“Adaptive learning” refers to a platform or company’s ability to deliver and recommend learning in a tailored and adjustable way. For example, as an individual completes a learning activity or takes a test, an adaptive learning system would potentially skip modules that are not needed and jump to more advanced topics, recommend remedial topics, or let an employee test out of some type of learning activity.
Many microlearning systems have adaptive features. In safety training, for example, if you pass the course in “forklift driving safety,” the system would not retest you or force you to take the course again until a certain time period or a new procedure becomes available. This type of functionality is very common in regulated manufacturing (energy, pharmaceuticals, airline pilots) and other operational training.
Some vendors throw this phrase around to convince buyers their platform is dynamic and recommends just the right learning. This type of AI-recommended learning is not necessarily adaptive, because it may simply know that you clicked on courses on this topic and will show you more of them.
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