Category Archives: Meta Cognition

Lessons from Khanmigo – Learning remains stubbornly human

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Sal Khan didn’t start Khan Academy in 2004 with a grand vision to disrupt global education. His objective was to help his cousin, Nadia, with her maths homework. He wasn’t trying to change the world, just be a good teacher. Despite these humble beginnings Khan Academy has become a huge success.

TL;DR – the short audio version

Khan Academy
Set up in 2005, the Khan Acadmey mission is to provide a free, world-class education to anyone, anywhere. It employs around 350 people and supports 40 to 50 million students each month. A not-for-profit that relies largely on donations (notably from the Gates foundation) to pay for its $120 million to $170 million operating costs.  

It is built on the idea that students learn best when studying at their own pace, able to revisit topics as many times as they like to clarify understanding. Support is available in the form of instant feedback, tips and hints and progress checking. The style of instruction is short (chunked) videos, often just a coloured pen writing on a black screen, followed by practice questions and step by step answers.  In terms of methodology It takes a flipped classroom approach. Instead of introducing new content in class, students watch videos or complete the initial learning at home. Class time can then be used for practice, discussion, and problem-solving. This allows the teacher to focus on addressing misunderstandings and supporting individuals. It incorporates mastery learning, where students are expected to fully understand a concept before moving on rather than progressing regardless of whether they’ve understood it or not.

Then in November 2022, the world changed when OpenAI launched ChatGPT, within two months it had 100 million monthly active users. Sal Khan actually received a personal email from OpenAI’s leadership just prior to its launch asking him to test the model. This was pretty special, a major new technology being given to educators, Duolingo were also early adopters because they offered something other businesses couldn’t. The opportunity to find out if AI could actually teach rather than simply automate process that led to efficiencies.

Khanmigo: Born 2023 Died 2026
On the 14th of March 2023 in partnership with OpenAI, Khanmigo was created. But this was no AI Chatbot simply offering answers to questions. Its core philosophy was to act as a virtual Socrates, asking questions such as: “what do you know about the subject already?” This was to reduce cognitive load, scaffold learning and create the right amount of desirable difficulty, all essential components for good learning. For teachers it helped them save time by producing lesson plans writing questions and tracking student progress.

So, what went wrong – Sal Khan really believed that AI, in particular Khanmigo would change the future of learning. In a widely viewed TED Talk in 2023, he declared, “We’re at the cusp of using AI for probably the biggest positive transformation that education has ever seen.”

However, in April this year (2026) even Khan had to admit “for a lot of students, it was a non-event. They just didn’t use it much.” While he remains optimistic about the many applicationa of AI in education, he’s also come to see its limits.

“I just view it as part of the solution; I don’t view it as the end-all and be-all.” Chalkbeat.

Part of the problem has been attributed to the students themselves, with Khans CLO Kristen DiCerbo saying that students aren’t great at asking questions. You can give them access to the world’s best AI tutor, but if they don’t know what they don’t understand, they won’t ask. And if they don’t ask, Khanmigo simply doesn’t work.

Lessons learned
Sal Khan has come in for a fair amount of criticism, partly due to his initial claims about Khanmigo being the biggest positive transformation that education has ever seen, and then having to admit that it wasn’t. But isn’t that precisely what innovation looks like? It takes a rare kind of conviction to believe deeply enough in an idea to pursue it, and it takes genuine integrity to stand up and admit you were wrong. Sal Khan didn’t just theorise about improving education, he tried to do something to make it better.

But all is not lost, there are some really important lessons to be drawn from the Khanmigo experiment. Not least about how AI technology actually fits into the practice of learning, and what impact it has on students when put to the test in real classrooms.

  • Students weren’t ready for Socrates – Khanmigo’s Socratic design required students to already possess some basic knowledge. When you don’t have the conceptual scaffolding to understand what you’re confused about, you can’t ask useful questions. This led some to simply past the same question into another AI platform to get the answer, and as a result learned nothing.
  • It favoured good students – Those with strong metacognitive skills (The ability to notice, monitor, and manage your own thinking) did well, but for the others it was a struggle leading to frustration and reduced engagement, clicking a few times before giving up.  Sal Khan said that it was like a shy student who won’t raise their hand.
  • Engagement was passive – Students didn’t actively engage in conversation, when asked a question by Khanmigo they often replied “IDK” (I don’t know) rather than thinking about what the question, resulting in usage falling below expectations. Initially engagement was high, but this was put down to novelty, and over time this simply fell away.
  • Not inspiring nor motivational – Although it was designed to be encouraging, you can only say “good attempt” so often before it has little effect. Students work hard for people. For a teacher who believes in them, a parent who will ask how they are feeling or a peer who can share their experience. Khanmigo removed all of that social texture. Although it is infinitely patient and never disappointed, there’s no one to let down.
  • Extrinsic motivation is underrated – Education theory has long championed intrinsic motivation, the idea that students should want to learn for its own sake. Khanmigo was built on that assumption. But for most students, extrinsic factors really matter e.g. grades, approval, peer comparison. Strip that away and many students simply don’t engage.
  • There was no relationship – Khanmigo could not replicate the sensitive, personal connection a human tutor provides, making it less effective, especially for struggling learners. A teacher knows that a student is distracted because of something that happened at home, or that they know the individual panics when faced with a test. The AI only “sees” the text.

Conclusion
Personally, I am a fan of Sal Khan, and see this as a huge educational experiment that simply didn’t work in the way it was intended. But “didn’t work as intended” is not the same as “wasted.” What Khanmigo revealed, perhaps more clearly than any research paper could, is that learning is stubbornly, irreducibly human. It requires relationship, stakes, and social texture. These are not new ideas, educators have argued this for decades but Khanmigo gave us a live, large-scale demonstration of what happens when we design as if those things don’t matter.

For those of us involved in teaching and course design, the lessons are important. We cannot assume metacognitive skill. Engagement needs scaffolding, not just encouragement. Motivation is more complex than theory suggests. And the relationship between teacher and learner is not a nice-to-have its critical.

Technology works best when it supports the human, not replaces them. Sal Khan himself has now arrived at this conclusion. The experiment is not over. But the next iteration will be better because of what this one taught us and that, in the end, is exactly how learning is supposed to work.

The independent learner – Metacognition

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Metacognition is not a great word but it’s an important one when it comes to learning, especially if you are studying at higher academic levels or on your own. Cognition refers to the range of mental processes that help you acquire knowledge and understanding or more simply, learn. These processes include the storage, manipulation, and retrieval of information. Meta on the other hand means higher than or overarching, put the two together and we are talking about something that sits above learning, connecting it by way of thought. For this reason, it’s often described as thinking about thinking or in this context thinking about how you learn.

Smarter not harder

When you have a lot to learn in terms of subject matter it may feel like a distraction to spend any time learning something other than what you must know, let alone reflecting on it, but this fits under the heading of working smarter not harder, if you can find more effective ways of learning that must be helpful.
As mentioned earlier cognition is about mental processes, storage and retrieval relate to memory, manipulation, to the shifting of attention, changing perception etc. But the meta aspect creates distance, allowing us to become aware of what we are doing, standing back and observing how for example perception has changed, this reflection is a high-level skill that many believe is unique to humans. One final aspect is that we can take control of how we learn, planning tasks, changing strategies, monitoring those that work and evaluating the whole process.

Keeping it simple

Its very easy to overcomplicate metacognition, in some ways its little more than asking a few simple questions, thinking about how you are learning, what works and what doesn’t.  Here are some examples as to how you might do this.

  • Talk to yourself, ask questions at each stage, does this make sense, I have read it several times maybe I should try writing it down.
  • Ask, have I set myself sensible goals?
  • Maybe it’s time to try something different, for example mind mapping, but remember to reflect on how effective it was or perhaps was not.
  • Do I need help from anyone, this could be a fellow student or try YouTube which is a great way to find a different explanation in a different format?

Clearly these skills are helpful for all students but they are especially valuable when studying on your own perhaps on a distance learning programme or engaged in large periods of self-study.

Benefits

There are many reasons for investing some time in this area.

  • Growing self-confidence – by finding out more about how you learn you will discover both your strengths and weaknesses. Confidence isn’t about being good at everything but understanding your limitations.  
  • Improves performance – research has shown that students who actively engage in metacognition do better in exams.
  • Gives control – you are no longer reliant on the way something is taught; you have the ability to teach yourself. Being an autonomous learner is also hugely motivational.
  • The skills are transferable – this knowledge will not only help with your current subjects but all that follow, not to mention what you will need to learn in the workplace.  

It will take some time initially but, in a way, metacognition is part of learning, it’s an essential component and as such you will end up knowing more about yourself at some point, even if you don’t want to, so why not do it sooner rather than later.

And just for fun – Sheldon knows everything about himself – even when he is wrong

The learning brain

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Brain 5

There are a number of books that not only taught me something but helped shape the way I think and opened up a whole new world. One such book was Mapping the Mind by Rita Carter, not as you might imagine a book about mind mapping but the Brain. Rita Carter is a science journalist rather than a neuroscientist and understands that it’s not about what she knows but what she can explain.

Having a better understanding of how the brain works will help do far more than improve your grades in a biology exam, you will develop insight as to why something works not only that it does. As a result, you can be confident you are using the most effective brain friendly learning techniques.

The infrastructure Brain 2
Rita Carter provides us with an excellent description of the brain, that it is as big as a coconut, the shape of a walnut, the colour of uncooked liver and consistency of firm jelly.

Imagine a cross section of the brain, taken from the side, alternatively look at the diagram opposite.

The cerebrum or cortex is the largest part of the human brain and is associated with higher brain function such as thought and action. It is divided into four sections.

  • Frontal lobe – associated with reasoning, planning, some speech, movement, emotions, and problem solving
  • Parietal Lobe – associated with movement, orientation, recognition, perception of stimuli
  • Occipital Lobe – associated with visual processing
  • Temporal Lobe – associated with perception and recognition of auditory stimuli, memory, and speech

The cerebellum coordinates movements such as posture, balance, and speech. Next to this is the brain stem, which includes the medulla and pons. These are the older parts of the brain and evolved over 500 million years ago. In fact, if you touch the back of your head and bring your hand forward over the top towards your nose, this effectively maps the ages in which the brain developed.

The Limbic system is largely associated with emotions but contains the hippocampus which is essential for long term memory and learning.

Synaptic gap – Cells that fire together wire together (Hebbian theory)
Although learning is complex, a large amount takes place in the limbic system because this is where the hippocampus sits. Here our memories are catalogued to be filed away in long-term storage across other parts of the cerebral cortex.

What comes next is important because it’s here within the hippocampus where neurons connect across what is called the synaptic gap that learning arguably begins. Synaptic transmission is the process whereby a neuron sends an electrical message, the result of a stimulus across the synaptic gap to another neuron that is waiting to receive it. The neuron’s never touch, the gap is filled by chemicals referred to as neurotransmitters examples of which include dopamine and serotonin. These are often referred to as the body’s chemical messengers.

Learning is making new connections, remembering is keeping them

When the stimulus is repeated the relationship between the neurons becomes stronger and so a memory is formed and learning has taken place. The whole process is called long term potentiation (LTP).

How does this help?
All a bit technical perhaps but very important as it explains so much. It is the reason that repetition is so valuable, for example, if you are reading something and it’s not going in, you need to fire those neurons again but perhaps using different stimulus. Try saying it out loud or drawing a picture alongside the text.

Don’t forget the blog I wrote in January 2018 that explained brain plasticity and how the brain changes as those new neural connections are made, a process called Neurogenesis.

The neurotransmitters, those chemicals released to fill the synaptic gap are also important as each one is different. For example, in addition to making you feel good, it’s likely that when you feel anxious your brain is releasing high levels of serotonin.

Although it’s fair to say there is still much we don’t understand about the brain, I  hope the blog has helped remove some of the mystery of learning, it’s not a magical process but a scientific one.

learn more

Dedicated to my dog Jack – our family dog and best friend

The Protege effect – Learning by Teaching

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Protege

The Protege effect states that the best way to learn is to teach someone else. Students develop a better understanding and retain knowledge longer than those who study in more traditional ways. The Roman philosopher Seneca put it even more simply ‘While we teach, we learn’.

The method, also called learning by teaching was originally developed by Jean-Pol Martin in the 1980s. Click to watch a short video.

 

There are many theories written about learning and education but the ones that are always most powerful for me are those that you can evidence in some way from your own experiences or from the experiences of others whose opinion you value. And I would be very surprised if any of my teaching colleagues would disagree with the basic concept that no matter how much you think you know about a subject or topic, the very process of teaching always offers up new thoughts and insights, deepening your understanding.

The teacher might be the student

The argument hinges on the relationship between a teacher and learner. Traditionally the teacher is the expert who provides knowledge, the learner the one who receives it, but the teacher need not be the person who stands at the front of class, the teacher can be the student and the student the teacher.

This role reversal is not as odd as it at first might seem, a good teacher will always listen to the answer a student gives in order to evaluate their own performance. And if you think of it like that, who is teaching who?

But how does it work? Imagine you were asked to teach a subject to others in your peer group. Knowing you were going to have to explain a topic will increase your level of engagement with the learning materials. In addition, reflection will be far deeper as you continually ask, does this makes sense to me? This process of preparing, “prepping” is one of the reasons teaching improves learning but there are others. For example, the construction of the learning itself will require imagination and creativity, how exactly will I teach this subject?  It may be a simple verbal explanation, conversational even, or perhaps something more formal, requiring slides or additional illustrations. Once again you will be forced to reflect, possibly writing down some of your ideas and again asking questions, how long will it take, am I making myself clear, what questions could I be asked? Its at this stage that you may even find your understanding lacking, requiring you to go back over what you previously thought you knew.

There is research (Bargh and Schul 1980) to prove that preparing to teach in the belief that you will have to do so improves learning, however there is one final stage, the teaching itself.  In 1993 Coleman, Brown and Rivkin investigated the impact of actually teaching, eliminating the effects resulting from the interaction with students, their conclusions, that there was a significant improvement in performance of those that taught compared to the those who prepared but didn’t in the end teach.

In summary, although thinking you have to teach and going through the process to do so improves learning, following through with the actual teaching is even better.

Protege in practice

Bettys Brain (Vanderbilt University) – Bettys brain is a computer based, Teachable Agent that students can teach and in so doing learn. The students develop a visual map (A concept map) of their own knowledge, forcing them to organise their thoughts. There are resources available within the programme to help them develop a deeper undertesting of the subject. They then teach what they learned to Betty, who like any other student will face a test at the end. If she does not do well in the test it is a reflection of the quality of the teacher or perhaps more precisely their understanding of the subject.

Click here for more details

Lessons for students – This is not a plea for students to pair up and teach each other, as good an idea as this might be. It is a hope that by explaining why teaching helps you learn, it gives an insight into how we all learn. For example, it highlights that reflection, i.e. thinking back on what you know is so important, it shows that high levels of concentration are required, the result of knowing you will have to explain concepts and ideas to others, and it offers up some evidence as to why talking out loud as you do when presenting, consolidates learning.

A few other takeaways, why not imagine you have to teach the subject you are learning and study with a “teaching mindset”. Preparing notes as if you are going to teach, crafting ideas as to how you might explain it to others. Get involved in group discussions, try to answer other student questions as they might answer yours.

Oh, and don’t always assume that the person in front of you fully grasps what they are saying, they are still learning as well.

 

 

 

 

Plastic fantastic – how the brain grows

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Stress BallA major new idea was presented to the world in 1991, to many it will mean very little but in terms of improving our understanding of the brain it was a milestone.

Functional magnetic resonance imaging (fMRI) had seen its roots in the earlier MRI, but instead of creating images of organs and tissues, fMRI looks at blood flow in the brain to detect areas of activity and so show how the brain works in real time.

The implications of this for learning are significant because for the first time we were able to identify which parts of the brain were reacting when different tasks were being performed. For example, we know that the cerebrum which is the largest part of the brain performs higher functions such as interpreting touch, vision, hearing, speech, emotions etc.

Brain plasticity

But it is the next discovery that is far more interesting from a learning perspective. For many years the common belief was that brain functionality (intelligence) was to a certain extent hard wired, largely genetic, with a fixed number of neurons. It probably didn’t help that the computer gave us a simile for how the brain worked which was misleading.

That all changed when it became possible to observe the brain and watch how it responded to what it saw and was asked to do. What this showed was that the brain has the ability to generate new cells, a process called Neurogenesis.

Click here to listen to neuroscientist Sandrine Thuret explain how humans can generate new brain cells i.e. Neurogenesis.

This may make sense for children given the basic brain functionality when a child is born, something must be happening to turn them into caring and thoughtful adults. In fact, by adolescence the brain has produced so many synapse, the connections between cells, they have to be cut back or pruned. Hence the term synaptic pruning.  What was perhaps more of a surprise was that growing new brain cells was not just something children could do, adults were able to do it as well.

The classic example is the evidence by Professor Eleanor Maguire from the Wellcome Trust Centre and colleague Dr Katherine Woollett who followed a group of 79 trainee taxi drivers and 31 controls (non-taxi drivers). Their research showed that London taxi drivers developed a greater volume of grey matter i.e.  cell development, three to four years after passing “the knowledge”  when compared to the control group.

Learning about learning

This may leave you thinking, all very interesting but what does it mean for me as a student?

In the same way that people can develop a growth mindset, bringing it within your control, you can do the same with your academic performance. Just because you don’t understand something or pick it up very quickly doesn’t mean that you won’t be able to. This is not to say that some people are not “brighter” than others, it is estimated that around 50%/60% of your intelligence is genetic, but that’s on the assumption your brain cannot change, and what this proves is it can.

And here is one last interesting observation, knowing how the brain works can actually help rewire it. There is evidence that students who know more about how they learn, (meta cognition) will naturally reflect on what they are doing when they are learning which in turn will help grow new cells, how good is that.