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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 ...
An elementary example of transfer learning would be, for example, in dealing with subject–verb agreement: When you have a singular subject you have to add an "s" on the end of the verb and when you have a plural subject you do not put an "s" on the end of the verb. However, when they are the subjects "I" and "You", they do not follow this rule.
Learning theory (education) A classroom in Norway. Learning theory describes how students receive, process, and retain knowledge during learning. Cognitive, emotional, and environmental influences, as well as prior experience, all play a part in how understanding, or a worldview, is acquired or changed and knowledge and skills retained. [1] [2]
Illustration of transfer learning. Transfer learning ( TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related task. [1] For example, for image classification, knowledge gained while learning to recognize cars could be applied when trying to recognize trucks.
Knowledge transfer refers to transferring an awareness of facts or practical skills from one entity to another. The particular profile of transfer processes activated for a given situation depends on (a) the type of knowledge to be transferred and how it is represented (the source and recipient relationship with this knowledge) and (b) the processing demands of the transfer task.
Transfer-appropriate processing (TAP) is a type of state-dependent memory specifically showing that memory performance is not only determined by the depth of processing (where associating meaning with information strengthens the memory; see levels-of-processing effect), but by the relationship between how information is initially encoded and how it is later retrieved.
Inductive bias is anything which makes the algorithm learn one pattern instead of another pattern (e.g. step-functions in decision trees instead of continuous function in a linear regression model ). Learning is the process of apprehending useful knowledge by observing and interacting with the world. [2]
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 ...