What did you learn today?
For some, this question is terrifying — but for others, this question is joyful. Learning sparks an array of emotions in people: Wonderful or horrific memories of teachers or events in school; lessons learned from failure or success; a feeling that they are missing something by not learning enough; or, feeling a sense of purpose through their learning. Humans have a deep-rooted desire to learn and grow, becoming an expert in some field. However, we are often at a loss for how to learn; this lack of understanding negatively affects our ability to learn. By understanding the basics of how to learn, you can integrate your current thinking with the lessons from your life experiences — leading to progress for your learning goals.
Organizing Information
Learning happens throughout life. From the moment we are born, we are constantly gathering information and making sense of the information. As we make sense of the information, we organize the information and use the information to produce predictions about the world. If the predictions are correct, we confirm the organization and information; however, if the predictions are partially or completely wrong, we must update the organization or information.
The fundamental idea for how we organize information comes from Jean Piaget’s learning theory of Cognitive Constructivism (pages 5-6). Piaget proposed that humans construct their own understanding of the world, creating a schema for everything they learn; a schema is defined as the “basic unit of knowledge that relates to all aspects of the world.” Related schemata (the plural of schema) can be combined into a conceptual model. A model for a concept can be defined as “a set of organized schemata for a concept that can be used to explain parts of the concept or predict outcomes from the concept” [1]. Both parts of the usage in a model for a concept are important: The model for a concept explains the schemata and the relationships between the schemata; using the schemata and relationships between the schemata, the model for a concept for the concept predicts outcomes in the imagined or real world.
In this definition of a model for a concept, the word concept is deliberatively vague. A concept can be simple or complex, exact or inexact, embodied or an abstract idea. There are many types of concepts, including these examples:
Physical actions — shooting a basketball, performing a julienne cut, executing a grand jeté;
Information about the physical world — forces, chemical reactions, microbiology [2];
Beliefs about “the truth” — Bayesian updating, base rate failures, the availability heuristic;
Decision-making — inversion, sensitivity to fairness, commitment and consistency bias [3].
No matter how simple or complex a concept may be, the concept can be broken into individual schema — therefore, the process of learning involves creating, modifying, and linking individual schemata into a model for a concept.
Learning
Although there are many definitions of learning, let’s use this definition: Learning is the process of creating, modifying, linking, and applying models for concepts. This definition of learning flows from our definition of a model for a concept: All pieces of information our bodies and brains collect and process are encoded in models for concepts; these pieces of information either create a new model for a concept, modify an existing model for a concept, link multiple models for concepts, or cause an application of a model for a concept. Researchers have found two main ways that we learn: The declarative learning system (learning fast) and the procedural learning system (learning slow) [4]. Both learning systems are important for learning; the learning systems can be leveraged — individually or together — to increase the rate of your learning and the strength of your learning.
Declarative Learning System — Learning Fast
The declarative learning system requires focus to use — but by focusing, you can learn fast. A simplified process of the declarative learning system works in four parts: Your senses take in information; working memory focuses the information; the hippocampus indexes the information; and, the neocortex stores the information by updating an existing model for a concept or creating a new model for a concept. The first time you focus on new information, your brain creates weak connections that result in an unorganized and weak model for a concept. As you continue to focus on the information through further thinking and practice, your brain creates stronger connections — resulting in an organized and strong model for a concept. More thinking and practice using the strong model for a concept continues the process of learning; the model for a concept will be modified, linked with other models for concepts, and applied to unique situations.
The initial type of practice for the declarative learning system is blocked practice. In blocked practice, you do the same activity repeatedly for some time; repeating the activity allows the brain to make the initial model for a concept, then strengthen the model for a concept. For example, consider a beginning soccer player learning to make a simple 10-yard pass. The initial work is with the proper technique: The angle of the foot, how to swing the leg, and where to strike the ball. Beginning players work with this technique over and over, ingraining the feeling of how to kick the ball for a 10-yard pass.
After reaching some skill with a 10-yard pass, blocked practice no longer is effective. Instead, the player should switch to spaced practice. Spaced practice — also known as spaced repetition — breaks the practice into shorter segments with time between the segments. Continuing with the soccer example for blocked and spaced practice: Blocked practice would be one 10-minute passing session; however, spaced practice would give players two 5-minute passing sessions with time between the two passing sessions.
The declarative learning system is how we “learn fast,” focusing our senses to take in information, make sense of information, and store information in models for concepts. As you practice with blocked and spaced practice, your models for concepts move from weak to strong — giving robust learning, quickly.
Procedural Learning System — Learning Slow
The procedural learning system requires large amounts of practice to become effective, making learning slow. Information is taken in by your senses, but the information is processed through the basal ganglia (and associated structures) then stored in the neocortex by updating an existing model for a concept or creating a new model for a concept. After enough practice to solidify the model for a concept, the procedural learning system can use the model for a concept extremely quickly — to the point where the action or thought tied to a specific model for a concept seems automatic.
This quick use of models for concepts is seen in experts in any field; take, for example, a master chef. As the master chef produces a dish, they are using knives, mixing ingredients, and performing many other tasks — but these tasks are not actually the focus of the master chef’s thinking! The master chef is thinking about the flavor profiles of individual ingredients and ways to create dishes; the models for concepts tied to the physical actions of cooking have been practiced repeatedly and embedded in memory through the procedural learning system, leading to quick use of the models for concepts. A novice chef does not have enough practice with the models for concepts tied to the physical actions of cooking, so the novice chef struggles to use a knife or mixer without conscious thought. As the novice chef develops their models for concepts of cooking, the procedural learning system helps the chef solidify their models for concepts and use the models for concepts more quickly.
The practice required for the procedural learning system is known as interleaved practice. Interleaved practice takes several parts for a concept and mixes the parts together; the same part is never practiced back-to-back. For example, consider four parts for a concept: A, B, C, and D. Each of the four parts will be practiced four times:
Blocked Practice: AAAA BBBB CCCC DDDD
Interleaved Practice (Simple): ABCD ABCD ABCD ABCD
Interleaved Practice (Complex): ABCD BCDA CDAB DABC
Interleaved practice can range from a simple, repeating pattern to a complex, repeating pattern, or be completely random; however, the point of interleaved practice is to have a different part for the concept practiced each time.
The procedural learning system is extremely good at pattern-matching, so interleaved practice allows you to create a model for a concept in many different ways. By comparing different ways to explain or predict outcomes from the model for a concept — especially through the use of examples and non-examples — you create, modify, link, and apply a model for a concept. After enough practice using the model for a concept becomes automatic, allowing you to effortlessly complete simpler tasks and focus on more complex topics.
Connecting Learning Fast and Learning Slow
Although the declarative learning system and procedural learning system use different brain structures to store information in the neocortex as models for a concepts, the commonality between the two systems is practice. Without practice, there is no learning — practice makes you think about a model for a concept’s information and skills, using the model for a concept to explain the concept or predict an outcome.
To fully reap the benefits of practice — especially after reaching a reasonable level of skill for a complex topic — the practice must be structured in a specific way:
Practice is outside your comfort zone with near-maximal effort, using full concentration and conscious action;
Practice applying the model for a concept is spaced and interleaved with related models for concepts; and,
Practice uses self-testing at regular intervals to determine your ability with the model for a concept and allow time for reflection on learning.
Astute readers will note these are the hallmarks from Anders Ericsson’s work on the idea of deliberate practice. Although Ericsson did not discuss deliberate practice in relation to the learning systems in his work, deliberate practice is fully aligned with the ideas of the declarative and procedural learning systems [5].
The declarative learning system and procedural learning systems share another similarity: Both systems take in information with your senses, then create, modify, link, or apply a model for a concept. The model for a concept — especially a complex concept — includes information and skills that have been learned through both systems, creating a strong model for a concept. After learning enough about a topic and creating strong models for concepts, take time to think about the structure of the models for concepts and consolidate important models for the topic. This process of reflection and consolidation organizes the models for concepts in topic, giving you stronger connections between the models for concepts of the topic.
Summary
Learning is the process of creating, modifying, linking, and applying models for concepts; models for concepts are created by connecting related schemata of a topic. The brain uses two main systems to learn: The declarative learning system and the procedural learning system. The declarative learning system requires blocked and spaced practice to create and strengthen the model for a conept; models for concepts can be formed quickly, giving you “learning fast.” The procedural learning system requires interleaved practice with different patterns to create and strengthen the model for a concept; models for concepts take a large amount of practice (“learning slow”), but strong models for concepts can be used very quickly. Using both learning systems requires practice with the models for concepts. In addition, both learning systems need a time of reflection and consolidation to organize and strengthen models for concepts. These are the basics of how to learn; with this model for the concept of learning you can integrate your current thinking with the lessons from your life experiences — leading to progress for your learning goals!
Next Actions
Now that you know about models for concepts, learning fast, and learning slow, what will you do with this information?
If you are a student in a discipline with established models for concepts (science, mathematics, languages, and others), your goal should be to create and link information about the established models for concepts into your personal models for concepts.
If you are an athlete or performer, your goal should be to create strong models for concepts of the technical skills and tactical ideas to succeed in your sport or performing art.
If you are a professional in a field with subjective performance measures, your goal should be to determine your definition of “success,” then find others who have met that definition of success. Study their work and generate models for concepts, then test those models for concepts against your definition of success. As you test the models for concepts, consolidate and reflect on the models for concepts — modifying and linking models for concepts as you progress in your understanding of the topic.
Notes
[1] There are other definitions of models for concepts, including these definitions:
“Private construction of a narrative in the mind of an individual” (Hestenes)
“An explanation of someone’s thought process about how something works in the real world. It is a representation of the surrounding world, the relationships between its various parts and a person’s intuitive perception about his or her own acts and their consequences.” (Wikipedia)
“A [mental] model is a simplified representation of the most important parts of some problem domain that is good enough to enable problem solving.” (Wilson)
Although these definitions are useful, I prefer the definition from this article.
[2] If you are a teacher, the American Modeling Teachers Association has an entire set of curricula based around models. This curricula aligns well with the Next Generation Science Standards and Advanced Placement science courses; using the ideas of Modeling Instruction is a wonderful way to teach!
[3] The ideas of “Beliefs about ‘the truth’” and “Decision-making” come from Chin’s work.
[4] Ideas about the declarative and procedural learning systems come from the book Uncommon Sense Teaching by Barbara Oakley, Beth Rogowsky, and Terrence Sejnowski.
[5] One of the major criticisms of Ericsson’s work is the difficulty of applying deliberate practice to complex and non-repeating topics. This is a reasonable criticism, but the criticism misses the point: The term deliberate practice has a tight set of criteria, which do NOT include any field or topic with subjective performance measures. Many everyday fields and topics — both simple or complex, repeating or non-repeating — have subjective performance measures, so these fields and topics do not fall within the technical criteria for using deliberate practice. The criteria for deliberate practice are the following:
The field must have a highly developed set of skills, with objective performance measures for what is “the best.” [Example: The world record for males swimming the 100-meter breast stroke.]
The learner needs a coach to guide them on the development of skills and sub-skills. [Example: A swimming coach for the swimmer, guiding the swimmer on breathing and body technique.]
The learner must use the principles of deliberate practice to get better relative to their prior performance and the objective measures of “the best.” [Example: The swimmer improved from 1:05.25 to 1:03.89 in one week; the world record for males swimming the 100-meter breast stroke is 55.28 seconds.]
Many of the studies using deliberate practice are in topics with repeatable skills and well-defined parameters, focusing on a particular skill or idea within these fields or topics. However, what happens when the field or topic has subjective performance measures? Ericsson recommends “getting as close to deliberate practice as you can. … In practice that often boils down to purposeful practice with a few extra steps: First, identify the expert performers, then figure out what they do that makes them so good, then come up with training techniques that allow you to do it, too” (2016, p. 103). Even though the field or topic has subjective performance measures, you can still create a robust model for a concept — allowing you to increase your performance relative to yourself.
References
Chin, C. (2018, December 31). Putting mental models to practice, part 2: An introduction to rationality. Commonplace - The Commoncog Blog. Retrieved February 16, 2022, from https://commoncog.com/blog/putting-mental-models-to-practice-part-2-introduction-to-rationality/
Chin, C. (2019, October 29). The mental model FAQ. Commonplace - The Commoncog Blog. Retrieved February 16, 2022, from https://commoncog.com/blog/the-mental-model-faq/
Ericsson, A. (2017). Peak. Vintage.
Oakley, B., Rogowsky, B., & Sejnowski, T. (2021). Uncommon sense teaching. TarcherPerigee.
University of California, Berkley. (2016). Learning: Theory and research. Teaching Guide for GSIs. Retrieved February 16, 2022, from http://gsi.berkeley.edu/media/Learning.pdf
• ⁃ Vinney, C. (2019, July 22). What is a schema in psychology? definition and examples. ThoughtCo. Retrieved February 16, 2022, from https://www.thoughtco.com/schema-definition-4691768
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