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Related Concept Videos

Purposive Learning01:22

Purposive Learning

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E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
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Cognitive Learning01:21

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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
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Implicit memories, also known as non-declarative memories, are long-term memories that function outside of conscious awareness. These memories influence behavior and skills without explicit knowledge. This type of memory is evident in tasks like playing tennis, snowboarding, and texting. Implicit memory has three subsystems: procedural memory, conditioning, and priming. This type of memory is essential in various activities, from everyday tasks to specialized skills.
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Explicit Memories01:27

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Explicit memories, also known as declarative memories, are consciously remembered, recalled, and reported. Studying for a chemistry exam involves material that will become part of explicit memory. There are two types of explicit memory: episodic and semantic.
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Schemas

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A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.
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Controlled processes in human consciousness represent high-alert mental states where individuals deliberately focus their attention on achieving specific goals. Controlled processes can be seen in situations like mastering new technology, where a person might become so absorbed that they ignore surrounding distractions. Such processes involve selective attention, requiring one to concentrate on particular elements of experience while disregarding others. These are governed by executive...
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Related Experiment Video

Updated: Feb 27, 2026

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
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Tacit to explicit knowledge conversion.

Osvaldo Cairó Battistutti1, Dominik Bork2

  • 1Instituto Tecnologico Autonomo de Mexico, Mexico City, DF, Mexico. cairo@itam.mx.

Cognitive Processing
|July 6, 2017
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Summary

This study presents a four-step methodology for converting tacit knowledge into explicit knowledge. It uses conceptual modeling for visual representation, aiding understanding without language or algebra.

Keywords:
Knowledge acquisitionKnowledge conversionKnowledge managementKnowledge modelingKnowledge-based systems

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Area of Science:

  • Knowledge Management
  • Cognitive Science
  • Information Science

Background:

  • Tacit knowledge, residing in individuals' minds, is difficult to transfer through traditional means like writing or speaking.
  • Effective knowledge transfer is crucial for innovation and improving products or services.

Purpose of the Study:

  • To introduce a novel methodology for converting tacit knowledge into explicit knowledge.
  • To facilitate the understanding and transfer of complex ideas through visual representation.

Main Methods:

  • A four-step process designed for tacit-to-explicit knowledge conversion.
  • Utilization of conceptual modeling for visual knowledge representation.
  • Implementation within a metamodel-based tool environment for efficiency and ease of use.

Main Results:

  • The methodology enables understanding concepts visually, bypassing linguistic or algebraic interpretations.
  • Conceptual models facilitate reasoning and knowledge transfer.
  • The tool environment supports efficient application of the knowledge conversion process.

Conclusions:

  • The proposed methodology offers a practical approach to overcoming the challenges of tacit knowledge transfer.
  • Visual knowledge representation through conceptual modeling enhances comprehension and application.
  • The metamodel-based tool environment promotes the effective use of this knowledge conversion technique.