Shining a Light on the Science of Learning

The ‘Science of Learning’ is a term that is currently being used as a ‘new’ anchor for curriculum design. It is a bit of new branding on pedagogy that makes it seem more palatable than ‘pedagogy’. The Science of Learning is, in fact, a synthesis of pedagogical theory and (a bit like a hearty stew) it is always good to know what is actually in it so that we can appreciate the ingredients we are being served a bit more.

Here are some of the key ingredients I’ve spotted that are worthwhile to know about.

1. Constructivism

Key Idea: Learning is an active, constructive process where learners build knowledge by connecting new information to their existing understanding.

Unpacking: Aligns with Vygotsky’s Sociocultural Theory (social interactions build knowledge). Drives the emphasis on student-centred, inquiry-based learning and encourages discussing learning to form deeper connections with new knowledge. Key players are Bruner, Piaget and Vygotsky.

What it looks like: We shouldn’t tell students what to think or what to write down. Instead, we can engineer social interactions and activities where they figure things out and make notes for themselves. It could be summarised by the difference between taking notes and making notes.

2. Cognitive Load Theory

Key Idea: Human working memory has limited capacity, and learning is more effective when the way that learning is delivered reduces extraneous cognitive load.

Unpacking: It is important to use strategies like chunking and worked examples to break content down. This also supports Dual Coding by encouraging simplification of visual and verbal information and the importance of presenting one thing in several different ways. Cognitive Load Theory makes sense when we think about how we remember phone numbers or shopping lists in categories or chunks.

What it looks like: If you fill someone’s brain with a lot of new information then their ‘brain bucket’ is too full - and it even starts leaking. It is hard to process new information if the bucket is full - so information needs to be chunked and iterated so that it can be gradually filled and the knowledge is more likely to be retained. It might look like providing a hand out before the workshop, going over it briefly in the workshop and then extending thinking beyond the workshop rather than skipping to the ‘how to apply’ in the first workshop which might overload the brain.

Chunking - maybe because if you ate the whole block at once you would feel sick! Chunking learning is similar.

3. Distributed Practice

Key Idea: Spacing learning over time (rather than massing it in one session) improves retention and retrieval. Like a well-constructed brick wall, we build on previous layers by overlapping bricks and we can build big walls one layer at a time. Another easy way to imagine this is teaching like a spiral that loops back on itself to go forward a little and then loop back to reinforce prior learning. Bruner even calls this a spiral curriculum. (I wrote a blog expanding this to a crochet analogy).

Unpacking: Distributed Practice links to Cognitive Load Theory by avoiding overload through spaced intervals and incremental knowledge and skill acquisition and it encourages revisiting prior content by applying it to new contexts.

What it looks like: One workshop might cover ‘A’. The second workshop might cover ‘B’. A better solution is to build slowly so that ‘A’ is not forgotten. So workshop 1 covers ‘A’ and workshop 2 covers and workshop 3 covers ‘ABC’. So retention and iteration and cognitive load are all catered to.

4. Schema Theory

Key Idea: Knowledge is stored in mental frameworks that are individual and different for all of us based on prior experience (schemas). Learning involves organising new information into these structures or creating new structures into which we can insert new learning effectively.

Unpacking: Well-designed schemas can limit cognitive load. Ways of presenting new information matters and might be different for every learner depending on their prior knowledge and understanding or existing schemas.

What it looks like: This might look like finding a drawing or metaphor to anchor new learning to. Like a seahorse, they fare better when they can hook their tail into something known to keep them from floating away….

5. Dual Coding

Key Idea: Combining verbal and visual representations improves understanding and memory.

Unpacking: Some learners need diagrammatic summaries or visual versions of content in order to be able to process the information most effectively. Others need information verbally and aurally - presenting information in multiple ways means that more learners can access the ‘hook’. This supports the idea that 'lecturing’ is not effective unless it is partnered with additionally and differently coded content.

What it looks like: Have you ever played Pictionary? Words go with pictures like peas and carrots. Don’t deliver with just words and don’t deliver with just pictures. Consider both to increase your chances of a ‘true hook’.

6. Visible Learning

Key Idea: Focuses on high-impact, evidence-based practices that maximise student learning, such as feedback, metacognition (thinking about thinking), and direct instruction. Visible learning is like ‘chemistry in the classroom’ where you are watching for changes in states and supports evidence-based interventions with regular data gathering. Teachers do things because they have measurable effect on learner achivement.

Here is a great infographic from the Visible Learning website.

Unpacking: Teaching strategies need to be explicit and reflective. Learners should be able to talk about what they are learning and how they are learning it so that learning methodology and outcomes are all visible. The key player to find out more about Visible Learning from is John Hattie.

What it looks like: Success and the steps needed to reach success are clearly outlined so that students or participants can see what they are doing and know where they are at on a clear scale, rubric or success descriptor framework.

7. High-Impact Teaching Strategies (HITS)

Key Idea: Deliberate and reflective practices (e.g., questioning, feedback, explicit teaching) have been shown to be highly effective in improving student outcomes.

Unpacking: Draws from Cognitive Load Theory (e.g., worked examples) and Distributed Practice. Encourages Constructivist engagement via collaborative and inquiry-based methods.

What it looks like: Designing activities to be data-driven. Similar to visible learning, HITS are measurable and the impact is data-informed. HITS is all about measuring the impact in ways that are proven to be effective.

8. Universal Design for Learning (UDL)

Key Idea: Designing flexible learning environments to accommodate diverse learner needs from the outset means that no student is left behind. Learning is designed to cater to all rather than the normal few.

Unpacking: Applies principles of Dual Coding in ways students access, process and show their understanding of learning.

What is looks like: Predicting needs and learning interventions before they happen - providing clear text, enlarged text, alt text, dual coding, iconographic summaries in more with the needs to diverse learners in mind. Remember, not accommodating known learning needs is akin to hosting a workshop on the third floor and not providing a ramp or elevator to wheelchair users. Once you know better - you do better, right?

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It seems like a lot, doesn’t it? Yes, great learning has a lot of lenses applied to it for sure!

Of course there are more - but 8 quick-fire theories seemed like a digestible chunk for now.

What should we do with the science of learning?

Well, like a good stew - a balance of ingredients will make it rich and tasty. The science of learning calls for a mix of explicit instruction and constructivist methodology to enrich teaching and learning experiences. It is never one theory - and it always needs to be a special blend crafted for the people in front of you.

And, of couse, if you need support - I can help you with all of the above and more!

Lastly, just in case you fancy some more reading - here’s a small recommended list:

Make It Stick: The Science of Successful Learning by Brown, Roediger, & McDaniel

Powerful Teaching: Unleash the Science of Learning by Agarwal & Bain

The Case for Constructivist Classrooms by Brooks & Brooks

Visible Learning: The Sequel: A Synthesis of Over 2,100 Meta-Analyses Relating to Achievement, Hattie.

How People Learn by Bransford, Brown, & Cocking.

Working Memory and Learning by Gathercole & Alloway

Cognitive Load Theory in Action by Ayres, Kalyuga, & Sweller.

Drive: The Surprising Truth About What Motivates Us by Daniel Pink.

Principles of Instruction by Barak Rosenshine.

CAST Framework for UDL.

Don the black hat! A thinking strategy for doing things better

New Zealand is currently faced with a worrying economic downturn. There are additional threats on the horizon such as the rapid developments of AI, impacts of Globalisation, looming international conflict expansion and environmental disasters due to climate change just to name a few. We turn our faces to the light and try to look for moments of brightness in the news and, particularly in the education sector and public sectors, it feels very dark indeed. Where is the light?

In these situations, it is useful to put on a black hat after Edward De Bono.

What is Black Hat Thinking?

Black hat thinking is a a way to adopt a deliberately pessimistic and cautious approach to problem-solving and decision-making with all of the ‘worstest’ superlative outcomes that we can think of. It means that we get to focus on identifying potential risks, problems, and consider of the possible negative outcomes. It is one of the six thinking styles in Edward de Bono's Six Thinking Hats model.

Why is it useful?
Black hat thinking encourages a kind of healthy skepticism. A lot of technology has been touted as ‘the next best thing’ for example and then it has quickly turned into a bubble that has popped more quickly than we might have predicted. Some examples of these are the dot.com bubble or the open plan classroom bubble - some may say, too, the AI bubble but this has not yet popped. (More on this later). This type of thinking is useful for carefully predicting and examining any potential flaws and weaknesses which ends up being a very useful prediction and forecasting tool.

Logical Analysis
While it might often be perceived as negative and ‘red penning’ any new and exciting prospects, black hat thinking is not about being pessimistic for its own sake. Another way of understanding it is as a useful way to critically analyse new systems/approaches/tools as a risk assessment process to ensure that any potential risks or threats are identified so that some safeguards can be put in place. Black hat thinking means that teams can anticipate and prepate for possible challenges.

Reverse brainstorming

My favourite way to facilitate Black Hat Thinking is with a reverse brainstorm. This means we look at how to do the opposite of whatever goal it is that we are striving to achieve. “How can we ensure that all of our managers fail?” or “How can we make sure that students never learn to read?” or “How can I become the worst leader of all time?” are some fun examples to play with. In one particularly memorable example in a secondary school context we reverse brainstormed “How can we make sure our students are unprepared for the future?” and there were some shocking truths suddenly up for discussion when some teachers recognised that their current pedagogy was setting kids up to fail…

The next step of a reverse brainstorm is to be as creative as possible and come up with ‘all the ways’ to make the opposite happen. Go wild. Have fun. Then review.

The final step of the reverse brainstorm is to flip the brainstorm and negate all of the negative suggestions and rephrase them as positives. If one answer for a ‘how can we become the worst leader’ brainstorm was ‘be late for all meetings’ then the solution is ‘be punctual’. The black hat thinking and using the reverse brainstorm as a facilitation method means that all of the negatives have been predicted and the opposite risk managing opportunity can be identified to inform meaningful strategic planning.

Foreseeing the rocks

If you hate the idea of a reverse brainstorm, another useful metaphor is a boat on its way to ‘some magical island outcome’. This method is great for visual thinkers. Draw a boat and draw a bunch of rocks and waves and kraken and pirates and whatever else you think might get in the way of a journey and then set about naming the hazards. What are all of the things in the way? Once this is done, you can start to strategise what your marine chart/road map might need in order to steer around those obstacles.

Both of these strategic planning experiences require the black hat to be donned - and like a black wizard’s hat, the outcomes of black hat thinking can be magical.

Black hat thinking is thinking about the weather, the rocks and the crew’s capabilities to better avoid disasters.

Making some magic

If you know where you don’t want to go, then you can forge a better path to your rightful destination. Similarly, knowing all of the bad things that ‘might’ happen, means that you can plan to avoid and manage risks accordingly.

Recently I have been working on an ‘AI in the Classroom’ rubric and black hat thinking has really helped me to consider best use case scenarios - only because I’ve spent time thinking of worst use case scenarios and then sought to fix them through reverse engineering.

The black hat brainstorm highlighted worst use of AI as ‘mindless prompting’ and ‘worksheet pumping’, ‘biased without balance’, ‘industrial model on steroids’, ‘data misusing’ and ‘environmentally disastrous’ (to name a few) which can then inform more critical analysis of how to mitigate these risks with educated, mindful, purposeful and policy-protected best uses to help me to design my self-assessment rubric. (This is coming soon).

So what kind of black hat will you wear?

Of course, you don’t need a real hat - but imagining your own black hat strategy to make better decisions in your workplace or classroom is a great thinking strategy to adopt if you want to know better to do better.