Tag Archives: writing

The Antidote for an AI snake bite – Metacognition

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I first wrote about metacognition back in 2019 – the skill of thinking about your own thinking. Since then, much has changed, I have learned a bit more but crucially AI has come along and is having a significant impact on much of what we do.

It’s now woven into how we write, make decisions and even remember, and with that comes the danger of AI quietly eroding our ability to develop metacognitive skills. Taking the path of least resistance and delegating the hard work to AI leaves us exposed, and ultimately dependant.

As important as metacognition is for managing our own thinking, it’s indispensable when working with AI. It’s what allows us to evaluate the output rather than simply accept it.

TL;DR – the short audio version

Metacognition
Meta comes from Greek, meaning “beyond” or “about.” Metadata for example is data about data, so “metacognition” is thinking about thinking, you’re not solving the problem, you’re watching yourself solve it. Think of it like this – when a chef makes a sauce, he is cooking. He tastes as he goes, deciding if it needs a little more salt, that pause to check if it’s all going to plan, is the meta part. Metacognition works the same way – you’re not just thinking, you’re pausing to ask questions about what you’re doing e.g. does that make sense, what’s the evidence for this, what should I try next?

“Those who know how to think need no teachers.” – Mahatma Gandhi

Flavell and the fluency illusion – Metacognition was coined by the developmental psychologist John Flavell in the 1970s, he made an important distinction.

  • Cognition – the actual knowledge and skills you’re acquiring (formulas, theories etc)
  • Metacognition – your knowledge about that knowledge, your ability to judge accurately what you understand, what you don’t, and what to do about the gap

“Metacognition refers to one’s knowledge concerning one’s own cognitive processes” – John Flavell

Flavell broke it down even further:

  • Metacognitive knowledge – understanding how you learn best.
  • Metacognitive regulation – planning, monitoring, and adjusting your approach as you go.
  • Metacognitive experience – the gut feeling of “I’ve got this” or “I’m lost”, which, crucially, is often wrong.

That last point, the gut feeling being wrong, is where most students come unstuck. Psychologists call it the fluency illusion. Re-reading a chapter, highlighting a paragraph – these feel like learning because the material is familiar and easy to process. But familiarity is not the same as retrieval. You recognise the answer when it’s in front of you but that’s a completely different mental operation to producing it from memory in the exam under pressure. The result is a systematic and predictable overconfidence, students walk out of revision sessions feeling as if they are ready, and walk out of the exam hall feeling like they weren’t.

Why does it matter – Research suggests metacognitive skill is often a better predictor of exam success than IQ, because it’s not about how much a student knows but how well they manage their own learning process. That said, it only helps if it leads to action, noticing confusion is only useful if the student actually changes course rather than just being aware of the problem.

“Metacognition is the ability to, at any moment, step off the stage and sit down in the director’s chair.” – Ujjwal Ganesh, author The Observation Effect

The Antidote to AI
In a previous blog I highlighted the problems with Khanmigo, Khan Academy’s AI tutor. It struggled because it was built like a virtual Socrates, and needed students to ask good questions to prove its worth. The trouble was that many students simply replied “IDK” (I Don’t Know). Not because they were being difficult, but because if you don’t have the metacognitive skills to think through what you know and what you don’t, you can’t ask useful questions. This is the quiet danger of a world with answers on tap. AI can hand you correct information in seconds, but it cannot give you a sense of what you personally still need to learn. That judgement remains yours.

“Thinking: the talking of the soul with itself.”  – Plato

It’s also the skill we need most in order to work with AI properly, to check whether its answers are actually correct, to judge whether they’re useful for what we’re trying to do, and to push our understanding to a higher level. In other words, we need to apply metacognition to AI’s output the same way we apply it to our own thinking, not just to ask “do I understand this?” but “is this actually right, and is it what I needed?” Metacognition does two jobs here. It protects (The antidote) stopping AI from doing our thinking for us. It also helps us get better at using AI by teaching us to question, test, and push back. Same skill, two uses.

Conclusion
Metacognition has always been very important in terms of learning, helping us regulate our own thinking, finding the gap between what we assume we know and what we actually know, which helps us deepen our understanding. That job hasn’t gone away. If anything, it matters even more. But AI makes it doubly important, it’s not just about regulating our own thinking, but our thinking about AI’s thinking.  

Nobody will wake up having forgotten how to think. It’s a slow transfer of judgement, question by question, until the habit of checking simply isn’t there anymore. AI hasn’t changed what metacognition is, It’s just made it a skill we can no longer afford to leave undeveloped, for our own thinking, and now, for everything we borrow from someone, or something, else.

Want to learn more – Metacognition: An Important Skill for Modern Times | Brendan Conway-Smith

Mastery Learning – The case for jumping from A to C

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Firstly, let me say that I am a huge fan of Mastery Learning, after all, what’s not to like. In simple terms all that is required is for the student to fully understand a topic before moving onto the next. They must master ‘A’ before moving to ‘B’, and ‘B’ before ‘C’. To skip ahead would of course be mad. To those who have not thought too much about this before, you might assume this is how all learning works, until you reflect on your own schooling, where progression was based on age, and not understanding!

TL;DR – the short audio version

But it’s not the only way to learn. Much of what we learn is not linear, in fact knowledge might be better thought of as a web, that you can come at from many directions rather than a ladder.

Mastery learning
Developed by Benjamin Bloom of Blooms taxonomy fame, Mastery Learning was driven by the 2-sigma problem – students receiving one-to-one tutoring outperformed classroom peers by two standard deviations, effectively moving from a grade C to a grade A. By fixing the standard rather than the time, he believed most students could reach levels of achievement traditionally reserved for the few.

This depended on formative assessment and corrective instruction. Low stake tests are used to identify knowledge gaps with the student needing to score around 80% – 90% before they can move on. If not, they receive “alternative” instruction rather than repetition. This continuous feedback loop was Bloom’s way of bringing classroom learning closer to that which can be achieved by one-to-one tutoring.  The word alternative is important here, the student does not simply go over the same material again, instead they are given a different explanation or re-taught with another method, for example pairing the student with those who have already reached mastery.

Sal Khan has adopted Mastery Learning in Khan Academy, here he makes a compelling case for its use with characteristic clarity – TED talk from 2018.

Jumping from A to C with no B
To help understand how we might pull off this magic trick, let’s look at the work of Lev Vygotsky, he developed the idea of the Zone of Proximal Development (ZPD). It makes a distinction between what a learner can do on their own, and what they can do with the right support. The gap between those two is not a barrier to cross, it’s where learning happens.

When a learner jumps to C with appropriate support, they do not completely ignore B they look back on it in the context of what they are about to learn in topic C. Because B now has a purpose, it tends to be learned and remembered more deeply than if it had been drilled in isolation.

The sequence flips: C with support → encounter B in context → C independently. The gap doesn’t have to be filled before you advance. It gets filled through advancing.

This approach is supported by Robert Bjork’s research on “desirable difficulties”, introducing challenge before a learner feels ready improves learning. Struggle is not always a sign something has gone wrong – it’s an opportunity for good learning.  

Horses for courses
This is not an argument to use the A – C approach over Mastery, there are situations where they can both be beneficial. It depends on context, for example early maths and reading benefit from attention to sequence, here Mastery should be used, but where personal developmental and social skills are the objective, the A-C approach might work best. Secondary school learners benefit from a blend, of both as well as project-based challenges, which helps develop problem solving skills. Adult professionals should be trusted to identify and fill in their own gaps, however where large amounts of knowledge and skills are required in a short period of time, as is the case with many high-stakes professional exams, Mastery is preferred.

Conclusion
The problem with Mastery Learning as an overarching model is that it presents a highly believable story as to how knowledge is actually acquired. Real learning, the kind that sticks and transforms, has always been messy. It involves confusion, premature exposure, partial understanding, backtracking, and sudden reorganisation. It might mean you are thrown into C before you feel ready and finding, to your surprise, that you manage.

Mastery is often described in terms of building strong foundations to support your future learning that sits on top. But knowledge is not a foundation, that once in place remains solid and strong, you never fully master anything, there are always gaps that over time without use will decay. Learning is less of a solid foundation and more like a piece of cheese, full of holes, and if left unattended, will only acquires more.

It is not always necessary to wait until you feel completely ready, in fact, the truth is many students never do. There are times when you just need to jump in, struggle, backfill, and push forward. The good news, you will develop a stronger and more resilient understanding of the subject – messy and illogical it might be, but its also hugely effective.

Sticky – The Science of Storytelling

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Long before writing, and even “classrooms,” people shared knowledge through the telling of stories. These stories conveyed essential lessons in survival and reflected the social norms of their time, handed down through generations.

To fulfil their purpose, they had to be memorable. What remains unclear is, did the story evolve to fit the brain’s natural ability to remember or did stories in some way shape our brains to make them easier to recall – a classic chicken-and-egg dilemma.

Regardless, it could be argued that stories were our first educational technology, influencing culture, guiding decisions, and ensuring knowledge was not lost.

If you don’t have time to read this month’s blog – listen to my AI alter ego summarise the key points.

Today, when we think of stories, we often associate them with novels, films, animations and more recently podcasts. At its core, they are simply a structured way of sharing events and information, with most following a familiar pattern. They begin by setting the scene, move into a middle phase where the story unfolds and end with some form of resolution that provides clarity or closure. This structure helps us make sense of experiences, maintain attention, communicate ideas, evoke emotions, and connect with others in meaningful ways. All of which help with recall.

They are also incredibly persuasive, and can become a vehicle for knowledge transfer, simply saying, “let’s take a moment, relax, I want to tell you a story” changes the mood in the room and opens the mind for a new experience.

If you’re still unsure about their power, Yuval Noah Harari provides a compelling example. He explains that money holds no inherent value, a banknote is simply paper, and digital currency just data. What makes money meaningful is the collective belief in its worth. This shared understanding allows it to function as a medium of exchange for goods, services, and influence.

He goes on to say….

Money is probably the most successful story ever told” he argues. “It has no objective value… but then you have these master storytellers: the big bankers, the finance ministers… and they come and they tell a very convincing story. ‘Look this piece of paper, it is actually worth 10 bananas’… and it works. Try doing that with a chimpanzee – it won’t work!” – Yuval Noah Harari, historian, public intellectual, and bestselling author

Why are stories sticky?
But what is happening in the brain when you hear a story or read one for yourself? Why do stories stay with us long after we’ve heard them, what makes them stick?

Cognitive rapport – When someone tells a story, something remarkable happens in the brain. Instead of just processing words, the listener’s brain begins to light up in multiple areas all at once. Stories create what researchers call neural coupling, the listener’s brain patterns start to mirror the storyteller’s, helping ideas flow more smoothly and making them easier to understand (Stephens et al., 2010).

“The human species thinks in metaphors and learns through stories.”  – Mary Catherine Bateson, writer, and cultural anthropologist

Emotional – Importantly, stories also stir emotion and when emotions are triggered, the amygdala and hippocampus work together to strengthen memory (Article McGaugh, 2013). In one test, a neutral learning event was given an emotional focus. Subjects were asked to memorise a list of words, a non-emotional task. They were then exposed to a brief, intense emotional experience e.g. Putting their arms into icy water (Cold Pressor Stress Test), which released stress hormones, epinephrine, and cortisol, telling the brain it is an important event. When tested weeks later, the individuals had forgotten the cold-water experience, but remembered the list of words!

“Storytelling is the most powerful way to put ideas into the world today.” – Robert McKee, author, lecturer, and story consultant

Structured – Stories give knowledge a shape and structure. A beginning, a challenge, and a resolution acting like mental scaffolding, allowing learners to slot new information into place. Structure also reduces cognitive load, (John Sweller 1988), and help create schemas, which are interconnected mental chunks of knowledge that are stored more easily in long term memory.

“Stories are memory aids, instruction manuals and moral compasses.” – Aleks Krotoski, broadcaster, journalist, and social psychologist

Engaging – And lastly, stories build a human connection, helping creat greater levels of engagement. Neuroscientist Paul J. Zak (2015) discovered that compelling narratives those with a strong dramatic storyline trigger the release of oxytocin, the neurochemical responsible for trust and empathy. In a learning context, this surge of empathy makes you more receptive to the message and strongly motivates, helping internalise the information and transforming simple facts into knowledge.

A word of caution – seductive details
However not all stories help us learn. The danger is that they include fascinating but irrelevant information known as “seductive details” (Harp & Mayer, 1998). This results in cognitive overload, causing the brain to waste resources processing the more interesting information at the expense of core principles. It can also break down that strong mental scaffolding, misdirecting the brain, to build a new organisational framework around the wrong idea. To avoid this, the detail in your narrative must directly support the learning objective, ensure the story integrates the facts, rather than just decorating them.

The final chapter
For educators, storytelling is not just a “nice extra” it’s a valuable tool and a natural way to help people learn. A well-told story draws attention, lowers resistance, and creates the sense that what follows is worth holding on to. Learners don’t just hear the information, they experience it, making knowledge far more memorable.
For learners, resist the urge to dismiss the story as a diversion from the important stuff, and instead listen with curiosity. They work on the mind in subtle ways connecting ideas, evoking emotions, and helping you see meaning, long after the classrrom door has closed. In this state, your brain does much of the hard work for you.

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