLT, it helps to understand the three main types of "load" that influence our mental processing:
In essence, effective instruction manages the intrinsic load, ruthlessly eliminates the extraneous load, and actively encourages the germane load (Clark et al., 2012).
So, how do we, the benevolent architects of digital education, apply these insights to create e-learning that genuinely fosters understanding rather than frustration?
This principle is all about chunking information for better digestion. Don't present large amounts of information all at once. Break down content into smaller, manageable chunks that learners can process incrementally (Clark et al., 2012). This prevents overwhelming working memory and allows learners to consolidate understanding before moving on.
How to put it into practice:
Structure your course into distinct modules, lessons, and topics, clearly signposting the scope of each section. Keep the smallest unit in your architecture (e.g. a topic) as short as five minutes if you can.
Segmentation is especially important for video, as learners are prone to “zoning out” on these! Instead of confronting learners with a 30-minute lecture video, break it into about five-minute segments, each focusing on a single key concept.
On a single page, use interactive elements like "click to reveal" or accordion components to present information in stages, rather than overwhelming the learner with all text visible at once. Let them get the big picture, then “ask” for more detail when they're ready.
When possible, present information through both visual (e.g., text, diagrams) and auditory (e.g., narration) channels (Clark et al., 2012). This leverages different processing pathways in working memory, effectively expanding its capacity. It’s also better practice for accessibility and inclusivity.
How to put it into practice:
Instead of simply displaying text on screen, provide a relevant graphic or animation with accompanying narration. The narration explains the graphic, reducing the need for learners to read text while simultaneously trying to interpret a visual.
I’m personally a big fan of carefully planned and signposted repetition in different modes. For example, if a learner just watched a five-minute video about a concept, offer them a “recap” afterwards in a different format like an infographic or a set of flashcards with key questions and answers. This way, the content will “stick” better and the learner will also be alerted if they didn’t pay attention to the whole video.
Some scholars argue that this creates redundancy and forces learners to choose between listening and reading, which can increase extraneous load (Kalyuga et al., 1999). I like to use on-screen text sparingly to highlight key terms or labels, then allow the voiceover to expand. These short text highlights should ideally match the relevant snippet of the voiceover because it does get difficult to keep up otherwise; just don’t put all the voiceover text on the screen and ensure you time things well. Of course, in this case you should also provide a transcript and closed captions for learners with differing abilities.
When teaching problem-solving skills, start with fully worked examples that demonstrate each step of the solution (Renkl & Atkinson, 2003). As learners gain proficiency, gradually "fade" out parts of the solution, requiring them to complete the missing steps, before moving to independent problem-solving.
How to put it into practice:
For a maths problem, show the problem and then each step of the solution, clearly explaining the reasoning behind each step.
In programming tutorials, provide complete, functional code examples alongside explanations, then later provide partially complete code for learners to finish.
Allow learners to observe a process or solution unfold in a simulation before asking them to manipulate variables themselves.
Avoid presenting information that is unnecessarily redundant (Kalyuga et al., 1999). If a concept can be understood without additional, overlapping information, remove the superfluous content. Extra, non-essential information adds to extraneous load.
How to put it into practice:
Write clear, concise content. Avoid wordiness, jargon, or overly complex sentences when simpler language will suffice.
Ensure every image, diagram, or animation serves a clear learning purpose. If a visual doesn't enhance understanding, remove it.
As mentioned with the Modality Principle, avoid having identical text on screen that is also being narrated. Choose one primary channel for that specific piece of information.
Now, I know what you’re shouting at the screen. “But you JUST SAID I should also repeat stuff intentionally! In this same article, you did!” And, you’re right. My views are a bit controversial in that sense.
If you’re up to the challenge, I think the trick is to use redundancy very intentionally and sparingly, with skill and nuance.
Don’t repeat everything! Just the five key takeaways of the unit or lesson, and ideally in a different mode to how the information was presented the first time. Maybe even as a job aid that is easy to access later. It really helps learners focus on what to do when they leave the safe space of the learning zone and go back to work.
Eliminate all irrelevant words, pictures, and sounds from your e-learning materials (Clark et al., 2012). Anything that doesn't directly contribute to the learning objective creates extraneous cognitive load and distracts the learner.
How to put it into practice:
Review your content and ask: "Is this absolutely essential for achieving the learning objective?" If not, consider cutting it. This applies to anecdotes, decorative graphics, and tangential information.
Opt for clean, uncluttered layouts. Avoid busy backgrounds, overly complex fonts, or excessive visual effects that don't add to understanding. But, at the same time, keep in mind that today’s audiences also like a bit of expression in their designs, and adore moments of delight. It’s a balance you have to strike between being boring and impersonal and turning your learning experience into an obstacle course.
Use background music or sound effects sparingly, and only if they serve a specific purpose (e.g., to create a mood for a scenario or introduction, but not during core instruction).
By thoughtfully applying these principles, we can design e-learning experiences that truly empower learners, making the process more efficient, more engaging, and ultimately, more successful.
Before launching your next e-learning module, give it a quick review using this checklist. Tick "yes" if you've addressed the principle, "no" if you need to revisit it. You can download a version of this checklist here.
Content and structure
Presentation and media
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Chandler, P., & Sweller, J. (1994). Cognitive load theory and the format of instruction. Cognition and Instruction, 8(4), 293–332.
Clark, R. C., Nguyen, F., & Sweller, J. (2012). Efficiency in learning: Evidence-based guidelines to manage cognitive load (2nd ed.). Pfeiffer.
Kalyuga, S., Chandler, P., & Sweller, J. (1999). Managing split-attention and redundancy in multimedia instruction. Applied Cognitive Psychology, 13(4), 351–371.
Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81–97.
Renkl, A., & Atkinson, R. K. (2003). Learning from worked examples and problem solving. In J. Sweller, R. E. Clark, & K. Koedinger (Eds.), Instructional interventions for human-computer interaction (pp. 31–43). Lawrence Erlbaum Associates.
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285.
Sweller, J., van Merriënboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive Architecture and Instructional Design. Educational Psychology Review, 10(3), 251–296.
van Merriënboer, J. J. G., & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17(2), 147–177.
