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Writer's pictureNathan Belcher

That’s How Learning Works?!?! A Comprehensive Model for Understanding the Learning Process

Updated: Oct 25

A visual representation for the learning process through Belcher's "Model for Learning"
Belcher’s "Model for Learning" [Image by Belcher]

Learning happens throughout life.

From the moment we are alive to our final days, the way we learn shapes who we are. Our experiences, abilities, and understanding of the world come from the way we learn, leading us down dark paths or into beautiful light.

Although learning is incredibly important, most people go through life without understanding the general and specific principles in the learning process. Traditional schooling typically focuses on the knowledge and skills for specific content, making students do “work” on a series of tasks. The principles in the learning process are rarely discussed; a learner must do outside research and thinking to understand the principles in the learning process.

Instead of neglecting the principles in the learning process, we need to make the learning process widely shared and known. Every person in the world should understand how to learn — both for themselves and for those they lead, coach, and teach.

This essay introduces Belcher’s Model for Learning, which offers insights for parents, leaders, coaches, teachers, and anyone fascinated by the mechanics of human learning. Whether you're a preschool teacher nurturing young minds, a corporate trainer developing professional skills, or simply someone eager to better understand the learning process, the Model for Learning provides a framework to comprehend and optimize learning.

Consistently applying the Model for Learning in your personal and professional context should result in more efficient and deeper learning — leading to enhanced learning across diverse domains and increased opportunities for success.


Why Care About the Learning Process?

Before we get into a 5,000-word discussion on the learning process, we should talk about the question in the header: “Why care about the learning process?”

Here are some possible reasons:

  • Learn a new skill: Playing the guitar, cooking a new dish, or hitting a beautiful shot
  • Get a promotion at work
  • Achieve a personal record in an event
  • Challenge yourself in many areas
  • Become a better leader for your family or team
  • Help students learn the knowledge and skills in your courses
  • Coach your players to learn technical and tactical skills
  • Create beautiful communities with people experiencing vigorous lives
  • Gain wisdom

From a very young age, I have implicitly cared about the learning process: Playing different sports from childhood through adulthood; building Legos and completing engineering tasks; discussing learning, philosophy, and theology; and, becoming a professional coach and educator. I explicitly understood my love for the learning process during my doctoral work, using the doctoral work to understand the foundations of excellent coaching and teaching. I realized that the foundations come from aligning my practices with the principles in the learning process, using these principles to create the best possible conditions for my players and students. As I shifted my coaching and teaching practices to align with the principles in the learning process, my players and students experienced more efficient and deeper learning — creating beautiful communities of learners and helping each learner become more wise.

Seeing my players and students come together into beautiful communities and experience wisdom gave us all joy. Although the players and students were not always successful, the players and students approached activities with energy and expectation — what were we going to learn today? Their energy and expectation made me want to continue growing as a coach and educator, leading to a virtuous cycle between me and the players and students.

After these experiences with my players and students, I feel an urgency to share what I know about the learning process with leaders, coaches, and educators. I believe that there is a crisis of feeling like a failure — a gnawing unease that there are missed opportunities, which leads to regret — but feeling like a failure comes from a sense that you did not act wisely and do everything that you could have at the right time.

My great hope for you is to experience the joy that comes from beautiful communities and wisdom, living the virtuous cycle of energy and growth. Changing your practices is not easy, but the payoff for aligning your practices with the principles in the learning process is well worth the effort. By applying these principles to your leading, coaching, and teaching, you can create the conditions for beautiful communities and increasing wisdom.

As you read each part, challenge yourself to relate the ideas to a specific part of your life. This practice allows you to anchor the ideas with a concrete example, which helps you learn the ideas more efficiently and at a greater depth. (I would love to hear how you are applying the ideas; please share with through The Learning Engine’s website!)
 
A note for the structure of the essay: The image below is a visual representation of Belcher’s Model for Learning, which creates the flow of this essay. I will place the image at appropriate places (so that you do not have to keep scrolling) and refer to the Model for Learning throughout the essay. Please take a moment and examine the image: What is your first reaction to the image?
A visual representation for the learning process through Belcher's "Model for Learning"
Belcher’s "Model for Learning" [Image by Belcher]

Information from the Environment — Sensing and Focusing

The Model for Learning begins with sensing and focusing. These two actions are inputs, initiating the learning process.

The body constantly processes information through the senses, sending the information to the brain through the central nervous system and other systems. Specific parts of the brain process the information and other parts of the brain select the most important and relevant parts of the information, focusing the information for use in the working memory.

By providing inputs to the brain through the senses, the process of sensing and focusing begins the learning process.

Sensing

Our bodies continuously use the senses, gathering a massive amount of information about the environment in every moment.

Through nerve cells associated with each of the five primary senses — sight, hearing, touch, taste, and smell — information is passed to the brain through the central nervous system and other systems. Specific physical characteristics of the person and environment impact the amount and quality of information that is passed to the brain, leading to a range of interpretations for the information.

Irrespective of the amount or quality of information collected by the senses, the senses begin learning the learning process.

Focusing

As our bodies collect information through the senses, our brain processes the information.

Focusing is the critical step by which we consciously direct our attention to specific aspects of the information, filtering the information to select the most relevant and important parts. The brain regions responsible for focusing are the prefrontal cortex, anterior cingulate cortex, and the parietal cortex; through chemical and electrical processes by the brain cells in these regions, information is passed from the senses to the working memory.

The sensing-and-focusing process is the foundation for learning, making focusing the gateway to learning.


Knowledge Organization — Brain Systems

A visual representation for the learning process through Belcher's "Model for Learning"
Belcher’s "Model for Learning" [Image by Belcher]

As the brain receives information from the senses and selects the information on which to focus, the brain performs two actions simultaneously:

  • One action is the chemical and electrical signals between brain cells, resulting in physical connections.
  • The other action uses conceptual models, resulting in abstract connections.

Both the physical and abstract connections are mediated through the brain’s systems, resulting in meaningful learning for a set of knowledge and skills.

Even though both the physical and abstract connections occur simultaneously, an essay is a linear set of ideas — therefore, I had to choose which connection type to discuss first. The next section will discuss the abstract connections; this section will discuss the physical connections in the brain.

(To keep the discussion from requiring years of studying neuroscience, many details will be omitted. If any explanation is grossly incorrect, please contact me to fix the explanation.)

Neurons

Brain cells are called neurons, with adult brains containing roughly 100 billion neurons. These 100 billion neurons create roughly 100 trillion connections (yes, trillion with a T!); the connections are the physical foundation for every part of life.


  • The main body is called the soma, represented in the top-right (under the word “neuron”) and bottom-left of the image.
  • An axon from one neuron attaches to another neuron, creating a connection.
  • Dendrites receive the axon connection through chemical and electrical signals.

Drawing of a neuron [Image by Christy Krames from Wikimedia Commons]

Parts of the Brain — Brain Stem, Subcortex, and Cortex


  • The most basic part of the brain is the brain stem. Located at the top of the spinal cord, the brain stem is responsible for fundamental survival functions.
  • The intermediate part of the brain is the subcortex, also called the cerebellum. Located atop the brain stem and spreading throughout the middle of the brain, the subcortex manages emotion, motivation, and connection.
  • The upper part of the brain is the cortex, also called the cerebrum. Located atop the subcortex and spreading over and around the top of the brain, the cortex gives humans our unique abilities. These abilities include abstract reasoning, reflecting on the past and planning for the future, and socializing through empathy, language, and cooperative planning — leading to both the devastating and magnificent actions that humans can do to and with each other.

Parts of the brain [Image from John Hopkins Medicine (https://www.hopkinsmedicine.org/health/conditions-and-diseases/anatomy-of-the-brain)]

Neuroplasticity — Working Memory, Long-Term Memory, Forgetting, and Learning

A visual representation for the learning process through Belcher's "Model for Learning"
Belcher’s "Model for Learning" [Image by Belcher]

One way to think about brain functions is processing and storage:
  • Working memory performs the processing, combining information from sensing-and-focusing with prior knowledge and skills from long-term memory.
  • Long-term memory is the storage, with physical connections between neurons forming the sets of knowledge and skills in your abstract conceptual models.

(Both working memory and long-term memory are distributed throughout various parts of the brain; the exact location depends on the specific knowledge or skill.)

Neuroplasticity

As your brain uses working memory and long-term memory during the learning process, the number and strength of connections between neurons changes.

These changes are known as neuroplasticity, which is a wonderfully hopeful term! Neuroplasticity means that you continue to change your brain as you learn and grow throughout your entire life

Even if you feel like you cannot learn, there is hope through neuroplasticity!

An Analogy with Roads

The strength and connections between neurons can be compared through an analogy:

  • Knowledge and skills learned weakly are like a twisting mountain road — you can get up the mountain, but the journey will be long and tiring.
  • Knowledge and skills learned strongly are like a wide, flat boulevard — movement is free and easy, with the journey happening quickly.

This analogy represents the connections in your brain for a set of knowledge and skills. The learning process causes neurons to wire and fire together, increasing the storage and retrieval strength for the set of knowledge and skills. Continuing to consider and use the set of knowledge and skills adds information, creating stronger and stronger connections between neurons.
Although the specific details vary from skill to skill, the overall pattern is consistent: Regular training leads to changes in the parts of the brain that are challenged by the training. The brain adapts to these challenges by rewiring itself in ways that increase its ability to carry out the functions required by the challenges. — K. Anders Ericsson in “Peak: Secrets from the New Science of Expertise

Forgetting

Using neuroplasticity to build strong connections between neurons is part of the learning process, but another part of the learning process is maintaining connections between neurons.

Forgetting happens when knowledge and skills are not used; the connections between neurons decrease over time. As the connections between neurons decrease, you lose access to some of the previously-learned knowledge and skills.

Although forgetting is a part of the learning process, there is good news: Because the neurons already have some (weaker) connection, the learning process happens much quicker during relearning.

Learning, from a Neuroscience Perspective

One lens to view the idea of learning is from the perspective of neuroscience, giving this definition for learning:

Learning in the process of creating, modifying, and strengthening connections between neurons.

When learning, your brain physically changes the connections between neurons. New neural pathways are formed, modified, or strengthened through neuroplasticity, changing your ability to use knowledge and skills. Continuing to strengthen the neural connections increases your performance, helping you progress from novice to intermediate to expert!


Knowledge Organization — Conceptual Models and Learning

A visual representation for the learning process through Belcher's "Model for Learning"
Belcher’s "Model for Learning" [Image by Belcher]

Now that we have discussed the physical connections in the brain systems, we will now discuss the abstract connections that lead to learning.

Schema and Conceptual Models

One major theory of learning is known as Constructivism. This theory argues that learning happens as we build — or construct! — knowledge and skills, taking small parts of the knowledge and skills and attaching the small parts into bigger and bigger parts.

The small parts of knowledge and skills are known as schema; a schema can be defined as the “basic unit of knowledge or skill that relates to any aspect of the world.”

An individual schema is a tiny slice in a part of knowledge and skills. Even if you are a novice at a certain topic, most of what you know is many individual schema combined into (slightly) larger schema. As you continue to learn the sets of knowledge and skills in the topic, your schema continually develop. By the time you are an expert in a topic, you have an incredibly high number and densely-connected network of schema stored in your long-term memory.

Sets of schema that combine are given a new name; this name is conceptual model. A conceptual model can be defined as “a set of organized schema for a concept that can be used to explain parts of the concept or predict outcomes from the concept.”

Both parts of the definition for a conceptual model are important: 

  • The conceptual model explains the schema and the relationships between the schema.
  • Using the schema and relationships between the schema, the conceptual model predicts outcomes in the imagined or real world.

By combining schema into conceptual models, you build beautiful cathedrals of knowledge and skills — deepening your understanding in every aspect of life.
Combining schema into a complex conceptual model [Image by Belcher]

Learning

Although there are many definitions for learning, my definition for learning flows from the ideas neuroplasticity, schema, and conceptual models:

Learning is the process of creating, modifying, linking, and applying conceptual models.”

Each of creating, modifying, linking, and applying conceptual models are important, helping you construct the knowledge and skills for a topic into a coherent structure.
A visual of Belcher’s definition for learning [Image by Belcher]

Belcher’s Model for Learning

I created the Model for Learning as a visual representation of this definition for learning:

  • The blue arrow and words represent creating and linking.
  • The purple arrow and words represent modifying.
  • The red arrow and words represent applying.

As you become more familiar with the knowledge and skills in a conceptual model, physical connections between neurons “store” the knowledge and skills in long-term memory. When you need to use the knowledge and skills in a conceptual model, working memory “pulls” the knowledge and skills and combines with sensing-and-focusing — giving you an application of the knowledge and skills.


Purposeful Application — Practicing and Performing

A visual representation for the learning process through Belcher's "Model for Learning"
Belcher’s "Model for Learning" [Image by Belcher]

The Model for Learning has an output of purposeful application — practicing and performing to use the knowledge and skills in your conceptual models.

By using the knowledge and skills in your conceptual models on tasks, you receive feedback on the strength and quality of your conceptual models. Did you quickly achieve success on the task? Did you achieve success, but you had to try hard? Or, did you not succeed on the task? Receiving feedback from the task is the only way to check your conceptual models; this feedback informs the direction of your next actions and continues the learning process.

Practice and performance have many different facets:

  • Reactive and responsive performance states
  • Spectrum of practice to performance
  • Organizing tasks for practice and performance

Although there are many more facets to practice and performance (which will be the subject of many future essays!), this essay will give a high-level overview of these ideas.

Reactive and Responsive Performance States

In the book Hardwiring Happiness, Rick Hanson discusses the relationship between each brain system, core need, and operating system.

Each brain-and-operating system can be in the Reactive Performance State (“going red”) or Responsive Performance State (“going green”), depending on whether or not the core need is met.
Table of information in "Hardwiring Happiness" [Modified version created by Belcher]
The Reactive Performance State (“going red”) is triggered when you are missing safety, satisfaction, or connection — which could come from physical or mental harm, lacking appropriate rewards, or being disconnected from your partner, colleagues, or peers.

  • When we are in the Reactive Performance State, life seems to be full of fear, frustration, and heartache.
  • We deal with challenging situations by closing ourselves from others, using fight-flight-freeze to get ourselves out of the situation.

The Responsive Performance State (“going green”) is created by having safety, satisfaction, and connection.

  • When we are in the Responsive Performance State, life seems to be full of peace, contentment, and love.
  • We deal with challenging situations by remaining curious and open, with a willingness to stay with the situation until we have a satisfactory ending to the situation.

Reactive and responsive performance states [Image by Belcher]

The brain’s physical connections — and conceptual models — are affected by the Reactive and Responsive Performance States, performing differently for each mode.

  • The Reactive Performance State sets off an alarm to get out of the situation, narrowing your focus to immediate details. Narrowing your focus is good for survival, but causes issues when practicing or performing.
  • In contrast, the Responsive Performance State opens and softens your focus; by opening and softening your focus, practicing and performing are much easier and more effective.

The learning process happens much better when you are in the Responsive Performance State, so the goal is to spend as much time as possible in this state during practice and performance.

Spectrum of Warm-Up, Practice, and Performance

Spectrum of Warm-Up, Practice, and Performance [Image by Belcher]

One way to think about practice and performance is on a spectrum.

  • The far left side of the spectrum is the Warm-Up, which has no stakes and low intensity.
  • Moving from left to right, the next three are part of Practice — beginning with low stakes and intensity and moving to high stakes and intensity when you “perform the practice.”
  • The two on the right side are with Performance, with “practice the performance” in a more controlled environment and the “full performance” in a fully uncontrolled environment — both of which are high stakes and intensity.

Though Warm-Up, Practice, and Performance are similar, each has their own unique characteristics.

Warm-Up

Although sometimes overlooked, the Warm-Up plays a massive role in the failure or success for practicing or performance.

The Warm-Up has two main points: Exploration and priming. The role of exploration is to do a self-check, calibrating yourself with small tasks and moving to larger tasks. Exploration also finds the end ranges of the tasks, which helps you understand your weaknesses and strengths for the upcoming tasks. The role of priming is to get yourself ready mentally, physically, emotionally, and spiritually, preparing yourself to stay in the Responsive Performance State.

Even if the Warm-Up is short, both exploration and priming help prepare you for the practice or performance session — allowing you to get the most learning and success from the session.

Practice

I define Practice with these main characteristics:

  • Focused on the knowledge and skills in a single conceptual model (or small number of conceptual models).
  • Structured sequence of tasks — using blocked, spaced, and interleaved tactics.
  • Closed and controlled environment.

By focusing on a single conceptual model with a structured sequence in a controlled environment, the learner can receive useful feedback from the task or instructor — and apply that feedback during the next task. Changing the difficulty of the task, stakes for the outcome of the task, or time-pressure to complete the task impacts the intensity of the practice, moving the practice session to the right on the spectrum. “Perform the Practice” is the highest-intensity version of practice, transforming the practice task into a similar experience as performing the task.

By varying the main characteristics with the intensity of practice, the learner can develop deeply interconnected and well-structured sets of knowledge and skills in their conceptual models — increasing the efficiency of their learning.

Performance

I define Performance with these main characteristics:

  • Focused on the knowledge and skills for a large number of conceptual models.
  • Unstructured sequence of tasks.
  • Open and complex environment.

Because performance happens through an unstructured sequence of tasks in an open and complex environment, the learner must use a large number of conceptual models. Performance is challenging because the learner can be overwhelmed in many different ways, from issues with the knowledge and skills in a single conceptual model to the dynamic interplay between the knowledge and skills in many conceptual models.

Though the intensity of the “Practice the Performance” and “Full Performance” is high for both, the stakes are lower in “Practice the Performance.” An example is an inter-squad scrimmage versus a match with another team — both have the main characteristics of a performance, but the match with another team has the highest stakes and intensity.

Organizing Tasks for Practice and Performance

To learn in the most efficient and effective way, organizing tasks for practice and performance are critically important.

Methods for Organizing Tasks

Several different methods exist for organizing tasks during individual sessions or across multiple sessions:

  • Blocked Practice — Repeating a task for many repetitions in a row.
  • Spaced Practice — Repeating a task with time between each repetition.
  • Interleaved Practice — Combining multiple tasks in a set sequence.
  • Random Practice — Randomly varying tasks or parts of a task.

To increase the efficiency and efficacy of learning, design of the task should include spaced, interleaved, and random practice. Blocked practice in small doses is reasonable (especially during the Warm-Up), but large doses of blocked practice gives an illusion of learning; the learner may have a pattern of success, but any change of the task will cause a return to failure. Using spaced, interleaved, and random practice to change the task helps the learner understand similarities and differences between the tasks, increasing the rate of learning in the medium- and long-term.

In an interesting twist, explaining the difference between the feelings of blocked practice and spaced, interleaved, and random practice is crucial for learning. Blocked practice feels really good during the session — “I can do this!” However, the gains during blocked practice fade quickly, leading to frustration and slower learning in the medium- and long-term. In contrast, using spaced, interleaved, and random practice is challenging, potentially leading to negative feelings during individual or multiple sessions. However, the gains during these sessions are stickier, leading to quicker and deeper learning in the medium- and long-term.

Feedback, Challenge, and Retrieval Practice

Although using spaced, interleaved, and random practice can be frustrating in the short-term, there are ways to keep learners engaged and upbeat about their progress:

  • Creating appropriate challenge within a single task or set of tasks.
  • Providing feedback before, during, and after tasks.
  • Leveraging retrieval practice for better conceptual models.

Creating appropriate challenge within a single task or set of tasks is crucial for the feelings of the learner, greatly helping with the emotions, leaning orientation, and motivation of the learner. During most sessions, the goal is roughly 80% success rate — if the success rate is lower, decrease the challenge; if the success rate is higher, increase the challenge. By managing challenges for the learner well, the momentum of learning goes in the positive direction!

Combined with appropriate challenge, the detail and timing of feedback helps the learner understand the failure and success for the task. Although the specifics for the details and timing of feedback vary hugely between novices, intermediates, and experts, the overarching ideas is that the learner needs some kind of feedback in a reasonable time frame. Too much detail in a short amount of time overwhelms the learner; too little detail in a long time slows the pace of learning. The sweet spot is the right amount of detail with appropriate timing, increasing the pace of learning and giving positive feelings about the learning process.

As the learner does any part of the spectrum from warm-up to a full performance, the learner is applying their conceptual models to complete tasks. The main difference between novices, intermediates, and experts is the depth and connections between conceptual models; experts have very in-depth and strong connections for the conceptual models. One way to increase the depth and connection of the conceptual models is through retrieval practice (also known as the generation effect or testing effect). With retrieval practice the learner tries to apply their conceptual models without any external prompting, then using the conceptual models for a task. The act of retrieving the conceptual models — combined with the failure or success for the task — primes the conceptual models, allowing the learner to deepen and connect the conceptual models through feedback.

By attending to the performance states, understanding the spectrum, and organizing tasks, the efficiency and depth of learning can increase — leading to better learning outcomes!


Additional Factors that Affect Learning

A visual representation for the learning process through Belcher's "Model for Learning"
Belcher’s "Model for Learning" [Image by Belcher]

Although Belcher’s Model for Learning is a representation of the learning process, there are other factors that affect the learning process:

  • Personal Factors — Emotions, stress, curiosity, learning orientation, and motivation.
  • Organizing Factors — Autonomy, authenticity, and relevance, plus sequencing and complexity of tasks in activities
  • Social Factors — Sociability, belonging, trust, play, competition, and collaboration

Changing these factors independently or together can decrease or increase the efficiency and depth of learning, making these factors important to the learning process.

Personal Factors

Emotions, stress, curiosity, learning orientation, and motivation are labeled Personal Factors because these factors are in every individual. External events can shape each of these factors, but ultimately the factors belong to the individual.

We’ve all had experiences with both the negative and positive versions of these factors, which tie directly into the idea of the Reactive and Responsive Performance States:

  • When these factors are trending in the negative direction, we move into the Reactive Performance State (“going red”).
  • When these factors are trending in the positive direction, we move into the Responsive Performance State (“going green.”)

As leaders, coaches, and teachers, the goal is to create conditions for the learner to trend in the positive direction. Although we are not able to control these factors for an individual, the way we relate to others can positively influence these factors — leading to increased efficiency and depth of learning, plus making the learning process feel fun!

Organizing Factors

Autonomy, authenticity, relevance, and the sequencing and complexity of tasks in activities are labeled Organizing Factors; these factors relate to the organization of learning experiences by the leader, coach, or teacher.

Organizing Factors are important because the organization of learning experiences massively impacts the learner’s Personal Factors, greatly changing the efficiency and depth of learning process. Poor planning of tasks leads to a series of problems:

  • Too much complexity or challenge given too quickly overwhelms the learner, leading the learner to experience frustration and stress.
  • Poorly-sequenced tasks create confusion because the learner cannot understand the main points or details that the tasks are using, again leading the learner to experience frustration and stress.
  • Tasks that feel forced, unauthentic, and irrelevant cause the learner to ask “why,” reducing the curiosity and motivation of the learner.

In contrast, great planning increases the efficiency and depth of learning:

  • Understanding an appropriate level of complexity and challenge helps the learner stay near an 80% success rate, leading to positive emotions and continued drive to learn.
  • Well-sequenced tasks guide the learner through the main points and supporting details for the tasks, again leading to positive emotions and learning orientation. (Note: Well-sequenced tasks are especially important for novice learners because their initial learning is fragile; by creating sequencing tasks well, the novice learner will move more quickly to the intermediate stage.)
  • Tasks that allow for autonomy, are authentic to the learner, and have relevance inherently contain the “why,” increasing the curiosity and motivation of the learner.

One way to understand impact a leader, coach, or teacher will have on their learners is to look at their ability with the Organizing Factors — are the tasks slapped together, or are the tasks well-sequenced? The goals is to use well-sequenced tasks, increasing the efficiency and depth of learning.

Social Factors

Sociability, belonging, trust, play, competition, and collaboration are labeled Social Factors. Humans are a very social species, so social interactions form a fundamental part of the learning process.

Sociability and belonging work together to either push people apart or bring them together, denying or creating psychological safety. When a learner are not sociable or does not feel a sense of belonging, the learner experiences negative emotions and stress — leading to reduced learning. However, when a learner is sociable and does feel a sense of belonging, the learner experiences positive emotions and safety — leading to increased learning.

Trust and play tie together with sociability and belonging: Trust comes from feeling a sense of belonging and psychological safety, leading to playful behaviors. Trust is earned through each social interaction, with each interaction decreasing or increasing trust. As trust increases so does play, which allows the learners to share interesting perspectives and ideas. By combining these in new ways, play helps all learners increase the efficiency and depth of learning.

Competition and collaboration can happen between members of a group or between entire groups. Like the rest of the factors, both competition and collaboration can decrease or increase learning. Competition can be destructive to learning if the learner is only focused on winning at any cost, but competition can be beneficial to learning if the learner is open to the experiences within the competition. Collaboration can reduce learning if the collaboration is one-sided, with one learner doing all the tasks; however, collaboration can be beneficial if two or more learners genuinely share the tasks and leverage each other’s perspectives.

Although each person creates their own conceptual models, comparing and correcting conceptual models happens through social interactions. Attending to the Social Factors aligns with our social needs as a species, increasing the efficiency and depth of learning.


A Return to Belcher’s Model for Learning

A visual representation for the learning process through Belcher's "Model for Learning"
Belcher’s "Model for Learning" [Image by Belcher]

The goal for this essay has been to expand your understanding of the learning process through explanations and visuals, which helps use the Model for Learning in your personal and professional context.
There is much more to say about each part of the Model for Learning, though I want to add a short note about generative artificial intelligence. This essay was published in October 2024, near the rise of generative artificial intelligence. There are many opinions on the role and capabilities of generative artificial intelligence in the learning process, but I believe that the Model for Learning and generative artificial intelligence are compatible. Generative artificial intelligence can be used as a complement to the parts of the Model for Learning, helping learners build initial conceptual models, provide directed and timely feedback, and engage in purposeful application.

Whatever method you use to receive the knowledge and skills in conceptual models, consistently applying the Model for Learning in your personal and professional context should result in more efficient and deeper learning — leading to enhanced learning across diverse domains and increased opportunities for success!

 

Keep the Conversation Going

Thanks for reading the essay! I am excited to understand how you apply the ideas in the Model for Learning to your personal and professional context — please contact me with your thoughts through The Learning Engine’s website or LinkedIn!

Newsletter on learning — join the discussion!

Register for The Principles of Learning course, which goes deeper into each part of the Model for Learning (each course has the same information, but different levels of feedback):
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