We define personalized learning as using adaptive learning technology to give learners greater control over their learning experience.
A report from the Aspen Institute recommends empowering learners to learn at “any time, any place, [and] any pace” for maximum impact. There are two common myths that impact personalized learning: the Path and Pace arguments.
The path argument states learners tend to learn more if they get to pick and choose what they learn. The pace argument states participants in a reinforcement program will learn more when they have more power over when, and at what pace, they learn.
In our view, the path argument goes against the concept of the nature of learning being cumulative. If you try to learn something at a high level, but lack the building blocks to contextualize the information, the learning experience becomes frustrating. Therefore, a leveled training approach is best so participants can learn the baseline, then level up as they continuously acquire knowledge.
Many learners don’t have the time to determine how a tack meshes with their individual learning needs. This means that learners often make poor decisions over what or when to learn, and ultimately fail to achieve the desired result.
Our brains are programmed to avoid activities we perceive as unpleasant. In the case of training, this could mean your employees actively avoid engaging in programs they find difficult or cumbersome. By using microlearning technology to guide learning and balance challenge versus satisfaction, you can encourage greater skill development over a greater period of time.
For the same reasons, many learners will opt for a slow learning pace. Since the reinforcement course is one more deliverable in an already packed schedule, speeding the pace of the learning program may not make sense.
Mindmarker allows you to create guided individualized reinforcement courses for any skills you wish to foster. To learn more about our proven methodology, download The Science Behind Mindmarker.
This post was originally published on August 5, 2016.
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