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Therefore, generalization is a valuable and integral part of learning and everyday life. Generalization is shown to have implications on the use of the spacing effect in educational settings. [13] In the past, it was thought that the information forgotten between periods of learning when implementing spaced presentation inhibited generalization ...
Learning is the process of acquiring new understanding, knowledge, behaviors, skills, values, attitudes, and preferences. [1] The ability to learn is possessed by humans, non-human animals, and some machines; there is also evidence for some kind of learning in certain plants. [2]
A polygon is a generalization of a 3-sided triangle, a 4-sided quadrilateral, and so on to n sides. A hypercube is a generalization of a 2-dimensional square, a 3-dimensional cube, and so on to n dimensions. A quadric, such as a hypersphere, ellipsoid, paraboloid, or hyperboloid, is a generalization of a conic section to higher dimensions.
Learning that takes place in varying contexts can create more links and encourage generalization of the skill or knowledge. [3] Connections between past learning and new learning can provide a context or framework for the new information, helping students to determine sense and meaning, and encouraging retention of the new information.
Learning theory (education) – Theory that describes how students receive, process, and retain knowledge during learning Constructivism (philosophy of education) – Philosophical viewpoint about the nature of knowledge; theory of knowledge; Radical behaviorism – Term pioneered by B.F. Skinner
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, complexity theory, and double ...
Colloquially, the task is known as learning from examples. Most theories of concept learning are based on the storage of exemplars and avoid summarization or overt abstraction of any kind. In machine learning, this theory can be applied in training computer programs. [2] Concept learning: Inferring a Boolean-valued function from training ...
In machine learning, lazy learning is a learning method in which generalization of the training data is, in theory, delayed until a query is made to the system, as opposed to eager learning, where the system tries to generalize the training data before receiving queries.