Brain-Based Learning: Theory, Strategies, And Concepts

One of the strongest applications of research in psychology, neuroscience, and cognitive science is brain-based learning. It allows us to leverage research on how the brain learns in creating a new set of guiding principles for learning, teaching, training, and education.


What is Brain-Based Learning?

Brain-based learning is a paradigm of learning which addresses student learning and learning outcomes from the point of view of the human brain. It involves specific strategies for learning which are designed based on how human attention, memory, motivation, and conceptual knowledge acquisition works. Brain-based learning and teaching can optimize learning holistically.

Historically, teaching and learning is largely based on what the students, teachers, and policy-makers think. Their opinions, experiences, logical-arguments, and quasi-experiments in the classroom inform the teaching and learning process. Brain-based learning takes a different approach. The way students are motivated, the way attention works, the way memories are formed, the way information is presented, etc. become the central aspects of teaching and learning.

One example is the construal level theory which can address the question – When and how should a student focus on the minute details contained in learning materials? Intuitively, one could say that details are important for mastery and students should learn details to demonstrate proficiency. However, this blanket statement isn’t an evidence-based approach. The construal level theory shows that understanding an overview without the details can engage a larger network of concepts a student learns or is sensitized to. Understanding the essence of a certain topic can also promote creativity because capturing the essence of a concept makes the concept vague and abstract. An abstract entity links to more abstract entities and makes the learning broad as opposed to details making the learning narrow and specific.

This was just one example of how a brain-based learning approach can better inform teaching and learning.

A brain-based approach doesn’t necessarily include intelligence testing, aptitude testing, and other standardized tests. While these can sometimes yield useful information, they are not required to utilize a brain-based approach. In some corner cases, it might be necessary – when there is significant cognitive impairment, physical disability, emotional distress due to confusion about careers, etc.

This approach can be considered quite accommodating because it doesn’t discard anything that is useful or evidence-based because of superficial reasons like not falling into a particular perspective or pedagogy.

Brain-based learning strategies, theory, and concepts
Image by Gerd Altmann from Pixabay


Brain-Based Learning Goals & Outcomes:

Considering that this approach is based on what and how much we know about the human brain and it’s interaction with the environment, we can broadly define a few learning goals:

  • Maximize the learning potential of a person
  • Minimize learning losses and wasted effort
  • Hijack known mechanisms to improve skills, knowledge-base, memory, and mental flexibility
  • Create verifiable improvements in learning and make people smarter (for lack of a better word).
  • Improve the productivity of students and teachers

What it isn’t:

  • A way to improve intelligence test scores. This does not mean that brain-based learning cannot make people smarter, it only expects that as an outcome. Some of the aspects involved in intelligence such as working memory, attention, long-term memory, verbal fluency, are likely to improve due to the use of specialized techniques (see below). A core assumption is that intelligence is unique and changeable.


Brain-Based Learning: An overview

Let us now look at a few fundamentals across 3 categories.

  • Brain-Based learning theory
  • Brain-Based learning strategies
  • Brain-Based learning as a function of student’s emotions

These factors can be construed as the markers and predictors of long-term learning.

I’ve covered these concepts across various other articles in different contexts. You’ll see the links to original articles for a particular topic at relevant places. Here is a short overview of the fundamental processes involved in learning. It is an introduction to this article.


Brain-Based Learning Theory

The first thing we need to do is understand the important factors and theories which either facilitate learning or govern learning processes.

Construal Level spectrum (CL): This describes the depth at which a concept or process is construed, also known as psychological distance. At the highest construal level, a mobile phone is a communication device. At the lowest construal, it is a Samsung S8. High construal is more abstract and widespread in how it relates to other concepts. Low construal is precise and concrete. The whole spectrum is valuable in effective learning. The CL can be managed and modified. 

In this example, a communication device links to more related concepts and activates more members of the category – It can represent mobile phones, satellite phones, pagers, computers, etc. It can link to related concepts like communication strategies, pros and cons of the main communication devices, communication channels (written word, radio frequencies, vocalizations, etc.) Now, a high construal level makes this network of interlinked concepts and information more available to memory. A low-level construal, such as Samsung S8, makes it harder to link to the written word as a communication channel.

Because the brain processes information in parallel and multiple levels, the construal level theory aligns itself with the notion that the brain a)Learns with focused attention and peripheral perception (background information) and b) Simultaneously processes/creates parts of a whole and the whole (details and the big picture simultaneously).

Variance, feedback: Research shows working with small variations in content promotes global learning within a domain. For example, working on multiple similar mathematical problems is better than repeating the same type of problem. Feedback in the form of details and feedback in the form of outcome (success vs. failure) can both promote learning, but differentially.

Variation in the features of the content which needs to be learned (for example, analogous but dissimilar math problems) can help create an aggregated and flexible mental template to approach a problem. This goes for motor and fine motor learning too – dance movements, musical sequences, sports movements, etc. Minute variations in the approximate physical form can improve the learning of the movements along with generating a greater ability to improvise.

Feedback systems are closely tied-in with variations because variations allow addressing changes. Feedback based on changes creates a seamless pathway to refine learning. Here are some common types of feedback mechanisms which improve learning:

  1. Real-time monitoring of changes – movement, mental awareness, sensory inputs
  2. Outcome-based feedback – whether the outcome was right or wrong, whether the outcome can be changed by addressing variables
  3. Introspective feedback – evaluating the process in one’s mind and applying modifications or reinforcements


Sensory integration: A large amount of information is embodied with sensory components. Information from multiple senses integrates before it is perceived. This creates an opportunity to pay attention to sensory elements. They become tethers for grounding information which translates into learning. Visual and auditory data is accessible in MOOCs and other online learning resources, and tactile data can be promoted via homework. The goal here is to encourage students to seek out opportunities that involve sensory inputs. Embodied cognition (without deeming it as an answer to “what is consciousness?”) can further help organize information. When physical movement is linked to information in the mind, learning can be reinforced and conceptualized in a rich way. Movement and using the body is valuable in learning because spatial memory (the memory for locations) is a highly specialized and broad memory system which binds information together.

For example, students can line-up and physically reorder themselves to embody a chemical reaction where a person can physically represent an atom or ion. Another example is how a student can create dance postures to represent a geometric coordinate system. Think: Can the YMCA dance moves represent any set of equations?

The Transfer effect: The transfer of learning describes how learning in one area can affect learning in another area. In some cases, transfer effects occur. In some cases, they are expected but rarely varied, and in some other cases, they are weak or non-existent. Current research is yet to draw a circle around the influence of transfer effects but there is evidence to show that transfer effects occur. The near transfer effect – learning something improves and transfers to something very similar – can be more readily leveraged than the far transfer effect – learning something transfers to superficially alien and disparate contexts.

Priming: In cognitive psychology, priming describes the influence of information on the cognitive processes that act on new information. You may have played this short game. First, I’ll give you a word to say 10 times. After you say it, I’ll ask you a question. You have to respond quickly. Say “Silk” 10 times. Silk Silk Silk Silk Silk Silk Silk Silk Silk Silk. What does a cow drink?

If you answered milk, you experienced the effects of priming. The sensory nature of the word silk primed your brain to utilize that sensory nature and manipulate your answer without your awareness (basically, because milk rhymes with silk). If you didn’t fall for this, you just overcame the effects of priming. There are various types of priming where exposure to some type of information affects mental processing speed, memory, behavior, etc. Priming effects are hard to spot but they exist and strategic use of priming information can manipulate learning outcomes and solutions to problems.

Collaborative Learning: Learning isn’t isolated from social contexts and interactions. Research shows that group activities and talking to others about learning can improve learning. But, they can also reinforce misinformation. Collaboration and learning in the presence of others engage a variety of mechanisms – expectations, judgments, ego-saving-demonstrations, etc. which can promote learning. However, social interactions can also create a number of negative scenarios – fear of failure, self-esteem based negative self-evaluation, humiliation, etc. These negatives can be mitigated in some ways. For example, discussions on Reddit can be considered social and anonymity can reduce some anxiety.

Inherent thinking biases & errors: The brain has inherent tendencies to think in specific ways. These are called cognitive biases. Some biases create the tendency to assign meaning to information when it doesn’t exist or has no utility. Some biases create the tendency to selectively look for specific information. Some logical arguments are filled with errors and we can be blinded to them because they feel intuitive. There are a few pervasive biases: a) The confirmation bias – we selectively attend to and remember information which fits our preconceptions, b) The survivorship bias – we focus on information that survives because the information which didn’t survive is removed from awareness c) The conjunction fallacy – the likelihood of one independent thing happening is higher than the likelihood of two independent things but because we fail to judge if things are independent or not, we assume the opposite. Overcoming such biases improves objectivity, decision-making, evaluation, and analysis. Here is a detailed post on cognitive biases and here is one on how to overcome them.

Cognitive and Conceptual Space: At the simplest level, this area can be called the Mind’s eye or The Mind. Most people can introspect and deliberate mental activities. A subset of what one can do with the mind is utilizing cognitive and conceptual spaces. Have you ever picked up clay or wet sand to create different shapes using it? You can do this to any type of information in this conceptual space. Conceptual spaces are closely related to working memory because they allow you to manipulate information in real-time. Think of a number. Now reverse the digits. Or take a shape and rotate it. You just utilized the cognitive and conceptual space you created for that number or shape. Manipulation in this space can get complex depending on how much you manipulate. Strategic thinking is one use of conceptual spaces. Shifting attention to different aspects of an idea is another use of cognitive spaces.

The environment: Classrooms, bedrooms, and your laptop can function as learning environments. One of the essential aspects of brain-based learning is to have a safe and encouraging learning environment. Any environment which makes someone uncomfortable and unsafe is likely to prime the body to enter a fight or flight mode. That means the environment can generate or mitigate stress which is known to compromise learning. The environment also includes social aspects like ease of communication, proximity to others, etc. Social interactions are necessary for learning because of its influence on well-being, feedback, collaboration, etc.

All of the factors mentioned above are actively present in various types of learning. Together, these aspects of cognition represent an active framework of learning.


Brain-Based Learning Strategies

When students learn, there is a considerable amount of loss in effective learning. These designed brain-based strategies should allow a student to reduce this loss as well as improve the baseline learning capacity.

I’ve covered these techniques across 2 other articles on how to study efficiently. You can read those for a detailed overview in a slightly different context.


Spaced repetition, Distributed practice, and Spacing Effects: Research shows that distributing learning over time and repeating information over increasing periods strengthens memories and buffers against forgetting. For example, a group of facts can be learned in 3 minutes. They can be repeated after 10 minutes, then in 30 minutes, then in 2 hours… then in 6 days. This helps to optimize memory for recall.

Improves: Memory for facts and details

Interleaving: Interleaving is learning similar and related concepts together in parallel. If there are 3 related math problems A, B, and C, practicing variations as ABC ABC ABC BAC CAB is more helpful than spending hours on doing AAAAA BBBBBB and CCCCC. 

Improves: Memory and the relationship between similar concepts

Generative learning: Generative learning includes the act of creating art, teaching something to others, experiencing learning in real-world contexts, making blog posts, discussing on forums, etc. This reinforces learning and uncovers hidden gaps in knowledge. 

Improves: Memory, understanding, depth and breadth of learning

Retrieval practice & the testing effect: Proof of learning often comes from the ability to demonstrate learning. This includes remembering information, practice, and the deliberate act of self-validation. This does not necessarily counteract forgetting because forgetting and remembering are not opposing forces. Retrieval practice & testing reinforce existing learning and create the opportunity to accommodate new learning by exploring errors and snowballing around. Retrieval practice can reinforce memory in the context of remembering. The brain optimizes learning for memory differently than learning for recall and remembering. When it comes to applying what is learned, the ability to recall information is important.

Improves: Remembering, confidence, and test-taking capacity

Mental Models, Models, and Metaphors: Mental models are representations of ideas that engender templates of thinking – feedback loops, natural selection, kinetic energy, etc. are all real-world processes that can be mentally represented and used as templates to hold information. These templates also permit creative usage and a method of analysis. For example, natural selection processes can be applied to some AI learning algorithms which learn to optimize over generations of “adjustments.” It is possible to apply natural selection to AI because the mental model for natural selection can be repurposed. Metaphors can also function as models. Humans like narratives and analogies and they can be leveraged for improved learning. A metaphor can create an analogy between a known process and an unknown process. Once the metaphor is used, human’s abstract and understand the essence of the unknown process.

Improves: Memory, understanding, and relationships between ideas

Chunking: The act of grouping information in small & easily digestible bites, preferably with an overarching theme, is known as chunking information. Information can be chunked based on superficial attributes such as color, category, similarity, relationships, etc. Multiple chunks are easier to remember than multiple individual elements because the brain utilizes networks of information.

Improves: Memory and conceptual understanding

Mental Manipulations: This is a skill that depends on working memory and other aspects of memory where you can direct your attention deliberately. Mental manipulations involve working in the cognitive space to change the nature of the information or use it to relate it to other aspects. Simple mental manipulations are like imagining a situation without certain elements – imagining how you can play football on a field with many potholes. Some may call this pure imagination. In that case, mental manipulations are deliberate and purposeful imagination. Complex mental manipulations are similar to how Dr. Manhattan sees the universe. 8)

Improves: Depth and breadth of learning, problem-solving, critical thinking, and creativity

Meta-cognition and inquiry: Metacognition is thinking about thinking. Mental manipulations, Mental models, metaphors, etc. are all elements of meta-cognition. Inquiry is related, but not so closely. Inquiry involves asking questions, discovering answers, taking on new perspectives, updating information, snowballing around a topic, and tackling hidden assumptions and restraints. This process can help to optimize an idea and explore it with more depth.


Improves: Depth and breadth of learning, problem-solving, critical thinking, and creativity


Neurons allow humans to learn with unlimited potential. Listening to the brain is a good starting point in optimizing learning. Image by Colin Behrens from Pixabay


Learning as a function of student’s emotions and motivation

It is easy to overlook this segment of learning. We don’t need to always focus on improving cognitive abilities like attention, memory, mental simulations, mental rotations, pattern matching, analyzing concepts, hypothetical & counterfactual thinking, intelligence, verbal ability, and sensory awareness.

Sometimes, the problem is more about emotion, motivation, behavior, and mental health. Cognition and emotions aren’t disparate entities but addressing one or the other can make addressing a problem irrelevant. Think: What use is memory training if a person has no inclination or intention to use it. Addressing both in a particular context is more holistic.

Here are a few emotional/motivational learning strategies. Students can often benefit from these because they address the emotions which percolate through one’s learning space.

  1. Manage cognitive load & change construals. Cognitive load is the weight of information and the strain on processing information. Changing the effort needed to process information can either hamper or promote learning. Construal levels can also be manipulated to target learning at various levels of detail. This changes the perceived and actual effort needed in learning which can change a student’s motivation to get on board with learning. Cognitive load is known for one important application – extremely easy or extremely difficult content hampers learning. There is a sweet spot where the content is challenging enough to motivate, stimulate, and engage students to optimize their learning and memory. If the learning material is too obvious and unstimulating, making it difficult to process can improve the depth and breadth of understanding.
  2. Tolerating aversive emotions to counteract procrastination and disliked content. Read this to understand why we procrastinate and how to overcome it.
  3. Add personal meaning to learning contexts. Personal relevance promotes motivation and creates an intention to apply one’s learning in the real-world. Learning with a sense of meaning makes it easier for students. Making things relevant and relatable taps into the innate human motivation called sense-making, which enables us to conceptualize all sorts of information.
  4. Conceptual interference: Addressing thoughts like, everything we are learning is wrong, so what’s the point. This is a segway into academic inquiry where students learn to update information and think about how and why information changes over time.
  5. Coping with last-minute studies: Addressing thoughts like, “Ok, I screwed up and I don’t have time. What do I do now?”
  6. Counter myths that sustain thoughts like, “I am dumb and stupid. I don’t understand anything. What’s the point?”
  7. Use relaxation techniques and entertainment such as music & games to neutralize distress and lighten up the intense study-mood to make it more fun and enjoyable. Having fun while learning has cognitive benefits.

You can read this article for a detailed how-to overview of evidence-based emotional regulation techniques. These will help in countering a number of problems that students face which indirectly affect their performance and learning – mental health, anxiety, stress, aversion, rebellion, etc. They are also useful for teachers to combat the pressure of teaching and they can help students address a wide range of issues.

There are many other aspects of learning which I’ve left out because this can go on and on. I’d like to highlight 3 other things.

  1. The brain is plastic – it can change it’s form and neural structures up until old-age to accommodate and allow new learning. I’m speaking about neurogenesis, synaptogenesis, and synaptic plasticity. Here is an introduction.
  2. Sleep is important for the brain to function at it’s best. You compromise that, you compromise everything. Here is how sleep affects memory and learning. And here are some techniques to fall asleep faster, in case that’s difficult for you.
  3. Breaks from work & time-bound routines while enjoying the mental “space” is important to let your brain process information and consolidate learning.

That’s it for today, take this article as an introduction to brain-based learning.


For students & professionals:

Do you feel you are productive? Yes? Carry on with your day.:) No? You might be looking at productivity from an unfavorable angle because the common idea is to inculcate productive habits. But in reality, productivity involves mental health, functional fixedness, using efficient strategies, knowing where to draw the line, emotional regulation, decision making, etc. I’ve prepared an exhaustive guide on how to be productive by addressing exactly what you need from the bottom-up.


Further reading:

https://oapub.org/edu/index.php/ejes/article/view/2356

https://www.sciencedirect.com/science/article/pii/S2452315117303636

https://www.tandfonline.com/doi/abs/10.1080/03055698.2011.570004

https://eric.ed.gov/?id=ED335141

http://etec.ctlt.ubc.ca/510wiki/Brain-based_Learning

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