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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] Behaviorists look at learning as an aspect of ...
Set theory is the branch of mathematical logic that studies sets, which can be informally described as collections of objects. Although objects of any kind can be collected into a set, set theory — as a branch of mathematics — is mostly concerned with those that are relevant to mathematics as a whole. The modern study of set theory was ...
Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. [1][2][3] Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data. Statistical learning theory has led to successful applications in fields such as ...
Bloom's taxonomy is a framework for categorizing educational goals, developed by a committee of educators chaired by Benjamin Bloom in 1956. It was first introduced in the publication Taxonomy of Educational Objectives: The Classification of Educational Goals. The taxonomy divides learning objectives into three broad domains: cognitive ...
The Maturational Theory of child development was introduced in 1925 [1] by Dr. Arnold Gesell, an American educator, pediatrician and clinical psychologist whose studies focused on "the course, the pattern and the rate of maturational growth in normal and exceptional children" (Gesell 1928). [2] Gesell carried out many observational studies ...
Learning styles refer to a range of theories that aim to account for differences in individuals' learning. [1] Although there is ample evidence that individuals express personal preferences on how they prefer to receive information, [2]: 108 few studies have found validity in using learning styles in education. [3]: 267 Many theories share the ...
Supervised learning. Supervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as a human-labeled supervisory signal) train a model. The training data is processed, building a function that maps new data to expected output values. [1]
Meaningful learning. Meaningful learning refers to the act of higher order thinking and development through intellectual engagement that uses pattern recognition and concept association. It can include—but is not limited to—critical and creative thinking, inquiry, problem solving, critical discourse, and metacognitive skills. [1]