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The label of discovery learning can cover a variety of instructional techniques. According to a meta-analytic review conducted by Alfieri, Brooks, Aldrich, and Tenenbaum (2011), [3] a discovery learning task can range from implicit pattern detection, to the elicitation of explanations and working through manuals to conducting simulations ...
According to Boyer, traditional research, or the scholarship of discovery, had been the center of academic life and crucial to an institution's advancement, but it needed to be broadened and made more flexible to include not only the new social and environmental challenges beyond the campus but also the reality of contemporary life.
Inquiry-based learning (also spelled as enquiry-based learning in British English) [a] is a form of active learning that starts by posing questions, problems or scenarios. It contrasts with traditional education , which generally relies on the teacher presenting facts and their knowledge about the subject.
It differs from blended learning models in which teachers assign online content and resources, since in self-blended learning it is the students who direct their own online learning. [2] It is a highly flexible model that allows for advanced students to take classes with increased specialization, and for students who have fallen behind in ...
Discovery-driven planning is a planning technique first introduced in a Harvard Business Review article by Rita Gunther McGrath and Ian C. MacMillan in 1995 [1] and subsequently referenced in a number of books and articles.
Collaborative learning is a situation in which two or more people learn or attempt to learn something together. [1] Unlike individual learning, people engaged in collaborative learning capitalize on one another's resources and skills (asking one another for information, evaluating one another's ideas, monitoring one another's work, etc.).
Observational learning is learning that occurs through observing the behavior of others. It is a form of social learning which takes various forms, based on various processes. In humans, this form of learning seems to not need reinforcement to occur, but instead, requires a social model such as a parent, sibling, friend, or teacher with ...
In supervised learning, the training data is labeled with the expected answers, while in unsupervised learning, the model identifies patterns or structures in unlabeled data. In machine learning , supervised learning ( SL ) is a paradigm where a model is trained using input objects (e.g. a vector of predictor variables) and desired output ...