Insights from the Science of Learning

Educators have forever been preoccupied with that most fundamental of questions: what is learning? And this question triggers a whole universe of ensuing questions – Why do some people learn more effectively than others? How does memory work?  Why are some things easier to learn than others?  What is the role of emotion in learning? The role of stress? The role of motivation? Etc. Etc.

In recent years there have been impressive advancements in the field of neuro-science – the study of the human nervous system with a special focus on the brain, its functions, and its relationship to learning and thinking and  behaviour. These advancements, concerned as they are with many of the questions named above, are obviously relevant to our work to a degree, but it’s important to remember that we are obviously not neuroscientists. The pace of scientific analysis and discovery about unfathomably complex things is slow, deliberate, hesitant, careful. And we hook in with great interest to those developments while, at the same time, having to do the immediate work of supporting students now, today, in their approach to learning. Complicating matters is the way in which many of these complex, preliminary, contingent findings emerging in the field of neuroscience get diluted and fed back to us in oversimplified and often questionable packages of pop-psychology. Educators are especially prone to this faddishness, eager as we are to find new, effective ways to teach. The punchline here is that these are extremely complicated waters. Education is not a scientific discipline, effective learning strategy work is not a thing to be reduced to scientific findings alone. Ours is a humanistic occupation, rooted in interpretation and subjectivity. This is never to say that we cannot also be rooted in the relevant objective findings of science, just that our work is not a discipline based in science, but rather, merely informed by it. So, while being eager to learn from the emerging findings from neuroscience and psychology, we should be wary of premature enthusiasm for and adoption of practices that are not yet borne out by sufficient evidence or are just plain dubious, and we should not imagine a “science of learning” that is straightforward to put into practice.

With those important caveats in mind, we can take a more responsible approach. One narrow slice of the broader “science of learning” field is that which focuses on study/learning practices. These are cognitive practices shown to be especially effective for certain kinds of performance-based learning typical of higher education. This is obviously relevant to our work, so something Learning Strategists should have in their quiver. Following are brief descriptions of some of the more common of these.

Retrieval practice:

This strategy is founded on the principle that retrieving knowledge from memory results in strengthened ability to do so and reinforces an idea about testing as not only a device for evaluation but also a method to strengthen memory.  It is in the act of calling forth information that we have stored away that we can improve our memory, even in the absence of feedback. It is the act of retrieval itself that is beneficial. The evidence for this comes from simple, replicable experiments in which participants who used retrieval practices are shown to demonstrably score higher on recall tests than those in the control groups not using retrieval practices.  This positive effect on memory has obvious benefits for fact-based or rote learning. Schooling once involved a great deal of memorization – indeed it was an expectation of students to memorize long poems, or passages from literature. And, prior to the now ubiquitous digital technologies, memorization was quite simply a feature of everyday living. This is becoming less and less true and one wonders whether the downloading of this function onto machines will have an effect on our memory capacities. Regardless, it is worth keeping alive the practice of information retrieval as a learning strategy – practices like making flashcards and doing practice tests.

Spaced Practice:

The operative principle with spaced practice is that X amount of repeated study that is distributed over time results in greater retention of information than that same X amount of repeated study done in a single session. Imagine having five hours to study something. The principle of spaced practice dictates that five separate 1-hour sessions with long breaks in between are much more effective than one 5-hour session. This likely has something to do with the inverse relationship between so-called retrieval strength and storage strength of memory. When retrieval strength is high (say, in cramming sessions), the storage strength is low. When retrieval strength is low (say when studying is spaced out over long intervals), the storage strength is high. In this insight is also the challenge for students who tend to prefer the immediate benefits of retrieval strength (cramming) over storage strength (retention). Spaced practice is a difficult thing to incorporate since it entails a commitment to the non-intuitive idea of, and the ability to plan a more complicated study schedule. But the evidence for this more positive effect on retention is very strong, replicated in classroom experiments over many decades, so sharing these findings with students can help convince them of the value.

Interleaving:

This is another technique that students regard as difficult, non-intuitive and that requires more complicated scheduling. The principle of interleaving is that occupying a study session with alternating types of problems, or skill acquisition is more effective than repeating the same type of problem or focusing on a single skill before moving to the next. Again, this flies in the face of what comes as intuitive to students who prefer to engage in repetition, applying their energy to the same kind of object over and over, and then moving onto the next kind. The concept of interleaving, with important caveats, is shown to be especially effective in certain domains such as the development of motor skills, and in certain essential math skills. Over-exuberant application of this concept has led to the advice that students even alternate subject matter in their study sessions. Rather than studying subject A exclusively before moving to subject B, then C,  (ie. AAABBBCCC…) the advice is to “interleave” the subjects and pattern the time in a mixed way (ie. ABCABCABC).  Evidence for the positive effect of this specific application of the method remains scant, and it remains true that the principle of achieving some sort of subject mastery baseline prior to moving on to other skills is still beneficial. However, the evidence is strong that judicious mixing of study focus is an effective technique.

Elaboration:

A simple definition of what we mean here by “elaboration” as a learning strategy comes from Hirschman who says elaboration is “…a conscious, intentional process that associates to-be-remembered information with other information in memory.”  In other words, techniques of elaboration are ways to deepen or enhance our memory by connecting what we already know to what we aspire to know. This, of course, can lead to varied interpretations of what exactly a technique of elaboration might involve, many of which are difficult to actually isolate and measure – vague strategies like applying a “deep” approach to engaging with subject matter or “integrating” the unknown subjects with preexisting cognitive frameworks. This kind of language and description does little to help guide students in actual concrete strategies. More fruitful is the suggested technique of engaging with new subject matter by asking questions about it and then, through a process of simply trying to answer those questions as one studies the material, one deepens their understanding and their ability to recall that information.

Dual Coding:

Emerging primarily out of the cognitive load theories of learning, the idea of dual coding is rooted in the idea that the brain processes information through multiple pathways, primary among them being visual pathways and auditory or verbal pathways. Given that processing reality, it follows that we are able to more effectively learn new subject matter when we engage both these pathways. In other words, we will be more likely to learn and remember something if we devise ways to engage with it both visually with imagery and verbally with words. Guiding students in the use of this strategy involves simply helping them first understand this feature of cognitive processing so they are motivated to use it, and then suggest ways in which this can be enacted – the creation of mind-maps, diagrams, timelines, doodles, that link words with associated images. As with other cognitive strategies, there is a limit here to be cautious of – too much over-stimulation of neural processing pathways can also add to cognitive load, which can diminish learning capacity.

Concrete Examples:

A final strategy to highlight here is the use of concrete examples applied to new, especially abstract subject matter. It is well known that the brain can process concrete information more effectively than abstract information, so the addition of supplementary detail to any abstract concept or idea will support the learning process. The process of identifying concrete examples to help illustrate a more complex idea is simply another form of active learning that results in enhanced understanding and recall. This strategy is most often applied as a technique for instructors in their teaching, but it can be adapted for students in their study. One point to be aware of here, again emerging from cognitive load theories, is that the concrete examples being applied are best when they are as relevant as possible to the actual content, and not merely gimmicky memory-triggers. The latter may help in simple recall but do little to deepen one’s understanding of the subject matter.

It is important to add here that the strategic function of our work is to help students be better at discerning which approaches, which tactics are best according to the context. Some of these tactics work well for, say, quantitative subject matter in the STEM disciplines, but not so much in the humanities where different approaches are needed. And vise versa. Learning Strategists help students make good choices about which tactics apply when they are studying.