How the Brain Learns Fifth Edition. Other Books From Corwin and David A. Sousa. The Leadership Brain: How to Lead Today's Schools More Effectively, Learning How the Brain Learns The world is changing at an unprecedented rate and the ability to learn is the single most important capacity we can gift to. Editorial Reviews. Review. “I have found this book to be quite useful for doctoral- level students How the Brain Learns 4th Edition, Kindle Edition. by.

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How The Brain Learns Pdf

Author: David A. Sousa Pages: Publication Date Release Date ISBN: Product Group:Book [PDF] Download. 𝗣𝗗𝗙 | History It is known that brains use networks of neurons to learn and that neuroscientists are studying where different things are learned in. How the Brain. Learns: New and Exciting. Findings. ASAIHL Conference. Nanyang Technological University. Singapore. Thursday.

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Educators and neuroscientists have been trying to put this knowledge to work by transforming the information of basic and clinical neurosciences into practical insights for the classroom. In a series of special features, we will be looking at how the brain works and what this can tell us about your teaching.

First, however, it is important to remember that all learning is brain-based. Through the process of education, we are trying literally to change the brain — not the pancreas, spleen, or lungs. Indeed, education is practical neuroscience. That does not mean that every teacher needs to become a neuroscientist or memorize neurotransmitters and 50 brain areas responsible for cognition.

But it does mean that teachers can become more effective with some knowledge of how the brain senses, processes, stores, and retrieves information.

Neural System Fatigue Learning requires attention. And attention is mediated by specific parts of the brain. Yet, neural systems fatigue quickly, actually within minutes. With three to five minutes of sustained activity, neurons become "less responsive"; they need a rest not unlike your muscles when you lift weights. They can recover within minutes too, but when they are stimulated in a sustained way, they just are not as efficient. Think about the piano and the organ; if you put your finger on the organ key and hold it down it will keep making noise, but the piano key makes one short note, and keeping your finger there produces no more sound.

Neurons are like pianos, not organs.

They respond to patterned and repetitive, rather than to sustained, continuous stimulation. Why is this important for a teacher? When a child listens as you say, "George Washington was 6'4" tall," she uses one neural system call it A.


But what does it look like in the classroom? The jump from theory to practice is not always easy. Just because you understand how the brain works, does not mean you can change your teaching practice to reflect that. Both books do an excellent job of helping you create that bridge, by providing sections on application at the end of each chapter including examples from expert teachers.

The information is similar in both books, but is organized differently and approached from different perspectives.

If you were to choose one book, you might want to do it on the basis of how the book is organized. The chapters in How the Brain Learns are based on different functions of the brain and include, among others, basic brain facts, how the brain processes information, memory, retention, and learning, the power of transfer, brain organization and learning, and thinking skills and learning.

We know astrocytes monitor neurons for this information.

Similarly, they can induce neurons to fire. Therefore, astrocytes modulate neuron behavior. This could mean that calcium waves in astrocytes are our thinking mind. Neuronal activity without astrocyte processing is a simple reflex; anything more complicated might require astrocyte processing. The fact that humans have the most abundant and largest astrocytes of any animal and we are capable of creativity and imagination also lends credence to this speculation.

The resulting pattern of the combined brainwave profiles that may be productive can be identified by specialised neurons within the amygdala in the brain.

How the Brain Learns Mathematics

The amygdala is able to select productive associations of knowledge elements, ideas, concepts and concept frameworks. It is assumed in this model that the amygdala uses similar processes to identify productive outcomes from our application of the imagination to form innovative new ideas, concepts and concept frameworks.

This is a critical capability as the sensory system is constantly receiving vast quantities of disassociated sensory data and the correct data needs to be associated with what is being perceived. Creativity takes place when curiosity, external questioning, reflection internal questioning , or a particular need or opportunity causes us to interrogate our internal library of knowledge, ideas, concepts or concept frameworks.

Our interrogation can create new links between existing knowledge, ideas, concepts or concept frameworks as well as the need for new knowledge, ideas, concepts or concept frameworks.

It is quite possible that the hippocampus also has a role to play in this process.. Or rather, we get educated out if it. Assessing risk requires a good understanding of what would or could be a good outcome.

By looking at what may appear to be an unlikely outcome can sometimes yield highly creative results. Being confident, focused, open, agreeable, extrovert and optimistic are all personality traits that assist in facilitating effective creativity.

The capacity to delineate between when collaboration is an advantage and when working independently is required is also helpful. The need to find a solution to a problem within a limited timeframe tends to encourage creativity and from that, innovation can also evolve.

We are curious as learners, but through a variety of experiences that curiosity can be dampened over time. As educators we should always be encouraging curiosity by encouraging learners in the belief that they can learn and they can be creative. This may seem counterintuitive to being focused and on-task but in fact, part of being focused on developing creative solutions requires that we spend time allowing ideas to connect in different and possibly unplanned combinations.

Interrogating each change to look for the opportunity or need is a very creative practice. With change always comes opportunity and new needs. This is a critical feature and concepts in new ways and in new allowing knowledge elements combinations. Confidence and practice within each concept to combine underpin the success of this process. This process provides knowledge elements, ideas and the capacity to develop new concepts.

Once again this modular contributing to or being involved in just approach enables the vast number one concept or a single concept of ideas to be developed, stored framework but rather each is reusable.

This modular approach to thinking allows and accessed dynamically through the brain to create and store billions of the activity of the brainwaves. The speed at which creativity takes place is extraordinary, and this is because brainwaves can scan the brain looking for possible outcomes in hundredths of a second.

The amygdala and the hippocampus combine to connect knowledge, ideas and concepts and create new or possibly more complex ideas, concepts or concept frameworks in fractions of a second. Similar ideas, concepts or concept frameworks have similar brainwave profiles.

While it is possible to come up with new ideas and be creative in a conscious state, it appears that the process of creativity is far more productive when we are in a non- conscious, daydreaming state. While it is true that human beings have been learning for hundreds of thousands of years, the required rate of learning on a daily basis, out of necessity or opportunity, has skyrocketed over the last ten years.

Learning in order to know something is important, but learning in order to understand and create completely new ideas, concepts and concept frameworks is something that is deeply rewarding and a capability unique to humans.

Creating memories is a complex aspect of learning and emerging research indicates that there appears to be different memory systems for each of our four learning systems. What follows is a theoretical framework for memory. Episodic memories can be temporary, fashion, Chua had short term or long term and each type involves a anticipated the idea different set of processes and storage.

Storage of that memristors temporary and short-term memories appears to be might have epigenetic. This is a process that happens within the something to say nucleus of neurons that we described earlier. There seems to be a choice of two systems for long-term about how our memories. The first is biological memristic memory. The second possibility is that long-term! Learning, creating and remembering ideas and concepts are stored as semantic memories.

The brain does not appear to store temporary memories for this learning system. Short-term memories may be stored within astrocytic networks but this is contentious. Long-term memories may be stored in the same way or via memristic or holographic processes. Creative memories involve different combinations of episodic and semantic memories and appear to be stored via the interference of brainwaves known as stochastic resonance, or they are possibly stored holographically.

Associative memories are formed when we associate particular elements of a memory and link them to form a single memory, such as when you remember a range of memories associated with your grandmother. These complex memories also appear to be stored via the interference of brainwaves known as stochastic resonance or possibly holographically.

Following this operation the patient may lose temporary and short-term episodic memories but does not lose any long-term episodic or semantic or creative memories. This seems to imply a holographic memory system as displayed in biological memristors. How our memories are stored is contentious and this is an area of research that is going through an extensive review of late.

The table below shows some possible associations of learning systems and memory systems. If we only had one learning system then it would be more likely that each learning system would have a temporary, short-term and long-term memory progression, but this does not seem to be the case.

The structures that are responsible for managing each of our memory systems in our brain are highlighted in the diagram. Learning Learn 2 So yes, we have always been learning, but the rate of learning now necessary and the amount of learning we are doing has grown dramatically. Simply downloading a mobile phone requires you to learn how to use the camera function, send text messages, use Skype, synchronise your device with iTunes to download music, movies, video clips from YouTube, TED talks, etc.

Then you will have to download and learn how to use Evernote. All of this for half the price of the digital camera that we bought in !

Learning how to learn as efficiently as possible is now Once we can learn independently critical for everyone due to the and do so efficiently we become an volume of learning we are doing. Once autodidact and we have the most we learn how to learn efficiently and important capability for the 21st we can learn independently without needing to be told how, then learning century.

Treadwell anything becomes possible and learning anything opens up the doors to innovation and ingenuity once we have our own creativity key to open that door. Everyone has the potential and the right to gain the capability of becoming an autodidact!

Providing learners with an understanding of the Learning Process bestows them with the gift of the fishing rod rather than them needing educators to find and feed them fresh fish every day. This capability is fast becoming the focus of schooling systems across the globe. This is a critical capability as we cannot possibly know what learners will need to understand in the next five years, let alone the next 20 or 30 years.

Understanding how to learn is now the most critical outcome for schools and is fundamental to the purpose and the mission that underpins the vision of all schools. This model for how the brain learns proposes four discrete thinking systems: Perceiving and storing sensory data. Learning and remembering knowledge via rote.

Developing ideas, concepts and concept frameworks. Applying knowledge, ideas and concepts creatively to develop new knowledge, ideas and concepts that are innovative and ingenious. Learning knowledge is essential in the Learning Process, but it is not the end point of learning. It is not possible to develop the capacity for reading and writing without learning the sounds and shapes of 26 letters and then developing a vocabulary of words so that you can communicate effectively.

Every idea and concept that we have ever developed sprang from a body of knowledge, no matter how small. Knowledge is the raw material that ideas, concepts and concept frameworks are crafted from!

Treadwell One of the challenges with current pedagogical practice in schools is that the body of knowledge that learners are expected to know and remember is expanding exponentially. This is due to reading and writing being based on a lot of rote learning of letters, sounds, words, grammar, etc. However, you did not necessarily struggle to learn to set up your mobile phone, download apps or take wonderful photos.

Despite what you might have been told, everyone is intelligent and that includes you! Almost everybody learns to drive a car and passes the practical test, regardless of how intelligent school may have judged them to be.

How Julie's Brain Learns

Driving is quite possibly the most complex cognitive task we ever attempt. How is it possible that everyone passes that test, even if it may take more than one attempt?

The answer to this question provides an explanation for why some subjects in school are easy and some are hard to learn. If we separate out subjects in school systems into the hard subjects and soft subjects we discover some similarities in the way each of these two groups of subjects are taught.

Soft subjects start off with a small amount of knowledge and then the learner is quickly presented with the opportunity to practice what they have just learned to build underlying ideas and concepts. Hard subjects on the other hand begin with large bodies of knowledge and then at the conclusion of the topic, having learned and remembered all that knowledge, the learner may be given one or two examples of applications for that knowledge.

The reason why soft subjects are easy to learn is because they leverage the way in which the brain learns most efficiently. This approach focuses on introducing a small amount of knowledge and then applying that to create ideas and concepts. New knowledge is added as it is required, rather than just in case it may be needed in the future. Hard subjects History Mathematics Science English Computing Soft subjects Drama Social Science Art Music40 Technology41 The exception to this idea is reading and writing, as these tasks require a massive amount of front-loaded knowledge before ideas and concepts can be developed.

An example may help. We all apply algebraic processes every day, every few minutes, we just do not realise we are doing it. To understand algebra what we need is an appropriate prompt: When you get up in the morning, there are a number of things that determine what clothes you wear on any given day.

We refer to these things that affect our decision-making as variables, because they can change from day to day. There are a number of variables that have to be taken into account before you decide what clothes you will wear on any particular day.

Those variables things that could change and influence your decision of what you would wear could include: How am I feeling? How important is looking fashionable? What clothes do I have available? Which clothes are clean? What is the temperature outside and in my place of work? What accessories will highlight what I wear? What particular clothes are appropriate to my position? What are the expectations of my peers and bosses?

Which items match? What clothes need ironing! Each of these variables will have a different level of importance for each of us. If we ask someone: Now we have a baseline for judging the relative importance of the other variables. We can apply the same thinking to each of the variables until we end up with the equation for what clothes they will wear today: Everyone can science teaching should understand this type of algebra; we apply this degenerate into the process for the trips we plan, the meals we cook, accumulation of the choice of book we download, the car we download, disconnected facts and the people we like and take on as friends, who we unexplained formulae, sit next to on the bus, and we compute these which burden the algebraic equations very quickly.

We are essentially walking algebra experts. Everett, Once concrete variables are understood, learners can begin to come to terms with abstract variables and make sense of them. The same applies to the concept of number and measurement and for every mathematical concept, but these must be introduced with minimal pre- loaded knowledge and that knowledge is immediately applied to contexts that the learner can relate to.

The task of all educators is to keep the concepts at the forefront of their mission and to not burden learners with knowledge just in case they may need it some time in the future. Smartphones are far better at remembering things like that — let the mind play with concepts as that is what it is designed to do.

Mathematics is absolutely critical in life. In school getting the exact answer is very important, whereas in life it is far more important to be able to approximate and that requires the ability to predict. The extraordinary thing about learning a concept is that once you have understood it you can predict what the discount will approximately be for anything. Understanding the concept of algebra and the concept of number are fundamental to life in the complex world of decision-making that we inhabit.

It is time we started evaluating and looking at how we teach what is worth learning. Educating for understanding allows us to focus on learning to learn rather than remembering scores of inane facts or processes that neither the learners nor we will remember after the test.

What is important to work out is what knowledge we do need to remember and make sure the learners in our schools and classrooms have this knowledge. To be worthy of having to remember some knowledge we need to be quite sure it underpins ideas and concepts that are essential for learners to understand.

This must be the gatekeeper for establishing what knowledge learners must learn. The randomness of learning inane facts about Aztecs, the size of planets and photosynthesis at 10 years old has to be removed from the curriculum. Buried within this notion is one of our greatest challenges as educators — we have to revise the very notion of what we consider intelligence to be.

Intelligence in the previous learning paradigm was all about how much we could remember and then recall in any given test.

How the Brain Learns Best | Scholastic

Intelligence now is being redefined far more in line with having the capacity to be able to learn and unlearn and to be able to do this as efficiently and effectively as possible.

Mathematics may well underpin the exotic and beautiful symmetry of the snowflake and while it is a good example of the application of symmetry, how much more powerful it could be as a great prompt coupled with the question: Learning is far more complex than ever imagined, with four learning systems that each have a degree of autonomy but work together in an integrated manner.

Of the four learning systems, our ability to learn via rote is the poorest and most dependent on our genetic inheritance. Unfortunately, emergent reading and writing capability requires large amounts of rote learning and there is no way around this. However, with new technologies we can now offer those learners who struggle to remember large amounts of information via rote- learning processes the opportunity to record their understanding using video rather than having to record it in a written format.

Likewise, we can now also offer learners the opportunity to watch and listen to a video rather than having to read large amounts of text. Through the application of the learning process, learning becomes far more equitable for all learners.

The challenge here is ensuring that educators have a thorough understanding of the underlying concepts and concept frameworks that form the foundation of each of the disciplines. Framing learning intentions in terms of concepts rather than contexts fundamentally changes the way in which learning has been approached over the last 50 years.

This approach also changes the standardised unit length that is allocated to each thematic unit taught. Learning can now be personalised, with each learner progressing through the different levels of understanding at their own pace. The shift to far greater learner agency responsibility over their learning and far greater responsibility for their own assessment and the assessment of their peers changes the role of the educator. The role of the educator now requires a greater level of sophistication and understanding of the learning process and the disciplines, competencies and literacies that they are responsible for.

Questions to reflect on: How does this new approach to learning resonate with your 'gut feeling' as an educator? What are your immediate concerns as you contemplate the implementation of the changes that are now required?

What are your immediate resourcing issues? What are the implications for the technological environment that is now required in order to implement this approach to learning? How do you feel about the notion of teachers becoming educator-learners? How do you think these changes will affect community perceptions and the status of teachers within your community? Do you think this revised approach to learning will better prepare learners for the world that they will live, work and play in?

Is the investment of your time and energy in making these changes worthwhile considering your answers to the above? What do you consider to be the greatest challenges in making these series of changes over the next three years? Section 2 The Learning Process! The brain is a learning instrument — this is what it is primarily designed to do.

Developing a model for how the brain learns provides the first step in being able to define what the optimal Learning Process should look like. Section 1 provided an overview of the emerging model for how the brain learns and now we can unpack the Learning Process stage by stage.

The Learning Process will require iterations and additional research to refine it further but it provides a framework that we can begin trialling in schools. This resource represents a first draft of the emerging model for how the brain learns and a framework for the Learning Process that allows us to optimise learning. Learning is central to our profession as educators and it is extraordinary how little science we have access to that informs us about how the brain learns.

This is partly due to how little neuroscientific effort has been applied to what has been a predominantly sociological based approach to learning. When asked, it not uncommon for most educators to struggle to provide a coherent theoretical framework for how learning takes place or how it could be improved. The foundation for the Learning Process provides educators with a framework to enable learners to take increasing agency over their learning.

The framework must have an underlying rigour and discipline surrounding the acquisition of knowledge and the subsequent development of ideas, concepts and concept frameworks. As an experienced learner we then ask and apply additional clever questions and the solutions to those questions are generated through the design and research processes.

By applying further clever questioning and interrogation of our knowledge it is possible to establish the relationships between two or more events that change over time variables to form a new idea. For example, we may make an observation that as it gets cooler as autumn approaches a variable , a particular tree outside the classroom loses its leaves another variable.

We develop the idea that this seems to happen at the same time each year. Now we have an idea that this tree loses its leaves at a particular time of each year. We can now make a prediction for this particular tree. A prediction is based on a pattern that repeats and is far more reliable than a guess! However, knowing this for one tree does not make it true for all trees.

By studying more about trees we realise that only some trees lose their leaves. Further research soon uncovers that trees can be deciduous or evergreen with only deciduous trees losing their leaves each autumn. Additional knowledge is then needed regarding how to tell the two types of trees apart. Once this knowledge is discovered we are able to form a general concept for all trees.

Deciduous trees originally lived in very cold climates or in tropical climates and lose their leaves as a survival mechanism to conserve water and energy, growing new leaves when the sun returns in spring or when moisture returns in the wet season.

We are now starting to develop a general concept about trees and why some lose their leaves. Understanding a concept allows us to make more complex predictions for almost any type of tree context. A concept such as this can then be linked to other concepts such as gathering and storing food. This concept may also be part of the concept framework of how plants and animals generally conserve their resources. We may then come up with the innovative idea that we could plant deciduous trees for shade in the summer and they would allow the light through into our homes in the winter.

An ingenious application may then be developing some guards for the house rain gutters that stop the leaves blocking the water flowing off the roof and being taken to the storm-water system. Two additional levels of complexity are presented later in this resource. Above all, the Learning Process requires creative educators to stimulate curiosity through the imaginative and creative application of prompts that in turn encourage the learner s to want to learn.

The Learning Process Stage 1: Once we understand the Learning Process and understand how to learn more efficiently and effectively we can apply that process to any learning situation — anything we would ever want to learn — AND we can then apply that understanding creatively or imaginatively to be innovative or ingenious; or NOT!

The Learning Process is made up of developmental stages but these are not necessarily locked into a set of predictable linear processes. So what does the Learning Process look like? The first step in the Learning Process is the creation of knowledge. The naturally occurring learning experiences that happen spontaneously for billions of us Prompts every day are almost always initiated by a can include: That emotion - objects - events engages our curiosity and that is expressed - YouTube clips in the form of asking questions of self or - news items others.

That feeling of intrigue born of our - ePals. Applying the Learning Process - speakers means adjusting our present pedagogy to - virtual worlds replicate the natural Learning Process as - images much as possible. A prompt creates within us a range of emotions such as amazement, awe, surprise or even anger, and these in turn can initiate our sense of curiosity. It is this notion of curiosity that drives our desire to better understand what it is that we have experienced.

That's the only thing that never fails. You may grow old and trembling in your anatomies, you may lie awake at night listening to the disorder of your veins, you may miss your only love, you may see the world about you devastated by evil lunatics, or know your honour trampled in the sewers of baser minds. There is only one thing for it then — to learn. Learn why the world wags and what wags it.

That is the only thing, which the mind can never exhaust, never alienate, never be tortured by, never fear or distrust, and never dream of regretting. White, The Once and Future King! It is this process that drives us to want to learn. By leveraging this very natural curiosity to want to learn, all learners can be inspired to learn and learn far more efficiently when they are inspired to want to learn. Curiosity is unusual in that it is not an emotion or a feeling, but rather it is an innate instinct that is genetically embedded within us and one that we have little control over.

Levels of curiosity can vary from person to person and context to context. The senses tell our brain about our needs, such as hunger, as well as a sense of balance or how warm or cold we may be. The senses gather data about the world outside of our bodies that allows the brain to make informed decisions about how we should dress, who to spend time with and what music we will listen to.

A structure in the brain called the amygdala mediates all this data and associates each data element with other data elements that are associated with the same event being perceived.

This is an extraordinarily complex operation and without it we could not make sense of our world. Gathering and associating data from our senses is an extremely important learning system, which we are completely reliant on.

In order to replicate the natural prompts that initiate learning, educators need to become increasingly creative in developing prompts that stimulate learning. Once we have experienced the prompt we then automatically ask questions and by asking simple, rich, open, fertile, high-order or Socratic questions of self or each other our learning is driven deeper.

What we feel when we are learning has a lot to do with how well we engage in the learning and how quickly we understand what we are attempting to learn. In this first stage of the Learning Process, the feeling of emotion releases hormones in our brain.

Some astrocytes have hormone sensors on their surface and in this model, particular combinations of hormones prompt astrocytes to map, remember and automate ideas and concepts. How we feel due to the hormones released in our brain , tells our brain how quickly we should learn and remember the underlying concepts behind what is being experienced.

In this emerging model, the release of hormones tells our brain how important the experience is and how quickly and permanently the concept should be mapped. When it comes to learning ideas and concepts, the speed of learning is determined by what combination of hormones are being released in our brain.

This does not appear to be the case for learning by rote, as neurons on their own do not appear to have the cellular mechanisms to sense the presence of hormones. Everyone wants to learn, as we are all innately curious, but teachers can sometimes steal the opportunity from the learner to be amazed by giving them the answer or giving them a textbook with the answer in it. We must ask the learner appropriate questions so they can find and own the answers!

An example: Stage 1: Knowing the address of the hotel will allow you to get a taxi to the exact address.

This knowledge is very specific to where you will be holidaying. In this notion of a Learning Process we define knowledge as factual information that you either learn through active or passive research via your senses. Facts are highly contextual. It is very cold in Iceland in the winter if you are standing outside on a glacier without thermal protection and there is no artificial heat source nearby. Knowledge really is very contextual because you could be very hot in Iceland if you happened to be sitting in a sauna.

How the Brain Learns_ 5th Edition.pdf

Learners, and that would be all of us, rarely want answers given to us. We like finding answers for ourselves. Sometimes we like to do that on our own and sometimes we prefer to carry out the searching for answers collaboratively, learning with our friends or colleagues.

Even the most reluctant of young people love learning, when it is done on their terms. That is so cool! Compared to this, the learning that takes place in the traditional school setting is often dominated by content that has to be remembered and this can be tedious, to say the least. Sadly, because we struggle to remember lots of content for a 1—2 hour exam, many learners think that they are not very intelligent, and this is simply not the case. In this new approach to learning, well-designed prompts inspire and create an emotional response and subsequently learners have questions they want answers to.

This happens very quickly and the culmination of these elements initiates our curiosity. Curiosity drives learners to discover the initial knowledge required to find answers to their questions. When educators prompt learning using a range of media and processes, the learner chooses to learn and they own the subsequent learning journey. Ownership of the Learning Process is what we refer to as agency and this is one of the greatest drivers of personalised learning.

The video clip here is a good example of how a prompt can be used to stimulate a learners curiosity to work out whether it is possible to do this prank, or whether this is a photo-shopped fake?

One of the reasons that many learners find learning difficult is that educators have tended to use a thematic approach to constructing units of work. Topics such as famous mathematicians, transportation, plants, Aztecs, healthy eating, volcanoes, etc.

Educators ask learners to work through these units of work that inadvertently include numerous ideas, concepts and concept frameworks that are not clearly articulated or worked through using an appropriate developmental sequence.

At the beginning of the unit of work, the learner will be expected to remember a substantial amount of content just in case it might be needed some time later. Most of that content will be learned by rote. Following the prompt, the learner may not have much knowledge about the topic they have been prompted to learn about, but their curiosity will drive them to want to discover and learn that knowledge.

The important distinction here is that knowledge needs to be researched and discovered. Knowledge requires the context of the prompt to be meaningful. If we are looking for knowledge because we want to understand our world, then the excitement driven by our curiosity increases our engagement, our level of persistence and also our willingness to learn from each other.

These dispositional characteristics associated with learning are critical while we are developing sufficient knowledge to be able to create an idea about what is being researched. This may quickly lead to the development of a concept surrounding what we have observed, researched and discussed. The competencies underpin this phase of the Learning Process, enabling it to be successful. The ability to think and question, develop a language for learning, collaborate, connect and reflect, manage self and, importantly, come to terms with our own identity are all foundational to successfully carrying out the research and being able to distil and synthesise that research into new ideas and concepts.

The point is to understand. The prompt and the resulting curiosity encourage us to learn sufficient knowledge to get us started with our thinking in order to obtain some initial and quite simple answers to our questions. Within that process we build the knowledge we require. Introducing too many new words, facts and labelled diagrams simply overwhelms most learners. The rationale for front-loading lots of knowledge via thematic based units is purely historical and it needs to be challenged.

Keeping the amount of front-loaded knowledge to an absolute minimum enables most learners to maintain their engagement. Remembering all that knowledge via rote requires our weakest learning system and associated poor memory systems. As a learner that has agency over our Learning Process we will identify what knowledge is required to develop our initial ideas.

As learners, we will return to this phase of the Learning Process often, as and when we need to develop additional knowledge to build whatever new understanding we require, to the depth that we require. We will do this out of our desire to understand our world. The drive to understand our world is driven by our curiosity, and to satisfy that we will need to steadily increase the depth of our body of knowledge.

It is not possible to build understanding without first developing an initial body of knowledge. The difficulty in the past has been that the body of knowledge educators introduced was overwhelming rather than being helpful, and unfortunately textbooks encourage this knowledge acquisition just in case it may be required.

The important pedagogical shift here is allowing the learner to develop knowledge as it is required, with them taking increasing ownership of this process as they develop the necessary learner dispositions via the competencies. Ideas are created when we realise that when something changes or varies a variable , this can cause other things to change in a particular way within a specific context. A good example of a variable would be weather forecasting, and if the weather forecaster predicts rain for the week when I am on holiday then I may feel grumpy.

The weather is one variable and my mood is another one. In this context my mood is dependent on the weather. From my knowledge of weather and mood I can form a connection between the two variables and an idea can form.

The idea I now have is that this upcoming holiday may not be as exciting as I had hoped because the weather is forecast to be bad.


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