ELearning/Foundations/Efficiency in learning
You have probably heard about the capacity of working memory as 7 ± 2 (7 plus or minus 2) bits of information. According to this guideline, our cognitive system can only process 7 ± 2 items at a time. Once this capacity is exceeded, our thinking bogs down – we lose track, we forget, we become overwhelmed, we get distracted.
The thinking behind this guideline has evolved into cognitive load theory, a set of learning principles that leverage human cognitive processes that, when used, have proven to result in efficient instruction and faster learning, better learning or both. Simply put, the use of cognitive load principles makes instruction and learning more efficient and more effective.
Cognitive load theory applies to every learning context, from technical content to soft skills, as well as all delivery platforms from classroom to e-learning.
Forms of cognitive load
The three primary forms of cognitive load we need to consider are intrinsic load, germane load and extraneous load (Clark, Nguyen & Sweller, 2006).
Intrinsic Load
The mental work imposed by the complexity of the content itself. Complexity is determined by the number and variety of mental and physical elements contained in the instruction. For example, entering a formula in an Excel spreadsheet contains visual and spatial elements (locating the correct cell for the formula and the cells to be used in the formula) as well as knowledge and formatting elements (to correctly enter the formula). Whether elements must be applied in sequence or in total determines element interactivity, with more interactivity resulting in more complexity. Applying the Excel formula is largely sequential; thus element interactivity is fairly low. Giving a speech, on the other hand, involves many activities at once. Speaking coherently and logically, using gestures, looking at, gauging and adjusting to our audience must all be carried out in smooth coordination in order to be successful. Thus there is a high degree of element interactivity to giving a speech. Although we can’t appreciably change the complexity of the instructional objective, we can manage intrinsic load by breaking complex tasks into a series of prerequisite tasks and supporting knowledge distributed over a series of lessons. In learning public speaking, we can practice speaking first, adding gestures next and looking at and gauging your audience later once the prerequisite skills have been attained.
Germane (relevant) Load
The mental work imposed by instructional activities that contribute to the accomplishment of the learning goal. Speeches come in many different forms, depending on the subject and audience. Humorous speeches for the local club are constructed differently than speeches introducing a new technology to a group of programmers. Thus, learning speechmaking involves learning about and practicing different sorts of speeches for different audiences. Skills that emerge from a homogenous set of examples are inherently more limited than those that emerge through the use of a diverse set of examples. Think of germane load as relevant load that leads to better learning.
Extraneous (irrelevant) Load
Mental work that is irrelevant to the learning goal and is thus a waste of time and mental resources. Worse, extraneous load actually degrades learning by interfering with intrinsic and germane cognition. Lessons containing the same message in verbal and written forms compete for our attention and waste mental resources. Split attention caused by spatially separating explanatory text from a related graphic is another example.
It’s Relative
Besides understanding the different sorts of cognitive load, it is also important to understand its relativity. Individual cognitive load depends on the interaction of three components: the learning goal and its associated content, the learner’s prior knowledge, and the instructional environment. For starters, eliminating extraneous load for learning complex tasks is much more important than for learning simple ones. It makes common sense and research bears this out. But what is complexity? Complexity is relative to individual knowledge and skill. What is simple for an expert may be incredibly complex for a novice. So we need to modify our initial guideline to say that eliminating extraneous load for learning complex tasks by novices is much more important than for experts or simple tasks. In fact, many of the techniques for minimizing extraneous load for novices actually impede learning for the more experienced. You need to change your instructional strategies as your learners develop expertise during your course or their course of study.
Building mental models
Learning is possible because of memory. Without it, we’re doomed to a life of repetitive instinctual behaviors without the benefit of experience. It’s useful and accurate to think of memory as consisting of two systems – working memory and long-term memory. Memory is part-and-parcel of our learning networks, discussed earlier. Additionally, memory is distributed throughout the brain in the form of circuits – schema as we saw earlier. Individual neurons (brain cells) or groups of neurons may be members of thousands of memory circuits. This memory interconnectedness helps explain the usefulness of tapping preexisting knowledge for new learning and building expertise.
Working memory is the active partner - consciously processing new information and creating schemas that are then stored in long-term memory. Schemas are very important for learning complex knowledge and skills. They are the brain’s way of simplifying complexity. Schemas are memory structures, or circuits, stored as long-term memory, that permit us to treat a large number of information pieces as though they were a single element. Consider all the separate tasks of driving. There must be hundreds. Now think of how difficult it would be to drive if you had to consciously work your way through each task. Novice drivers know how difficult it can be. The very essence of expertise, schemas are built of experience and learning added to again and again, strengthening with each use until they become automatic or nearly so.
In turn, the capacity of working memory is increased by using the schema stored in long-term memory. Instead of processing the hundred or so individual elements of driving, it consciously processes the single element of “driving on the highway” or “driving in a school zone”. If memory is essential to learning, then experience is essential to memory. Experience is mediated through the senses. What we hear, see, touch, do, manipulate, taste, smell and feel are all involved in learning to differing degrees. The visual and auditory senses are dominant in most formal learning settings, certainly online learning, but the other senses are vital to a multitude of skills. The important point here is that when groups of cells in different areas of the brain are excited simultaneously, the memory circuit – the schema - is strengthened. "Neurons that fire together, wire together." This is the primary reason why multiple media working together – not in opposition – generally create better learning than any single media alone.
See learning theories for more on mental models.
Accommodating differences in learner expertise
Teaching strategies for novices seek to simplify and chunk content, optimize cognitive load and otherwise accommodate the learner:
- Using visuals and audio narration to exploit working memory resources.
- Focusing attention and avoiding split attention.
- Providing less instruction instead of more, concentrating on the essentials.
- Providing external memory support to reduce working memory load.
- Using segmenting, sequencing and learner pacing to impose content gradually.
- Transitioning from worked examples to practice.
In essence, these methods serve as substitutes for schema to compensate for their absence in novice learners. As learners gain expertise, teaching strategies need to change in order to account for their increasingly sophisticated schema. Many instructional methods that are effective for novice learners either have no effect or, in some cases, actually depress learning for those with more expertise. This is so due to a phenomenon called the expertise reversal effect – occurring because the advanced learner must divert mental resources to resolving conflicts between their refined schema and the incoming simplified, chunked information meant for novices.
Specific guidelines for managing cognitive load are included in the Managing cognitive load article in the Course development module.
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