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Categorization is a type of cognition involving conceptual differentiation between characteristics of conscious experience, such as objects, events, or ideas.It involves the abstraction and differentiation of aspects of experience by sorting and distinguishing between groupings, through classification or typification [1] [2] on the basis of traits, features, similarities or other criteria that ...
TRIZ flowchart Contradiction matrix 40 principles of invention, principles based on TRIZ. One tool which evolved as an extension of TRIZ was a contradiction matrix. [14] The ideal final result (IFR) is the ultimate solution of a problem when the desired result is achieved by itself.
Higher-order thinking involves the learning of complex judgmental skills such as critical thinking and problem solving. Higher-order thinking is considered more difficult to learn or teach but also more valuable because such skills are more likely to be usable in novel situations (i.e., situations other than those in which the skill was learned).
Problem solving consists in using generic or ad hoc methods, in an orderly manner, for finding solutions to problems. Some of the problem-solving techniques developed and used in artificial intelligence , computer science , engineering , mathematics , medicine , etc. are related to mental problem-solving techniques studied in psychology .
Strategy consultants use MECE problem structuring to break down client problems into logical, clean buckets of analysis that they can then hand out as work streams to consulting staff on the project. Similarly, MECE can be used in technical problem solving and communication.
Concept learning, also known as category learning, concept attainment, and concept formation, is defined by Bruner, Goodnow, & Austin (1956) as "the search for and testing of attributes that can be used to distinguish exemplars from non exemplars of various categories".
Bloom's taxonomy is a framework for categorizing educational goals, developed by a committee of educators chaired by Benjamin Bloom in 1956. It was first introduced in the publication Taxonomy of Educational Objectives: The Classification of Educational Goals.
One-shot learning is an object categorization problem, found mostly in computer vision.Whereas most machine learning-based object categorization algorithms require training on hundreds or thousands of examples, one-shot learning aims to classify objects from one, or only a few, examples.