Learning how to learn: mental models
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Learning how to learn: mental models

A practical philosophy with basic principles for learning, doing and dealing with problems

About the Book

Learning is perhaps one of the key points of existence. We learn so that we can have new or different experiences. Being able to learn means we can do new things or do old things in novel ways. This ability to learn underlies the ability to solve problems. It also underlies the ability to create meaningfully.

Mental models, or more simply models, are what we create when we learn. Whether we are learning something that is outside of ourselves, some system we have to run, build, sell, install, fix or upgrade or whether it is something that directly involves ourselves, mental models are the result of that learning.

A key to effective learning, to understanding, is building these models from two points of view. So that learning is efficient and non-frustrating we can break what we are learning into clearly defined elements and focus on small groups of these in relative isolation.

A further element of learning is indexing the models that our brain builds so that we can call them up without having to think.

An additional key to learning is being able to check what we’ve learned, so that we can improve our models when necessary.

This books details a set of simple concepts, and includes principles (both first principles and basic principles) that can be easily adapted to make learning, problem solving, and creating easier.

These concepts and principles provide a framework for both thinking about how to do things and how to actually do them. 

Learn how to learn, and how to:

  • Build better mental models (and how to scale and modularize them)
  • Make learning efficient, effective and less frustrating
  • Improve problem solving abilities
  • Deal effectively with fear and frustration
  • Use limits to become less limited
  • Utilize mental models for better muscle control and body awareness
  • Improve our understanding and the way that we do things

It all starts with the notion that our brain builds models, mental models, and those models form the foundation of our understanding, intuition and habits. At the same time, we can choose how we construct and index those models thus improving our understanding and the way that we do things.

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Translations

About the Author

Neil Keleher
Neil Keleher

Hi, I'm Neil Keleher


When I was sixteen I quit school and enlisted in the British Army.

I spent five years as an armourer while continuing my education by studying math and English via correspondence course.


Moving back to Canada, I studied Systems Design Engineering at the University of Waterloo. While there, my dad, uncle and I built a custom Harley and not long after I learned to ride a motorcycle.


I spent three years as an Engineer and then dabbled in acting before spending the next 25 years as a yoga teacher.


Moving to Taiwan, I studied Tai Ji and Chinese calligraphy. I also got so frustrated looking up Chinese characters (I was using a paper dictionary) that I spent 15 years building my own dictionary and designing several indexing systems. In the process I learned how to touch-type Chinese and how to program using Python as well as Node.js.


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Table of Contents

    • Overview
      • Mental Models
      • Habits and Intuitions
      • Noticing
      • Stability and room to move
      • Mind-states
      • Short-term memory
      • Breaking down
      • Two points of view
      • Indexing and Contexting
      • Practice
      • Gradual increments
      • Clear Ideas
      • Fracticality
      • Checking and fast(er) feedback
      • Resting is necessary
      • Reusable concepts
      • Systems
      • Ideas
      • Relationships
      • Problems
      • Prototyping
      • Systems, Sensitivity and Change (Sensible limits)
      • Sensori-motor learning
      • Slow and smooth movements
      • Creativity
      • Zeroparallax
      • Dual mind-states, Dual points of view
      • Limits for becoming limitless
    • 1 Mental models
      • Modelling the world so we can interact with it
      • Models for the things we do
      • Models for the things we use
      • Models represent and predict
      • Making learning less effortful
      • Human (vs AI) Learning
      • Enabling the power of choice
      • Model Hardware
    • 2 Mind-states (Thinking and Not-thinking)
      • The fluid mind-state
      • Experiences of fluidity
      • The day-dreaming mind-state
    • 3 Habits
      • No time to think
      • Answering math questions quickly
      • Negligent Discharge
      • My first experience of riding (without the necessary habits)
      • Habits as options
      • Making life easier
      • Reducing frustration via habits
      • Habits can be changed…
      • Sudden knowings, an output of mental models
      • Intuition as a model output
      • Building intuition
      • Inner space
      • Expanding fully into the imaginary or fully into the real
      • Habit override
    • 4 Noticing (and paying attention)
      • Noticing how things relate
      • Noticing details
      • Fast feedback
      • Stability and room to move
    • 5 Short term memory
      • It only holds so much
      • Chunky Learning
      • Short-term memory limits
      • Recognizing sufficient practice
      • Memorizing brush strokes
      • Breaking things down
      • Embedding in long-term memory
      • Recognizing
      • Notes on memory limits
      • Isolating: Learning to ride a motorbike
      • Learning Tai Ji
      • Making choosing easier
      • Listening in chunks
      • Grouping to learn
      • Isolating and then re-integrating
      • Re-useful: Grouping for re-use
      • Making learning joyful
    • 6 Breaking things down
      • Breaking down rifles
      • Learning to program
      • Learning a sequence of yoga poses or movements
      • Learning Tai Ji (Weight shifting)
      • Muscle Grouping via attachment points
      • Isolated Muscle Head function
      • Breakdown and isolate to learn
      • Yoga and Muscle activation
      • Breaking down Chinese characters
      • Limits enable learning
      • Dealing with overwhelm
      • Recognizing completion
    • 7 Mental models need two points of view
      • Two points of view with calculus
      • Breaking things down
      • Integrating
      • Small arms and practical calculus
      • A benefit of fixed sequencing
      • Manual learning
      • Building a better predictive model
      • Building more effective models
      • Learning effectively while reading
      • If we have the book why learn it?
      • Figuring out what each part is about
      • Figuring out the two points of view
      • Memory techniques
      • Memory palace dual views
      • Laplace transforms
      • Feynman-like understanding
    • 8 Indexing (and contexting)
      • An example of poor indexing
      • Learning to touch-type Chinese
      • Common traits
      • Contexting
      • Spiderbots
      • Warehousing
      • How our brain indexes?
      • Systems as a context
      • Clear definitions
      • De-contexting
      • Typing is faster than looking up
    • 9 Practicing requires purpose
      • Deciding the purpose of a practice
      • Drawing practice
      • Fail safely
      • Recognizing completion while practicing
      • Levels or types of practice
      • Practicing Chinese characters
      • Using sensitivity and control
      • A transferable skill
      • Practicing mind-state control
      • Practicing thinking
      • Using limits to become less limited
    • 10 Learning is iterative (checking is required)
      • Checking what we’ve done
      • Fixing the model to fix its outputs
      • Fast feedback and better indexing
      • Efficiently correcting problems
      • Dancing with chaos (as modular as possible)
      • Checking ourselves
    • 11 Learning from experience
      • Two mind-states, two points of view
      • Sensing limits in the fluid mind-state
      • The dangers of thinking
      • Overcoming fear
      • Directing our mind and our senses
      • Riding a river versus watching it
      • Viewing time as a river (it carries us through space)
      • The journey and looking back
      • Stopping to check our map
      • Complex numbers, the root of -1
      • Real and imaginary space
      • How to be like water
    • 12 A Clear Idea
      • Swift, Python and Node JS
      • It’s a web app (I think)
      • Well why not build a web server
      • Teaching yoga
      • Selecting a computer
      • Selecting (and unselecting) an iPad
      • Deselecting a place to eat
      • Define the problem
      • Coat Hooks
      • Rebel AI
      • Loon
    • Resting is necessary
    • 13 Systems
      • Why we learn systems
      • Components
      • Signals
      • Two views
      • Defining and Redefining Systems (and Models)
      • Fracticality, choosing a practical scale for break down
      • A Dauntless approach to learning
      • Landmarks (making or using maps)
      • Recognition (and using labels)
      • Indexes as a component view
    • 14 Ideas
      • Defining an idea
      • Undestanding an idea
      • Systems as ideas
      • Being like water
      • Thinking clearly in terms of ideas
    • 15 Relationships
      • Ideas, Relationships, systems
      • Connection
      • Connections and the flow of change
      • Ideas and relationships as options
    • 16 Problem solving requires learning
      • Fault finding a custom built Harley
      • Components and change
      • Checking our solution
      • Learning to feel and control muscles
      • Basic principles for muscle control
      • A model for pain, posture and tightness
      • Stability is a pliable concept
      • The greater the change the greater the required stability
      • Fixing problems with the body
      • Learning while problem solving
    • 17 Prototyping is a different type of learning
      • Creating something real
      • Working towards the change we want to create
      • Building a mental model in reverse
      • Prototypical understanding
      • Building from two points of view
      • Prototypical experiences
      • Specifying what we want
      • Experience from practice and prototyping
    • 18 Sensing change as early as possible
      • Change
      • Outer and inner environments
      • Sensing our inner environment
      • Event horizons and sensory limits
      • Change doesn’t stop
      • Maximizing the event horizon
      • Staying with the pack
      • Extending our inner environment (expanding our control)
      • Directing our senses externally
      • Configuring to transmit change or dissipate it
    • 19 Sensitivity, Responsiveness and Control
      • Sensing instead of thinking
      • Applying body awareness to motorcycling
      • Recognizing
      • Feeling and controlling weight shifts
      • Recognizing skin contact
      • Sensitivity (and control) is transferable
      • Doing math without thinking
      • Doing Tai Ji without thinking
      • Balancing sensitivity, stability and responsiveness
      • Adjusting to find the middle spot
    • 20 Sensible Limits for Learning
      • Modelling a medical irradiator
      • Learning body awareness
      • Calibrating for touch and pressure
      • Calibrating internal sensation
      • Elbow sensitivity
      • Improving elbow sensitivity and control
      • Upper arm and forearm sensitivity
      • Practicing arm control in context
      • Scanning
      • Practicing whole body awareness
      • Tuning and adjusting
      • Shoulder rotation
      • Arm adjustments in a context
      • Creating sensation first
      • Two sides of the same coin
      • Creating straightness or length
      • Sensing our body as a whole
      • Sensitivity and responsiveness
      • Creating transferability
      • Becoming less limited
    • 21 Zeroing parallax (or calibrating to account for it)
      • Parallax and chemistry
      • Parallax, pilots, clocks and watches
      • Understanding relationships when drawing
      • Understanding relationships when weight shifting
      • Assessing or controlling relationships
      • A reference for change
    • 22 Basic Principles for learning and doing
      • Know the change we want to create
      • Work within Short-Term memory limits
      • Recognize relationships
      • Create stability (a reference for change)
      • Adjust for Room to sense, Room to move
      • Room for all
      • Riding a motorcycle: ideas, relationships, and change
      • Augmented first principle thinking
    • 23 Using limits to approach infinity
      • Limits in the thinking mode
      • Limits in the fluid mode
      • Limits for learning to feel and control our body
      • Discerning change
      • Handling change
      • A taste of infinity
    • 24 A practical philosophy: the calculus of why we are here
      • An IQ of 1
    • Concepts, terminology, tenets
    • References etc.
      • Cortical Columns
      • The Loon Project
      • Other
      • My stuff
    • About Neil Keleher

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