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Published on BioPortfolio: 2018-06-15T02:13:10-0400
An e-learning module to teach how to evaluate ears in children was recently designed. The aim of this study is to measure the impact of this e-learning module on the trainees' ability to a...
In the pilot trial cardiac patients will be provided with e-learning videos, 2 à 5 times/week during the 4-week trial period.
The study aim is to determine whether simulation based learning would improve senior anesthesiology residents' patient care performance during the insertion and management of cerebrospinal...
HOPP Learning will be implemented in elementary schools in the Horten municipality and will assess the effect of a combined pedagogical approach, active learning, on a large student popula...
This study aims to compare heart rate variation, cognitive load, and learning outcomes of novel image-based virtual reality with traditional video in learning for otolaryngology. Half of p...
Contemporary perspectives on regulated learning are moving beyond models, emphasising individual learning (self-regulated learning) to models that position social transactions at the core of learning ...
Personalized learning refers to instruction in which the pace of learning and the instructional approach are optimized for the needs of each learner. With the latest advances in information technology...
Implicit learning and statistical learning are two contemporary approaches to the long-standing question in psychology and cognitive science of how organisms pick up on patterned regularities in their...
Recent advances in the learning sciences offer remarkable potential for improving medical learning and performance. Difficult to teach pattern recognition skills can be systematically accelerated usin...
To introduce active learning session for a large group of 250 students, we combined the strengths of problem-based learning and team-based learning to promote a structured active learning strategy wit...
Process in which individuals take the initiative, in diagnosing their learning needs, formulating learning goals, identifying resources for learning, choosing and implementing learning strategies and evaluating learning outcomes (Knowles, 1975)
A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of labeled paired input-output training (sample) data.
A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of unlabeled paired input-output training (sample) data.
Change in learning in one situation due to prior learning in another situation. The transfer can be positive (with second learning improved by first) or negative (where the reverse holds).
Usually refers to the use of mathematical models in the prediction of learning to perform tasks based on the theory of probability applied to responses; it may also refer to the frequency of occurrence of the responses observed in the particular study.