In a previous post, we gave an overview of the three main principles required for any effective adult learning experience:

  1. understanding the learner’s context (past, present and future);
  2. establishing and responding to the learner’s existing level of knowledge; and
  3. providing adequate and appropriate practice over time.

This post looks at the first of these principles in more depth.

Here’s a question …

When is a “learner” not a learner?

OK, trick question. But the point is that so-called “learners” are, of course, people first and foremost. Just because they are currently sitting in a particular class or using a particular app doesn’t mean that all the other things going on in their brain, body and life in general are irrelevant or forgettable. And this wider learning context can significantly influence their learning success.

For a learning designer, then, understanding a person’s micro and macro learning contexts is the first critical step in designing something that will work well for them individually.

Are you paying attention?

At the individual level, common conceptions of learning often start with the role of the brain, and especially memory. When planning and monitoring the effectiveness of any learning experience, we may well wonder: what actually happens (or doesn’t happen) inside the learner’s head?

The world is full of stimuli which we somehow need to selectively filter and pay conscious attention to. And while there are many theories about how information moves from working memory to long-term memory, there’s still no widespread agreement among researchers on the exact processes involved.

What we do know is that by filtering, attending and connecting the stimuli we encounter, we reinforce and consolidate networks of knowledge in our long-term memory. These networks are known as “mental models” or “schemata”, and they ultimately guide our perception, our decisions and our actions.

This means that, in order to build up solid mental models, we need to focus and control our attention somehow while learning.

The challenge is that, unlike long-term memory, the capacity of working memory is limited. The brain can only process so much information at a time, and if we exceed the capacity of these attentional resources, we also run the risk of an unmanageable cognitive load, and this will negatively affect our learning.

So, what determines cognitive load?

Essentially, more than five “interactive elements” will probably be too many. As defined by Chen et al (2018), these are “elements that must be processed simultaneously in working memory as they are logically related”.

Both the material and the learners themselves can influence cognitive load. Depending on how much someone already knows about what they’re studying, the content might be too unfamiliar or complex, requiring lots of new things to be processed at the same time and overloading their working memory.

But equally, even for a learner with a good level of existing knowledge about the subject at hand, the content might be presented in such a way that it feels more unfamiliar or complex, or in a way that makes it very difficult for the learner to figure out what to focus on.

For example, learning material nowadays often includes “seductive details”—in other words, details or information that are attention-grabbing but irrelevant to the task at hand. These might make a textbook look more appealing, like a magazine, or seem “fun” to someone who just glances at an app without seriously trying to learn from it; but such details take up valuable attentional resources. And this is especially true for learners who don’t already have enough existing knowledge of the subject to help them work out easily which details of the material are relevant and which are irrelevant.

Related to this: multitasking is a myth. For conscious learning, a single focus of attention is very important. In those instances where we feel that we do manage to split our attention effectively, this is probably because one of the things we’re focusing on is already well-known and/or automatic. But we are often inaccurate in our judgments of how many things we can focus on simultaneously.

This point has been made very dramatically by road safety campaigns:

Of course, the consequences of split attention during a learning experience are probably not quite so dangerous as split attention while driving! But the underlying mental processes are the same, so it’s important for learning designers working with digital tools and content to remember: we should be careful with the use of technology and not allow any feature, game or interaction to be so distracting that it obscures the learning content.

Why bother?

While it’s undoubtedly helpful and satisfying to start with some inherent aptitude for a subject, this alone isn’t enough to guarantee success in a learning experience.

Psychologists will confirm that people need a sense of purpose in life, a feeling that what they are doing is worthwhile—and this is also true at the level of an individual learning experience. Indeed, motivation is such a powerful influence on learning that some researchers in the field of Second Language Acquisition (SLA), for example, argue that motivation is the most important factor for success, more important even than pre-existing ability.

People need to see the value in what they’re learning, and intrinsic motivation—that is, an inherent interest/enjoyment in the subject—is generally a better incentive than extrinsic motivators such as rewards, punishments, external coercion, career reasons, etc.

This suggests that learners whose task is extrinsically motivated would do well to somehow internalise and integrate this need—in other words, they’ll benefit from seeing their goal as more intrinsically motivated, in line with their other values and needs. And if they are feeling particularly negative about the experience—bored, uninterested, frustrated, etc.—they can make it more appealing and manageable through the use of emotional self-regulation strategies such as “cognitive reappraisal”.

For example, imagine someone whose company requires them to attend a training course. They may not be wild about this idea—perhaps they are already too busy at work or don’t believe the new skills they’re learning will actually help their daily efficiency. By recasting it as “an opportunity to improve my memory” or relating the new skills to their future promotional/employability prospects, they can improve their performance without any significant cognitive cost.

Similarly, motivation and success in learning are also influenced by how “self-determined” a person is. This means that learners need:

Keep going … you’ve got this!

Of course, learning is not always easy and learners will inevitably face difficulties and challenges along the way. There has been a lot of research focusing on conscientiousness, “hardiness” or “grit”, and some learners may well be sustained through challenges by these personal qualities.

But interestingly, the key factor in all these cases is actually perseverance of effort. Much has been written about “grit”, for example, which is essentially made up of two things: perseverance in the face of obstacles and consistent application to learning something (rather than frequently changing interests). Reviewing the research overall suggests that the first element is the truly critical one

In short, successful learners will be those who keep going—those who feel driven to finish what they’ve started, even when it’s hard. It’s important not to give up at these moments. Even when we are genuinely interested in learning something, there will be some tough moments when we won’t feel especially enthusiastic. But if we persevere, if we continue making an effort even at those times when our interest is waning, if we take a deep breath and then keep working away nevertheless, it is this perseverance that will help us ultimately succeed.

All in the mind?

So far, we’ve mainly considered what goes on within an individual learner. But it would be a big mistake to forget that:

“Brains are in bodies, bodies are in the world, and meaningful action in these worlds is in large part socially constructed and conducted.”

In other words, like so much of human experience, learning is significantly socially and culturally mediated. The cognitive, emotional and sociocultural dimensions of learning are all interrelated. As one researcher points out: “Not only are emotions often given expression during interaction in social settings, but it is often social settings that give rise to emotions.”

Unfortunately, a lot of approaches to learning design don’t do justice to the fact that learning is not all in the mind.

For example, increasing globalisation is a widely-recognised phenomenon, but the nuances of its influence are often unappreciated: what cultural baggage does a particular learning experience carry? What expectations do the designers have about how people will engage with the experience? What underlying, unquestioned ideas do they have about what “learning success” actually looks like and how to measure it? How can social norms and personal biases affect practical approaches to learning design?

As learning experience designers, we should always be careful to check what implicit assumptions we bring to the design process, as ideas that seem perfectly appropriate and useful might not be acceptable to learners in some contexts. The adage “think globally, act locally” remains very sound advice.

And why does it matter that the learning environment itself is a social context?

For one thing, through peer support, one person’s skills or strengths can support the development of those abilities in others. This can help learners ultimately to become more autonomous, able to achieve things independently which they weren’t previously able to do without help.And in settings where people are learning in teams (such as at work or in sports), effective collaborative learning allows for shared cognition, active listening, consideration of a range of alternatives and pooling of individuals’ various abilities.What’s more, when the success of individual goals or tasks actually depends on teammates’ own successes, this improves social cooperation and a sense of shared responsibility. Essentially: everyone succeeds when everyone succeeds. As such, a team with a shared goal is quite distinct from a group of people who just happen to occupy the same space.

So there you have it. Principle #1 of designing an effective learning experience: an understanding of context is key. The whole person and the whole environment are relevant to effective learning, not merely the subject matter at hand.

We should remember that the learning experience will vary greatly according to a particular individual’s cultural norms and expectations, their emotional state, their prior knowledge, motivation(s), commitment, self-awareness, aptitude for a given subject or skill, their relationship with other learners, etc.

Effective learning is not simply a question of transmitting information from expert to novice; learners need to understand how the learning process itself works and how it relates to their own context, experience and identity.


References

Bird, C. M., & Burgess, N. (2008). The hippocampus and memory: Insights from spatial processing. Nature Reviews Neuroscience, 9(3), 182–94. doi:10.1038/nrn2335

Cheek, D.W. (2015). ‘A panoramic view of the future of learning and the role of design(ers) in such experiences.’ In B. Hokanson, G. Clinton & M. W. Tracey (Eds.),  The design of learning experience: Creating the future of educational technology, London: Springer, pp. 5-37.

Chen, O., Castro-Alonso, J. C., Paas, F. & Sweller, J. (2018). ‘Undesirable difficulty effects in the learning of high-element interactivity materials’. Frontiers in Psychology, 9(1483), pp. 1–7.

Churchill, E., Okada, H., Nishino, T., & Atkinson, D. (2010). ‘Symbiotic gesture and the sociocognitive visibility of grammar in second language acquisition’. The Modern Language Journal, 94, p. 234–253.

Credé, M., Tynan, M. C. & Harms, P. D. (2017). Much ado about grit: A meta-analytic synthesis of the grit literature. Journal of Personality and Social Psychology, 113(3), 492–511. Accepted manuscript version retrieved 17 October 2019 from https://pdfs.semanticscholar.org/000a/51e0d37b8a557318559e19905d0f07f9ea00.pdf

Deci, E. L. & Ryan, R. M. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78.

Leroy, V., Grégoire, J., Magen, E., Gross, J. J. & Mikolajczak, M. (2012). Resisting the sirens of temptation while studying: Using reappraisal to increase focus, enthusiasm, and performance. Learning and Individual Differences, 22, 263–268.

Murray, G. (2014). The social dimensions of learner autonomy and self-regulated learning. Studies in Self-Access Learning Journal, 5(4), 320–341.

Sheard, M. (2009). Hardiness commitment, gender, and age differentiate university academic performance. British Journal of Educational Psychology, 79, 189–204.

Schweppe, J. & Rummer, R. (2014). Attention, working memory, and long-term memory in multimedia learning: An integrated perspective based on process models of working memory. Educational Psychology Review, 26(2), 285–306.

Ushioda, E., & Dörnyei, Z. (2009). Motivation, language identities and the L2 self: A theoretical overview. Motivation, language identity and the L2 self, 1-8.

Van den Bossche, P., Gijselaers, W. H., Segers, M., & Kirschner, P. A. (2006). Social and cognitive factors driving teamwork in collaborative learning environments: Team learning beliefs and behaviors. Small Group Research, 37(5), 490–521.

Ward, P., Hodges, N. J., Williams, A. M., & Starkes, J. L. (2004). ‘11 Deliberate practice and expert performance’, in Skill acquisition in sport: Research, theory and practice, 231, pp. 434–479.

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