What is adaptive learning? Lots of people are talking about it, but not everyone fully understands it.
Imagine a futuristic utopia of learning, where people aren’t subjected to static, rigid training programmes. Instead, their training is able to adapt to their needs and interests until it’s just right for them.
Don’t worry, we’re not going to drag you all the way back to a gritty reality, because we’re already living in the early stages of this utopia!
Let’s take a closer look at what adaptive learning is, and why it’s making such a big impact in the world of L&D.
Adaptive learning is a branch of the much wider area of personalised learning. What makes adaptive learning unique is that it’s focused on the use of technology to personalise learning.
In an adaptive learning solution, the system can keep track of everything that the learner is doing. It’s clever enough to analyse their actions and so it will be able to adapt the training to better suit that individual, such as by giving them access to more relevant learning materials.
Though this is all automated, don’t think that it puts L&D professionals out of a job! It still requires a lot of human input, and actually requires even more content to be created. You need to have materials ready for every scenario or branching path, so that the system can push learners towards them.
Ways adaptive learning works
Adaptive learning generally uses algorithms to adapt training. These can work out the best possible intervention given any number of actions the learner takes.
For example, if the learner takes a test, the algorithm can adapt the training according to the answers given. Doing badly on certain questions can trigger the system to push relevant content to the learner, or the overall performance could determine which learning path they take.
More advanced systems can even step in during content. For example, it might detect that a learner is spending lots of time on a question or asking for lots of hints. This could trigger it to unlock an extra section of the course which breaks the subject down further to try and make it easier to take in.
As algorithms in learning technologies improve, we move closer towards the experiences we’re used to when using social media or online shopping sites. Learners can be grouped together based on their actions and interests, and completing a particular piece of content could lead to other content being recommended, which other similar learners have benefitted from.
Interventions aren’t limited to the online world either. An adaptive learning system can flag up when learners might be struggling with the programme as a whole, alerting the training managers to step in and provide support.
Future of adaptive learning
As exciting as all of this is, the technology used within adaptive learning is still in its relative infancy. As computer scientists toil away at their algorithms, artificial intelligence will continue to improve.
To give a sense of scale to the progress in this field, Google Deepmind’s AlphaGo stunned the world back in March by defeating one of the world’s most experienced Go players. This is such a complex game that experts in the field thought that we were still at least ten years off seeing this kind of victory!
While it will still be some time before AI is able to create the content for us, the adaptive learning systems will continue to get more and more complex. They’ll be able to better pair up learners with the perfect content and make it easier to create a truly personalised learning program.
Machines adding the personal touch into learning – who would’ve thought it?
Keep an eye out for plenty more entries into our Online Learning Glossary over the coming weeks!
And if you’re looking to put together a massively successful online training programme, then you’ve come to the right place! Download your free Engagement Engine Workbook to map out a strategy which uses gamification, social and personalised learning: