6 Minutes of reading
Is adaptive learning the future of professional training?
After a turbulent few years, many of us have changed the way in which we work. The kitchen table is taking the place of the traditional office, and today’s employees are often either working solely from home or in a hybrid arrangement. To meet the needs of a more mobile workforce, professional training is having to adapt. One solution that is growing in popularity is adaptive learning.
It’s not difficult to see why adaptive learning has caught on. Thanks to this system, companies can offer personalised training courses that evolve over time to meet individual needs. This encompasses both the order in which employees take certain modules and the content they see. What’s more, adaptive learning is improving all the time, and now offers more accurate recommendations than ever before. This raises an important question: is adaptive learning the future of professional training?
Introduction to adaptive learning
The idea behind adaptive learning is that each employee should undergo training tailored specifically to them. This includes personalisation according to their existing knowledge and abilities, their needs and goals, and more information about them as an individual.
In traditional educational models, a single teacher is in charge of imparting their knowledge to a room of learners. The problem is that this fails to take into account each individual’s preferences and skill level. Adaptive learning moves away from this and towards a more targeted, personalised approach.
All of this is made possible by software such as LMSs and LXPs, which collects information about each learner that adaptive learning algorithms are then able to interpret. It’s also often referred to as data-driven learning due to its use of data analysis to provide accurate recommendations.
One of the best parts of adaptive learning is that it automates what were once time-consuming tasks. We’ll take a closer look at this below.
How does adaptive learning work?
A tech-enabled approach to training
A couple of decades ago, the idea that our training programmes would be shaped by neuroscience, artificial intelligence and machine learning might have sounded like something out of science fiction. Nowadays, adaptive learning means that this is a reality, and it’s one made possible by the websites and apps we all use at work every day.
The process begins when learners use a training platform, which collects data about them and analyses it in real time. In turn, the machine learning systems that make adaptive learning possible gain a more complete picture of the learner. This includes information such as their scores on any assessments, the speed at which they learn, their history on the platform, and personal details such as their age.
Following on from this, the system starts to determine each learner’s preferences, as well as any gaps in their knowledge. It then moves on to put together a training course aimed to meet these specific needs, as well as personalising the content offered to the learner. Competency frameworks will also be taken into account at this stage.
Here, we can see one of the main benefits of adaptive learning: it constantly adjusts to meet employees’ needs, and offers educational formats and content that suit them best.
Nonetheless, it’s important to remember that not all adaptive learning software is made equal. Some offer only a basic level of personalisation that groups learners together simply by means of a single initial assessment. Others go further, taking into account each individual’s skills and cognitive abilities to put together a truly tailor-made course for every learner.
Different levels of personalisation
Adaptive learning exists in two forms: micro and macro. We’ll walk you through the differences between the two below.
Macro adaptive learning
The first variety we’ll cover is macro adaptive learning. This is a form of personalisation that sees all learners cover the same content, but in a different order. Those who already possess a certain level of knowledge are also able to skip certain modules.
As the learner progresses through the course, the system is able to detect if there are any gaps in their knowledge. If required, it can recommend that they go back and revise or redo a certain module if they haven’t properly taken the information on board.
With macro adaptive learning, all learners will eventually reach the same skill level, but will do so at their own pace. Along the way, the learning platform makes real-time adjustments to their course so as to provide them with the best experience possible. This is a great choice for longer courses involving many modules, such as learning a programming language.
Micro adaptive learning
Next, we move on to discuss micro adaptive learning. This type of adaptive learning takes personalisation to the next level by tailoring not just the course but the content itself. Put simply, each learner is offered training material that best suits their needs and requirements.
The format and content of each module and assessment is personalised so as to fit the learner’s cognitive profile. Neuroscience plays a major role in making this possible, as this form of adaptive learning relies on an understanding of the ways in which each of us think. This is a good choice if you’re aiming to teach your learners a specific skill in a short period of time.
Is adaptive learning the future of professional training?
Faster upskilling as the world of work changes
Today’s workplaces are in constant flux, with new roles and even entire sectors rapidly coming into being. Employees need to be able to adjust quickly to this ever-changing environment, all while gaining the new skills they need to be able to perform at their best. Adaptive learning is the perfect tool to meet these challenges.
By personalising training to suit each individual, businesses reap the benefits: employees are more motivated to learn, gain new skills more quickly and retain them more effectively. This in turn makes the entire training process more efficient—a clear benefit of adaptive learning systems such as Rise Up.
Better still, there’s plenty more on the horizon for adaptive learning, which is only just beginning to come into its own. With progress being made constantly in this field, this approach to professional training offers exciting new possibilities. As the full potential of adaptive learning becomes clearer than ever, businesses are seizing the opportunity now.
Can adaptive learning do it all?
The benefits of adaptive learning are more than apparent, and it’s certain that this approach will play a major role in the world of professional training. Nonetheless, it is at its most effective when used alongside other educational methods to provide learners with a diverse and well-rounded training experience.
One key issue is the lack of human interaction that takes place within adaptive learning. Largely automated and reliant upon data and algorithms, it cannot alone make up the entirety of an employee’s training programme. After all, we learn best when we discuss and communicate with those around us. Whether we’re modelling our behaviour on that of a trainer or working in a group, social settings are key to gaining new skills.
Moving forward, adaptive learning will be an important part of the world of training, but must be complemented by face-to-face sessions and other learning methods. Blended learning is the way forward—and it’s made possible by systems such as Rise Up.