Nuts and Bolts: Brain Bandwidth – Cognitive Load Theory and Instructional Design

In Maywe looked at some of Richard Mayer’s research-based principles oflearning and training design. Another area of current thought inlearning and brain science – closely linked to ideas around thosediscussed in May — relates to Cognitive Load theory. Prominentnames here are John Sweller, Frank Nguyen, and Ruth Clark; I’veincluded a reading list below.

The basics of the theory aren’t hard:it pretty much posits that there’s only so much new information thebrain can process at one time. Why should we care? Because so oftendesigners and trainers simply overload learners, hurting learning andlearner motivation, and thereby undercutting the very thing we say wewant to accomplish. Understanding cognitive load theory depends on anunderstanding of memory; in particular, the concepts of workingmemory and long-term memory.

Working memory isn’t to be confusedwith the idea of short-term memory, which is remembering somethingfor a little while. It’s more about the amount of information thebrain can hold and manipulate at once – what we can manage at agiven point in time. Research data disagrees on the specifics, likethe exact limit, issues with processing numbers and words at once,and indications that working memory capability improves withpractice. But it’s easy enough to see the basic idea for yourself.

For instance, work this problem in yourhead:

Now, try this one in your head:

In the second instance, the “problem”is the same as the first. The processing is the same. The same skillsare used. But for most of us, the second sum just asks for more thanthe brain can handle; we can’t hold and manipulate that muchinformation at once. And my guess is that most of you didn’t evenattempt to work the second problem: if you’re like me, the verysight of it destroyed your motivation to try and solve it. [Are you amath geek with lots of tricks up your sleeve? You’ve alreadyfigured out how to reduce your own cognitive load, and the secondproblem was no problem for you. OK, then, imagine a typical “wallof words” e-Learning screen and the effect it might have onlearners and learning. That’s how the long math problem looks tothem. More for you in the “novice and expert” section below.]

Long-term memory, on the other hand, isrelated to time — how long something stays with us and can becalled upon. It’s presumably limitless, but it is also a funny,seemingly capricious thing. One of my favorite quotes is fromAmerican writer Austin O’Malley, who said, “Memory is a crazy oldwoman who hoards colored rags and throws away food.” It speaks towhy we can remember a particular dress our first-grade teacher wore,but we can’t recall what we had for lunch last Tuesday.

So the trick for trainers andinstructional designers: providing instruction in such a way thatlearning in working memory can be moved to long-term memory where itwill, we hope, be called upon as needed, possibly in anot-very-conscious way.

Some solutions?

Assuming other things are equal (butthey never are) like learner attention, learning environment, andinterruptions, there are a number of things designers and trainerscan do to reduce cognitive load in their courses.

Chunk the content

Pay attention to how much informationthe learner is accessing at any one time. Consider the “ruleof 7.” George Miller, an early researcher in cognitive load theory,suggested that the largest number of discrete pieces of informationthe brain could mange was seven, plus or minus 2. Think about thingslike phone numbers (in the U.S.: 123-456-7890; that is, groups of 3 +3+ 4 numbers), U.S. Social Security numbers (123-45-6789; that is,groups of 3+2+4 numbers), and worldwide postal codes.

Be aware that “chunking,” though,isn’t just relative to breaking content apart in some scattershotway: the chunks need to represent something meaningful. In moreacademic terms, we intend chunking to help the learner build and addto the schema, or framework for organizing and making sense of theinformation.

Also, employ simple visual designbasics: Use white space and fonts as organizing tools, and make useof meaningful (not decorative) images that teach.

Use modules

This is, essentially, another form ofchunking, and it is usually easier for those creating asynchronouse Learning to justify to stakeholders. Those working intraditional or virtual classrooms often see training events madelonger in order to have learners travel to a training site only once,in order to minimize instances of pulling essential staff from thework site, and in order to maximize opportunities to virtuallyaccommodate time-zone issues. The danger of that should be apparentby now: Cognitive overload. When possible, use modules rather thanpack everything into a one-shot show.

Consider Novice and Expert

So often training and e-Learning aredesigned as one-size-fits- all endeavors. This may make sense interms of economics and in getting something developed and launchedquickly, but ultimately can hurt the learning experience. What isadequate for the expert may overload the novice, while what iscomfortable for the novice may bore the expert. In the arithmeticexample above, the “math geek” type likely has learned tricks orhas practiced this sort of thing enough to manage the cognitive loadit presents. Me? I can barely do the 2 X 2 addition in my head.Consider developing different programs for different levels oflearners, or at least branching tracks or modules leading fromcritical content to different levels of practice based on expertise.Clark, Nguyen & Sweller (2006) suggest providing novices withworked examples and experts with problems to solve, gradually fadingthe worked examples as novices move toward expertise.

Remove extraneous material, including that which is there only for “interest” or decoration

In my workshop on this I askparticipants to think of the brain as having only so much“bandwidth”; information enters the brain through two channels,visual and auditory. The channels can carry only so much data at atime. (Add to this additional but less formally recognized “channels”that sometimes come into play during learning: touch, as with amachine assembly task, and sometimes smell, as with cookinglessons.) Removing extraneous material is hard to do, especially asevery stakeholder will have ideas about what is “extraneous.” Formore on that, visit my earlier column on finding your critical 20% ofcontent(https://www.learningsolutionsmag.com/articles/472/nuts-and-bolts-find-your-20).

Once you’ve culled out the criticalcontent, look at the design itself. Is it a pretty but irrelevanttemplate, with ¼ of the space taken up by irrelevant elements? Losethe template. Are there pretty, irrelevant, and unhelpful clip art,photos, screen/slide transitions, and sounds? Lose them. They don’tengage anybody, and furthermore they confuse people trying to makesense of why the items are there. I am thinking of a screen I oncesaw: a cartoon of an ant lifting a barbell illustrated the idea ofemployee loyalty and it was accompanied by a “wind chime” soundwith every screen change … the learner didn’t have a chance.

You can’t control how intrinsicallyhard the task is. You have little control over learner motivation andeffort to learn it, but you have complete control overextraneous information.

Bottom line?

I’ve observed with past columnsciting research and data that some people bristle at ideas differingfrom their own. While I certainly believe in the role of intuitionand gut feeling in good design, I also think we need to pay attentionto what the data show as working or, especially, harming learning.

Think of it this way: The questionshouldn’t be, “How can I teach this?” but “How can they learnit?”

This Was Intended to Be An Overview. Want more?

Clark, R. , Nguyen, F., & Sweller, J. (2006). Efficiency inLearning: Evidence-Based Guidelines to Manage Cognitive Load. SanFrancisco: Preiffer.

Clark, R. & Mayer, R. (2007). Elearning and the Science ofInstruction: San Francisco: Pfeiffer.

Moreno, R., &Mayer, R. (1999). “Cognitive principles of multimedia learning:The role of modality and contiguity.”Journalof Educational Psychology91:358–368. doi:10.1037/0022-0663.91.2.358. 

Miller, G.A.(1956). “Themagic number seven plus or minus two: some limits on our capacity toprocess information.”PsychologicalReview63(2): 81–97. doi:10.1037/h0043158.PMID 13310704.

Sweller, J.(1988). “Cognitive load during problem solving: Effects onlearning.”CognitiveScience12(2): 257–285. doi:10.1016/0364-0213(88)90023-7. 

Sweller, J., VanMerriënboer, J., & Paas, F. (1998). “Cognitive architectureand instructional design.” EducationalPsychology Review10:251–296. doi:10.1023/A:1022193728205.