So, what's next for cognitive science in education?


So, what's next for cognitive science in education?

Last week, the EEF released their review on Cognitive Science in Education, which covers areas such as retrieval practice, spacing, interleaving, dual coding and Cognitive Load Theory. They highlighted that knowing about these can be really valuable for teachers and that there are a general set of principles, if not specific strategies, that help.

However, they also highlighted that teaching and cognitive science are messy, complex and nuanced. Specifically, more research is needed from both a wider range of subjects and a wider range of students.

This got us at InnerDrive thinking: what are the broad principles of cognitive science that most would agree with? And crucially, what questions would we like to see research explore moving forward?

 

The principles of cognitive science

In some respects, cognitive science research may not tell us much more than we already know about how students learn, but it does provide a framework and an explanation for it. For example:

  1. Working memory is small and easily overloaded
  2. Information is forgotten if it is not revisited regularly
  3. If we think hard about things, we are more likely to remember them
  4. Novices know less than experts, and as such need scaffolding, support and modelling to help them

 

It’s clear to see how research areas such as retrieval practice, spacing, interleaving and Cognitive Load Theory have developed from these four principles.

 

So, where next for cognitive science in education?

Once we agree on the above general principles, we can then delve deeper into the specific strategies that they may generate. There is never going to be a “one size fits all” or “off the shelf” strategy that is guaranteed to work. Teacher judgement and expertise will always play a role.

This is because many factors affect teaching — as the brilliant Evidence in Education guys highlight in the Great Teaching Toolkit Review, factors such as the content, the environment and maximising opportunity to learn all play a role. This is neatly summed up in a different way by the Chartered College of Teaching in this graphic:

Venn diagram. Circle 1 reads: best available evidence from research. Circle 2 reads: context - system, setting, group, individual. Circle 3 reads: teacher experience, expertise and professional judgment. The intersection of the 3 circles reads: evidence-informed practice.

So, that is what we do know about using research to inform teaching strategies and impact learning outcomes. But what do we need to figure out next? Here at InnerDrive, there are 10 questions we would love cognitive science research to explore in more detail over the coming years:

  1. How much time should we leave before revisiting material with spacing? We have some rough guidelines on this, but more detail would be helpful.

  2. Should we do some blocking first before we do interleaving? As far as we know, this is one of the few studies that looked at this. Essentially, we know that interleaving is more effective, but also that students don’t like it — the study found that doing some blocking before interleaving achieved similar results to just interleaving, but was much more enjoyable. Does this mean in practice a combination of the two may be best?

  3. How many different topics should we interleave? How many is too many? We have explored this in a previous blog (our gut feeling is probably around 3-4 topics), but it would be nice to have some more data on this.

  4. Which format of retrieval practice works best? There are lots of different ways to use retrieval practice: multiple choice quizzes, verbal Q & A, past papers, flashcards… but which one works best for which situation?

  5. Is there an ideal percentage of time to spend in each lesson on retrieval practice? We imagine the answer is no. But it is a question we get asked a lot, so some more research on the subject would definitely be useful.

  6. Does retrieval practice work differently for novices and experts? It is well established that novices think and behave differently to experts. What impact does retrieval practice have on either?

  7. How do we best balance 30 students in one class having different optimal levels of cognitive load? This is the age old issue of differentiation. If it is hard to measure cognitive load, how do we find an optimal way to ensure we only meet some students’ ideal cognitive load and overload all the others who have different sweet spots within one classroom?

  8. Does the difference in working memory in young and old students make some areas of cognitive science more pertinent than others for different age groups? A recent paper found that retrieval practice was effective for a large age range of students, but is the same true for other aspects of cognitive science? For example, we suspect Cognitive Load Theory may be even more important for younger students, as their working memory is smaller, but don’t currently have the evidence to back this up.

  9. What are the best design principles to maximise dual coding in education? Dual coding is perhaps one of the areas of cognitive science that has intrigued educators the most, who yet get very little training time dedicated to designing effective PowerPoint slides or exploring principles of design.

  10. How do we best balance providing support (i.e. scaffolding) and helping students think hard with desirable difficulties? Thanks to cognitive science principles, we are aware of “desirable difficulties” and that “memory is the residue of thought”. Both of these have helped shaped many educators’ practice. However, balancing these with ensuring early success is always going to be difficult. More direction on this would be beneficial.

 

These are some of the questions that we’d like to see research find answers to — and we’re sure you have even more.

But in the absence of a definitive answer, we shouldn’t stop using these techniques. Teachers are experts in their domain and know their students best, and we should trust our colleagues with their professional judgement. Chances are we will never get a final and indisputable answer on most of these, but we can marry what we do know with our professional experience to make the best judgement call possible.

 

Final Thoughts

Cognitive science is the research of how students think, learn and acquire knowledge. As this is precisely the goal of education with students, the research in this area is of great importance. It really matters. It is not intended to replace teacher judgement, but rather to inform it.

As a profession, we have been plagued by fads and gimmicks, wasting precious time, effort and money. At a time when we are short of all three, it is imperative that we use research to ensure we help our students learn as effectively and efficiently as possible.

Research will never have all the answers — nor should we expect it to. But it can help us develop best bets, principles, or guidelines. We should keep demanding that researchers explore these difficult but important questions. If they do, then cognitive science can continue to really help us all develop our practice, and make better informed decisions.

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