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Bioconcentration. In aquatic toxicology, bioconcentration is the accumulation of a water-borne chemical substance in an organism exposed to the water. [1][2] There are several ways in which to measure and assess bioaccumulation and bioconcentration. These include: octanol-water partition coefficients (K OW), bioconcentration factors (BCF ...
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A PBL group at Sydney Dental Hospital. Problem-based learning (PBL) is a teaching method 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 desirable skills ...
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 ...
Dunn and Dunn's learning styles model is widely used in schools in the United States, and 177 articles have been published in peer-reviewed journals referring to this model. [1]: 20 However, the conclusion of a review by Coffield and colleagues was: "Despite a large and evolving research programme, forceful claims made for impact are ...
Lifelong learning is the "ongoing, voluntary, and self-motivated" [1] pursuit of learning for either personal or professional reasons.. Lifelong learning is important for an individual's competitiveness and employability, but also enhances social inclusion, active citizenship, and personal development.
Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent ought to take actions in a dynamic environment in order to maximize the cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and ...
Deep learning is a subset of machine learning methods based on neural networks with representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.