Cognitive Load Theory and its Applications for Learning - Scott H Young

Over the past few decades, cognitive load theory has amassed a lot of interesting experimental effects with catchy-sounding names. Here are a few:

Traditionally, math education has focused on having students solve problems to get good at math. Sweller and Cooper pushed back against this idea, showing that studying worked examples (problems, along with detailed solutions) is often more efficient.

Worked examples have since been shown to be powerful tools in many domains. The rationale is that problem solving is a cognitively demanding activity. This creates a lot of extraneous load, making it harder to abstract what the general solution procedure involves.

Cognitive load isn’t just found in problem solving. Badly designed instructional materials can increase cognitive load by requiring learners to move their attention around to understand them.

Consider these two flashcards for learning Chinese characters. The first creates extra cognitive load since the pairing between sound and character requires more spatial manipulation. Learning is enhanced when instructional materials are organized so that information doesn’t require any manipulation to be understood.

Cognitive load theory’s principal applications are in instructional design. How should a subject be taught so that students will efficiently master the patterns of knowledge it contains? Cognitive load theory favors direct instruction, quick feedback and plenty of practice.

Here are a few suggestions:

In my experience, the Feynman Technique mainly works by slowing things down. A concept can be confusing in a lecture because critical assumptions aren’t made explicit or intervening steps are skipped. Walking through the explanation yourself lets you figure out exactly where you get lost.

Math and science tend to have high element interactivity, which is why mastery of them is seen as a sign of intelligence. Working memory is associated with intelligence, and those with slightly more working memory can handle slightly greater element interactivity. While this creates only a modest advantage in the short term, greater ease in learning basic concepts can accumulate into a considerable advantage in the long run .

If you’re struggling in a subject with high element interactivity, the key is to go back and invest in more practice in the underlying skills.