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PALMs stands for Perceptual and Adaptive Learning Modules.
After answering correctly, the module will display your response time. Getting a problem wrong, or taking so long that the problem times out, will prompt feedback about the correct answer.
Perceptual and Adaptive Learning Modules (PALMs) offer, for the first time, systematic ways of teaching pattern recognition. PALMs targeting crucial learning domains in mathematics and science have been shown to have powerful, long-lasting effects on learning.
The patented adaptive learning and perceptual learning technologies tailor learning to the individual, using past and current performance to optimize the spacing and sequencing of learning events. The automated sequencing procedures guarantee that items will not be presented too early or too late in the learning process - both of which can impede efficient learning.
PALMs targeting learning domains within mathematics and a variety of sciences have been shown to have powerful, long-lasting effects on student learning. This approach can be applied to many areas of learning.
Perceptual Learning refers to changes in the way we pick up information as a result of experience or practice and is achieved through exposure to varied examples. A characteristic of experts in any domain is that they selectively pick up relevant information, discover important patterns, and see key structure in new cases or situations. They are able to extract key patterns quickly and fluently with little effort (cognitive load), freeing up attention for higher-level problem solving. Expertise and perceptual learning are tightly interwoven. The patented Perceptual Learning approach groups items into categories according to an underlying common pattern (eg, diagnosis, species of animals, related set of mathematic problems) and presents a new exemplar each time a category is revisited. This allows the learners to master each category's underlying structure, rather than simply memorizing specific examples.
Adaptive Learning is a broadly-used term referring to approaches that individualize the sequence of problems presented to a leaner according to the learner's past performance and level of mastery. The patented Adaptive Response-Time Based Sequencing dynamically adjusts content based on student proficiency, using both fluency and retention to create a uniquely efficient learning experience. Because learners have different learning needs, every PALM presents a different learning pathway for each learner, dynamically choosing which learning points to focus on and how much practice is necessary to reach optimal learning.
The algorithm takes into account both the accuracy and speed of the learner on every learning trial. Each category of items is tracked individually to determine the optimal order of learning material. The automated sequencing procedures guarantee that items from the same category will not be presented too soon or too late — both of which can impede learning. Items from less well-learned categories will return sooner, whereas more well-learned categories are spaced further apart. These algorithms attempt to space out presentations for as long as possible, fostering long-term retention of the material.
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