Transfer of Learning
A capability that comes from
generalization and is
related to learning by analogy. Learned
information can be applied to other problem instances and possibly
even other instances. Three specific types of learning transfer
are normally identified:
Within-Trial
Learning applies immediately to the current situation.
Within-Task
Learning is general enough that it may apply to different problem
instances in the same domain.
Across-Task
Learning applies to different domains. Examples here include some types of
concept acquisition in which a concept
learned in one domain (e.g., blocks) can be related to other
concepts (e.g., bricks) through similarities (e.g., stackable).
Across-task learning is then strongly analogical.
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