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For five years, Mishra & Koehler conducted an experiment to understand educators’ development of rich technology uses as well as helping them develop their teaching with technology. As a result of this work, they arrived at the Technological, Pedagogical, Content Knowledge (TPCK) model in 2008, later renamed to TPACK.
The worked-example effect is a learning effect predicted by cognitive load theory. [ 1 ] [ full citation needed ] Specifically, it refers to improved learning observed when worked examples are used as part of instruction, compared to other instructional techniques such as problem-solving [ 2 ] [ page needed ] and discovery learning.
The template effects emphasizes the pre-organization provided by the coordination sphere, although the coordination modifies the electronic properties (acidity, electrophilicity, etc.) of ligands. [1] An early example is the dialkylation of a nickel dithiolate: [2] The corresponding alkylation in the absence of a metal ion would yield polymers.
The four levels of Kirkpatrick's evaluation model are as follows: Reaction - The degree to which participants find the training favorable, engaging and relevant to their jobs; Learning - The degree to which participants acquire the intended knowledge, skills, attitude, confidence and commitment based on their participation in the training
Failure mode and effects analysis (FMEA; often written with "failure modes" in plural) is the process of reviewing as many components, assemblies, and subsystems as possible to identify potential failure modes in a system and their causes and effects. For each component, the failure modes and their resulting effects on the rest of the system ...
Psychology professor Finn Tschudi's ABC model of psychotherapy uses a structure similar to a decisional balance sheet: A is a row that defines the problem; B is a row that lists schemas (tacit assumptions) about the advantages and disadvantages of resolving the problem; and C is a row that lists schemas about the advantages and disadvantages of ...
A mixed model, mixed-effects model or mixed error-component model is a statistical model containing both fixed effects and random effects. [ 1 ] [ 2 ] These models are useful in a wide variety of disciplines in the physical, biological and social sciences.
In applied mathematics, test functions, known as artificial landscapes, are useful to evaluate characteristics of optimization algorithms, such as convergence rate, precision, robustness and general performance.