Model

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Model is a set of facts and rules that describe a phenomenon. A model is a generalization of the phenomenon it represents. Models make it easy to operate on reality using concepts stored in human memory. Efficient use of models underlies human intelligence.

For example: jigsaw puzzle metaphor of learning is a model of how knowledge coherence emerges in the process of learning.

The term model overlaps with terms such as theory, metaphor, opinion, schema, view, and more.

In human brain, forgetting and memory optimization play a vital role in the process of generalization that converts a set of disjointed facts and/or rules into a coherent model.

For more see:

This glossary entry is used to explain SuperMemo, a pioneer of spaced repetition software since 1987

Abstract knowledge terminology

  • generalization: a process in which detail is ignored to reveal a deeper structure. The term overlaps with abstraction, conceptualization, inductive reasoning, modeling, theorization, categorization, conclusion, unification, colligation, de-concretization, pattern extraction, pattern separation, and more. Example: Trump is a winner is a gross generalization that ignores Donald Trump's failures
  • concept: a generalization of a set of objects/nouns. It overlaps with idea, entity, notion, group, etc. For example, animal is a concept derived from objects such as specific cats, birds, etc. Perhaps this should also include: property, attribute, quality, etc. i.e. the abstraction of object characteristics (e.g. the concept of yellowness)
  • rule: a generalization of an observed regularity. It overlaps with formula, theorem, principle, proposition, law, statement, and more. Example: "no pleasure, no good learning" is a fundamental law of learning. It is an example of a general rule that determines learning strategies
  • model: set of rules that apply to a specific phenomenon. It overlaps with theory, metaphor, opinion, schema, view, (concept) map, (formal) system, and more. Example: jigsaw puzzle metaphor of learning is a model of how knowledge coherence emerges in the process of learning
  • abstractness: universality of a concept or a rule, e.g. 2 apples and 2 apples add up to 4 apples is less abstract (i.e. more concrete or more specific) than 2+2=4
  • applicability: usefulness of a rule or model. It overlaps with usability. Example: 2+2=4 is useful in counting apples, but not-too-helpful in memorizing song lyrics
  • abstract knowledge: well-generalized, highly applicable knowledge that is conceptual/abstract in nature. It overlaps with: "big picture", set of rules/formulas, abstract set, theory, etc. Example: mathematics is the queen of abstract knowledge
  • abstract thinking: conceptual computation on rich and complex abstract knowledge