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Transfer of learning. Transfer of learning occurs when people apply information, strategies, and skills they have learned to a new situation or context. Transfer is not a discrete activity, but is rather an integral part of the learning process. Researchers attempt to identify when and how transfer occurs and to offer strategies to improve ...
Generalization allows humans and animals to recognize the similarities in knowledge acquired in one circumstance, allowing for transfer of knowledge onto new situations. This idea rivals the theory of situated cognition, instead stating that one can apply past knowledge to learning in new situations and environments.
For example, after completing a safety course, transfer of training occurs when the employee uses learned safety behaviors in their work environment. [1] Theoretically, transfer of training is a specific application of the theory of transfer of learning that describes the positive, zero, or negative performance outcomes of a training program ...
Concept learning. Concept learning, also known as category learning, concept attainment, and concept formation, is defined by Bruner, Goodnow, & Austin (1967) as "the search for and listing of attributes that can be used to distinguish exemplars from non exemplars of various categories". [This quote needs a citation] More simply put, concepts ...
Machine learningand data mining. Vapnik–Chervonenkis theory (also known as VC theory) was developed during 1960–1990 by Vladimir Vapnik and Alexey Chervonenkis. The theory is a form of computational learning theory, which attempts to explain the learning process from a statistical point of view.
Other learning theories. Other learning theories have also been developed for more specific purposes. For example, andragogy is the art and science to help adults learn. Connectivism is a recent theory of networked learning, which focuses on learning as making connections. The Learning as a Network (LaaN) theory builds upon connectivism ...
Domain-general learning theories of development suggest that humans are born with mechanisms in the brain that exist to support and guide learning on a broad level, regardless of the type of information being learned. [1] [2] [3] Domain-general learning theories also recognize that although learning different types of new information may be ...
Multitask Learning is an approach to inductive transfer that improves generalization by using the domain information contained in the training signals of related tasks as an inductive bias. It does this by learning tasks in parallel while using a shared representation; what is learned for each task can help other tasks be learned better.