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A flow-based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing flow, [1] [2] [3] which is a statistical method using the change-of-variable law of probabilities to transform a simple distribution into a complex one.
Analogously, a classifier based on a generative model is a generative classifier, while a classifier based on a discriminative model is a discriminative classifier, though this term also refers to classifiers that are not based on a model. Standard examples of each, all of which are linear classifiers, are: generative classifiers:
The Keller Plan has mainly been used in higher education, particularly as a more personalized form of instruction in large classes, but there is nothing inherent in Keller's formulation to restrict its application to particular grade levels, content, or types of courses; [4] for instance the papers [5] and [6] report on usage in elementary school and junior high school, respectively.
Instructional design (ID), also known as instructional systems design and originally known as instructional systems development (ISD), is the practice of systematically designing, developing and delivering instructional materials and experiences, both digital and physical, in a consistent and reliable fashion toward an efficient, effective, appealing, engaging and inspiring acquisition of ...
The testing effect (also known as retrieval practice, active recall, practice testing, or test-enhanced learning) [1] [2] [3] suggests long-term memory is increased when part of the learning period is devoted to retrieving information from memory. [4]
The generation effect is typically achieved in cognitive psychology experiments by asking participants to generate words from word fragments. [2] This effect has also been demonstrated using a variety of other materials, such as when generating a word after being presented with its antonym, [3] synonym, [1] picture, [4] arithmetic problems, [2] [5] or keyword in a paragraph. [6]
Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 2 ] [ 3 ] [ 4 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 5 ] [ 6 ] based on ...
Situativity theorists suggest a model of knowledge and learning that requires thinking on the fly rather than the storage and retrieval of conceptual knowledge. In essence, cognition cannot be separated from the context. Instead, knowing exists in situ, inseparable from context, activity, people, culture, and language. Therefore, learning is ...