Department store suits are all right but those that are tailored directly on the person who will be wearing them are ten times better. Of course, getting a suit done at a tailor’s means several visits, many measurements and a lot more decisions (involving the materials, the shape, the buttons, the length of the trousers, and so on) on the part of the customer and the craftsman. The end result, however, will most definitely be worth it.
Mass production may have done wonders for economic growth and cost efficiency but unique (often hand crafted) items will always be infinitely more valuable and sought after. This is mainly because individuals themselves are unique and like to celebrate that in the objects and experiences they have.
Adaptive learning – an individual-focused endeavor
Adaptive learning has been called in several ways – such as intelligent tutoring or adaptive instruction. Regardless of what we call it, adaptive learning is mainly seeking to employ modern day technology to better the education or personalize the learning experience.
First of all, the platform has to pay attention and keep track of everything the learner is doing, analyze all that data and use the results to tailor the online content and the medium in which it is being delivered to optimally respond to the unique needs of the individual. It may sound a bit “big brother”-ish and lacking the human touch but though it is an automated process obsessively recording everything a learner does, its ultimate goal is to recognize and celebrate the uniqueness of each individual.
And L&D professionals should not be nervous about their jobs either since content delivery might be automated but content design is not. Adaptive learning requires a lot of learning materials at hand so if anything, content designers will have more work to do rather than none.
Algorithms – the key to efficient personalization
In order for adaptive learning to work, it needs very well thought algorithms behind it. These have to be able to use all the gathered data to calculate the best possible course to take. If the learner completes a test, for example, the algorithm can take into account the correct and incorrect answers and push relevant content forward – it will obviously pick the units that will help the person enrolled in the course give better answers to the questions they missed.
If several scenarios have been drawn up, the platform can even pick the right one for every specific learner. In case somebody gets stuck on one question or is browsing a lot through the already covered content in search for information or clues, the interactive platform can take the learner back to the specific section covering that or take him to an additional section with more detailed information on the subject in order to clear it up.
The future is adaptive
Of course, algorithms are not perfect but as technology evolves they are constantly improving and are moving the learning experience closer to what social media or online stores are already doing – grouping people based on their likes and interests while recommending appropriate events or products.
This personalized approach holds great appeal to the learner, especially since the online technology allows for approaching the material at their own time and pace. Adaptive learning technology allows participants to make sure they use their learning time as efficiently and productively as possible.
Participants still have to make an effort in order to succeed; but with adaptive technology, this effort will be channeled better. As one recent study found: “There is also evidence that adaptive systems positively impact other aspects of quality such as learner persistence and engagement. More compelling still are the intuitively appealing cases for adaptive learning systems as engines with which institutions can increase access and reduce costs.”
Adaptive learning is still in its infancy but it definitely represents the future.