At the ResearchED conference last Saturday, when I queried the usefulness of the diagram of working memory that was being used, I was asked two questions. Here’s the first:
What’s wrong with Willingham’s model of working memory?
Nothing’s wrong with Willingham’s model. As far as I can tell, the diagram of working memory that was being used by teachers at the ResearchED conference had been simplified to illustrate two key points; that working memory has limited capacity and that information can be transferred from working memory to long-term memory and vice-versa.
My reservation about it is that if it’s the only model of working memory you’ve seen, you won’t know what Willingham has left out, nor how working memory fits into the way the brain processes information. And over-simplified models of things, if unconstrained by reality, tend to take on a life of their own which doesn’t help anyone. The left-brain right-brain mythology is a case in point. An oversimplified understanding of the differences between right and left hemispheres followed by a process of Chinese whispers ended up producing some bizarre educational practices.
The second question was this:
What difference would it make if we knew more about how information is processed in the brain?
It’s a good question. The short answer is that if you rely on Willingham’s diagram for your understanding of working memory, you could conclude, as some people have done, that direct instruction is the only way students should be taught. As I hope I showed in my previous post, the way information is processed is more complex than the diagram suggests. I think there are three key points that are worth bearing in mind.
Long-term memory is constantly being updated by incoming sensory information
Children are learning all the time. They learn implicitly, informally and incidentally from their environment as well as explicitly when being taught. It’s well worth utilising that ability to learn from ‘background’ information. Posters, displays, playground activities, informal conversations, and dvds and books used primarily for entertainment, can all exploit implicit, informal and incidental learning that will support and extend and reinforce explicit learning.
We’re not always aware that we are learning
I only need two or three exposures to an unfamiliar place, or face or song before I can recognise it again, and I don’t need to actively pay attention to, or put any effort into recalling, the place, face or song in order to do so. I would have reliably learned new things, but my learning would be implicit. I wouldn’t be able to give accurate directions, describe the face so that someone else would recognise it, or hum the tune. (Daniel Willingham suggests that implicit memory doesn’t exist, but he’s talking about the classification rather than the phenomenon.)
Peter Blenkinsop and I found that we were using different definitions of learning. My definition was; long-term changes to the brain as a result of incoming information. His was; being able to explicitly recall information from long-term memory. Both definitions are valid, but they are different.
Working memory is complex
George Miller’s paper ‘The magical number seven, plus or minus two’ is well worth reading. What’s become clear since Miller wrote it is that his finding that working memory can handle only 7±2 bits of information at once applies to the loops/sketchpads/buffers in working memory. At first, it was assumed there was only one loop/sketchpad/buffer. Since then more have been discovered. In addition, due to information being chunked, the amount of information in the loops/sketchpads/buffers can actually be quite large. On top of that, the central executive is simultaneously monitoring information from the environment, the body and long-term memory. That’s quite a lot of information flowing through working memory all the time. We don’t actively pay attention to all of it, but it doesn’t follow that anything we don’t pay attention to disappears forever. In addition to working memory capacity there are several other things the brain does that make it easier, or harder, for people to learn.
Things that make learning easier (and harder)
1. Pre-existing information
People learn by extending their existing mental schemata. This involves extending neural networks – literally. If information is totally novel to us, it won’t mean anything to us and we’re unlikely to remember it. Because each human being has had a unique set of life experiences, each of us has a unique set of neural networks and the way we structure our knowledge is also unique. It doesn’t follow that everybody’s knowledge framework is equally valid. The way the world is structured and the way it functions are pretty reliable and we know quite a lot about both. Students do need to acquire core knowledge about the world and it is possible to teach it. Having said that, there are often fundamental disagreements within knowledge domains about the nature of that core knowledge, so students also need to know how to look at knowledge from different perspectives and how to test its reliability and validity.
Tapping into children’s existing schemata, not just those relating to what they are supposed to be learning in school but what they know about the world in general, can provide hooks on which to hang tricky concepts. Schemata from football, pop culture or Dr Who can be exploited, not in order to make learning ‘fun’, but to make sense of it. That doesn’t mean that teachers have to refer to pop culture, or that they should do so if it’s likely to prove a distraction.
2. Multi-sensory input
Because learning is about the real world and takes place in the real world, it usually involves more than one sensory modality – human beings rely most heavily on the visual, auditory and tactile senses. Neural connections linking information from several sensory modalities make things we’ve learned more secure because they can be accessed via several different sensory routes. It also makes sense to map the way information is presented as accurately as possible onto what it relates to in the real world. Visits, audio-visuals, high quality illustrations and physical activities can convey information that chalk-and-talk and a focus on abstract information can’t. Again, the job of multi-sensory vehicles for learning isn’t to make the learning ‘fun’ (although they might do that) or to distract the learner, but to increase the amount of information available.
The brain relies on trial-and-error feedback to fine-tune skills and ensure that knowledge is fit for purpose. We call trial-and-error learning in young children ‘play’. Older children and adults also use play to learn – if they get the opportunity. In more formal educational settings, formative assessment that gives feedback to individual students is a form of trial-and-error learning. It’s important to note that human beings tend to attach greater weight to the risk of failure and sanctions than they do to opportunities for success and reward. This means that tasks need to be challenging but not too challenging. Too many failures – or too many successes – can reduce interest and motivation.
Willingham emphasises the importance of rehearsal in learning. The more times neural networks are activated, the stronger the connections become within them, and the more easily information will be recalled. Rehearsal at intervals is more effective than ‘cramming’. That’s because the connections between neurons have to be formed, physically, and there’s no opportunity for that to happen if the network is being constantly activated by incoming information. There’s a reason why human beings need rest and relaxation.
Willingham is often quoted as saying ‘the brain is not designed for thinking’. That’s true in the sense that our brains default to quick-and-dirty solutions to problems rather than using logical, rational thought. What’s also true is what Willingham goes on to say; ‘people like to solve problems, but not to work on unsolveable problems’ (p.3). The point he’s making is that our problem-solving capacity is limited. Nonetheless, human technology bears witness to the fact that human beings are problem-solvers extraordinaire, and the attempts to resolve problems have resulted in a vast body of knowledge about how the world works. It’s futile to expect children to do all their learning by problem-solving, but because problem-solving involves researching, re-iterating, testing and reconfiguring knowledge it can be an effective way of acquiring new information and making it very memorable.
6. Writing things down
Advocates of direct instruction place a lot of emphasis on the importance of long-term memory; the impression one gets is that if factual information is memorised it can be recalled whenever it’s needed. Unfortunately, long-term memory doesn’t work like that. Over time information fades if it’s not used very often and memories can become distorted (assuming they were accurate in the first place). If we’ve acquired a great deal of factual information, we won’t have time to keep rehearsing all of it to keep it all easily accessible. Memorising factual information we currently need makes sense, but what we need long-term is factual information to hand when required, and that’s why we invented writing. And books. And the internet, although that has some of the properties of long-term memory. Recording information enormously increases the capacity and reliability of long-term memory.
In a classic Sesame Street sketch, Mr Johnson the restaurant customer suggests that Grover the waiter write down his order. Grover is affronted: “Sir! I am a trained professional! I do not need to write things down. Instead, I use my ‘waiter’s memory’.” Waiters are faced with an interesting memory challenge; they need to remember a customer’s order for longer than is usually possible in working memory, but don’t need to remember the order long-term. So they tend to use technical support in the form of a written note. Worth watching the sketch, because it’s a beautiful illustration of how a great deal of information can be packed into a small timeframe, without any obvious working memory overload. (First time round most children would miss some of it, but Sesame Street repeats sketches for that reason.)
It won’t have escaped the attention of some readers that I have offered evidence from cognitive science to support educational methods lumped together as ‘minimal guidance’ and described as ‘failing’ by Kirschner, Sweller and Clark; constructivist, discovery, problem-based, experiential, and inquiry-based teaching. A couple of points are worth noting in relation to these approaches.
The first is that they didn’t appear suddenly out of the blue. Each of them has emerged at different points in time from 150 years of research into how human beings learn. We do learn by experiencing, inquiring, discovering, problem-solving and constructing our knowledge in different ways. There is no doubt about that. There’s also no doubt that we can learn by direct instruction.
The second point is that the reason why these approaches have demonstrably failed to ensure that all children have a good knowledge of how the world works, is because they have been extended beyond what George Kelley called their range of convenience.
In other words they’ve been applied inappropriately. You can’t just construct your own understanding of the world and expect the world to conform to it. Trying to learn everything by experience, discovery, inquiry or problem-solving is a waste of effort if someone’s already experienced, discovered or inquired about it, or if a problem’s already been solved. Advocates of direct instruction are quite right to point out that you usually need prior knowledge before you can solve a problem, and a good understanding of a knowledge domain before you know what you need to inquire about, and that many failures in education have come about because novices have been expected to mimic the surface features of experts’ behavior without having the knowledge of experts.
Having said that, relying on an oversimplified model of working memory introduces the risk of exactly the same thing happening with direct instruction. The way the brain processes information is complex, but not so complex it can’t be summarised in a few key principles. Human beings acquire information in multiple ways, but not in so many ways we can’t keep track of them. Figuring out what teaching approaches are best used for what knowledge might take a bit of time, but it’s a worthwhile investment, and should help to avoid the one-size-fits-all approach that has bedevilled the education system for too long.
Image of Grover from Muppet Wiki http://muppet.wikia.com/wiki/Grover