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A PBL group at Sydney Dental Hospital. Problem-based learning ( PBL) is a student-centered pedagogy in which students learn about a subject through the experience of solving an open-ended problem found in trigger material. The PBL process does not focus on problem solving with a defined solution, but it allows for the development of other ...
Learning styles. 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.
70/20/10 Model (Learning and Development) The 70:20:10 model for learning and development (also written as 70-20-10 or 70/20/10) is a learning and development model that suggests a proportional breakdown of how people learn effectively. It is based on a survey conducted in 1996 asking nearly 200 executives to self-report how they believed they ...
Project-based learning ( PBL) is a teaching method that involves a dynamic classroom approach in which it is believed that students acquire a deeper knowledge through active exploration of real-world challenges and problems. [1] Students learn about a subject by working for an extended period of time to investigate and respond to a complex ...
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 human-labeled supervisory signal) train a model. The training data is processed, building a function that maps new data on expected output values. [1]
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.
Mastery learning (or, as it was initially called, " learning for mastery "; also known as "mastery-based learning") is an instructional strategy and educational philosophy, first formally proposed by Benjamin Bloom in 1968. [1]
v. t. e. Temporal difference ( TD) learning refers to a class of model-free reinforcement learning methods which learn by bootstrapping from the current estimate of the value function. These methods sample from the environment, like Monte Carlo methods, and perform updates based on current estimates, like dynamic programming methods. [1]