Life is a series of choices. From the moment we get up in the morning until the minute we lay our heads down at the end of the night, we are faced with choices. It is one after another. Yet for some reason, we enter the corporate training environment and the choices suddenly disappear. Everyone is fed the exact same information in the exact same way and expected to keep up and enjoy the process.
Adaptive learning is a principle that runs directly opposite to the one-size-fits-all educational model. It not only offers learners real choices, but it also adapts to those choices to create a more personalized learning environment in real time. Such adaptation is the core of the competency-based training platform developed by Salt Lake City’s Fulcrum Labs.
More About Adaptive Learning
Adaptive learning is all about turning students (and employees) into learners, a true shift in mindset. It is not about dispensing rote information that only need be memorized for a short amount of time. Rather, adaptive learning seeks to help learners quickly and efficiently master skills. It seeks to reinforce learning behaviors that promote success, so that once training is complete, what was learned will be carried into the real world and applied as intended back on the job.
As such, adaptive learning encourages learners to be engaged participants in their own training. For example, the Fulcrum Labs platform offers learners three different ways to engage with course material. They can read text, they can watch multimedia, and they can practice what they learn.
Choices go one step further by allowing learners to combine each of the three options as they see fit. One learner might need more time reading, while another might prefer watching videos, also depending on the content. Both might need varying levels of practice as well. They can customize their engagement in whatever way facilitates the best learning.
Choices Help the Platform Too
The most advanced platforms, including the one developed by Fulcrum Labs, incorporate artificial intelligence and machine learning technologies. Highly advanced algorithms continuously run data analysis as a learner progresses through the course. The artificial intelligence component ‘learns’ from both the answers provided and the learner’s behaviors and, over time, customizes the environment for that particular individual.
The end result of all these choices, and their respective analyses, is an experience that operates more like a one-on-one training session than an inflexible e-learning experience. Learners are more likely to thrive as a result.
Choices Increase Learner Engagement
The combined effect of choices on both learner and software creates an environment in which learners are engaged. They are engaged through a platform that draws them in through the choices they make. The more they are drawn in, the more they become learners rather than students. What is the difference?
Students are fed information they are expected to memorize and repeat. They are essentially being handed test answers they have to remember long enough to pass their assessments. Learners go deeper. They want to know more than just facts. They want more than just test answers. They want to understand the finer details and nuances of the information they are studying.
Learner choices are crucial to adaptive learning for this very reason. If learners are not given choices, they are merely receptacles of static information. Thus, they are no longer motivated to dig deeper and understand why. This type of adaptive learning is of very little value to them.
On the other hand, giving learners choices gives them a reason to do better. Adapting to those choices results in using an adaptive learning platform to its fullest potential. Students become learners who eventually master the required skills, build their confidence and then apply those skills outside of the learning environment.