By this stage, we’ve all gathered that presenting all employees with the same training material just doesn’t get the job done. Your workers are different. They learn differently, have different needs, and draw on unique experiences.
What I’m getting at here is that “one size fits all” usually fits nobody.
So, what’s the solution? The best way to guarantee your staff training actually works is by investing in adaptive learning.
Adaptive learning is all about looking at how individual learners behave, their skills, and how efficient they are as learners. You can do this by gathering info like learner data and clicks, as well as by analyzing how people interact with the platform you’ve provided them with.
So if your organization isn’t seeing the training ROI or behavior changes you want, it may be time to jump on the adaptive bandwagon. Keep reading to discover:
- What is adaptive learning?
- The benefits for businesses and employees
- Examples of adaptive learning in action
What is adaptive learning?
Adaptive learning provides students with tailored training experiences through personalized learning paths, AI-driven analytics, and just-in-time feedback. It uses data to design learning experiences that meet trainees’ individual needs and goals.
Here’s how that looks in an employee training environment, say your onboarding program:
Employees begin the onboarding process by answering questions about their previous experience and skill set. An adaptive learning platform can then analyze their answers and adjust the onboarding training content they receive accordingly.
Some employees may be looking for additional support or resources, while others won’t.
An example would be OKRs. While junior employees may wish to see a training video on what they are and how they work, senior managers typically won’t.
The platform’s AI can also push training material based on how employees perform on a quiz or other learner behaviors.
The result is a more personalized and efficient learning experience that focuses on what the employee needs.
Benefits of adaptive learning in employee education
When you think about employee training, “streamlined” and “effective” aren’t the terms that usually pop up.
An adaptive training approach can change that:
1. Identifies knowledge gaps
The thing (or should I say one of the things) about cookie-cutter training is that it doesn’t give you the full picture.
Employees can fly under the radar pretty easily, and unless you’re going through your LMS reports with a fine-tooth comb, it’s easy to miss skills gaps.
Adaptive learning solves this problem.
AI-powered analytics and detailed learner feedback enable you to drill down and see where employees require more training. You can also see performance trends across different topics, which helps determine which skills gaps are most widespread.
That way, you can react and plug those gaps before they impact performance.
2. More detailed learner data
Speaking of data, adaptive learning platforms give us plenty of insight. Guesswork is rarely effective when it comes to understanding our employees’ needs, wants, and pain points. This is no different in a learning context.
Adaptive learning tracks learner data on a deeper level, aggregating essential pieces of info so you can get a real feel for where your learners are.
Not only is this essential for plugging knowledge gaps, but it also gives you a proper idea of who your learners are and how they behave.
Knowing this is worth its weight in gold when planning future training programs, tweaking current ones, and avoiding unnecessary work.
3. More personalized learning experiences
Following on from our second benefit, having access to deeper learner analytics and feedback helps us design more personalized training programs.
Why does this matter?
Well, 93% 1 of high-performing companies confirm that personalized training increases learner engagement, supports employees as they meet their career goals, and garners higher knowledge retention rates.
Adaptive learning lets us tap into what trainees really need and the best way to give it to them. And by creating bespoke learning experiences, we set ourselves up for a number of other benefits (more on that below).
4. Enables self-paced learning
Since adaptive learning creates a more individualized training experience, employees are better able to go through it at their own speed.
When we consider the audience – busy professionals with a million tasks to do – self-paced training is a dealbreaker.
With this approach, learners can choose their own journey through the training material, spending extra time on the areas they struggle with (or find more useful).
All in all, this leads to a more accessible and pleasant experience for learners.
5. Higher learner engagement
The ability to gather more comprehensive learner data leads to a number of pretty juicy perks. Let’s start with one that’s music to every instructional designer’s ears: learner engagement.
You can know all the best instructional design models and best practices in the world. But if your training isn’t relevant, learners are going to switch off.
Adaptive learning combats this by ensuring your training material aligns with learners’ knowledge levels, goals, and job roles.
They won’t have to aimlessly click through slides of content they already know, nor will they struggle their way through assessments that are just too difficult.
The more personalized the training is (thanks to data analytics), the more engaged your employees will be.
That leads us to our final benefit.
6. Better training outcomes
At the end of the day, as much as we want learners to enjoy the experience, what we really want are results.
Employee training is about solving real-life performance problems and preparing staff with the skills to advance their careers.
So how can we get them there?
Well, the truth is that we can’t.
But before you throw your hands up in despair, we can still do plenty to lead them there.
We’ve already seen how adaptive learning boosts engagement by delivering targeted training content. Now let’s see how that can impact employee performance.
There’s plenty of research that confirms that when learners are engaged with training, they retain knowledge better.
As a result, they’re better equipped to apply new concepts to their jobs and make those desired behavior changes (the whole reason you created the training in the first place).
In other words, adaptive learning can facilitate better training outcomes, which translate into higher on-the-job performance.
There’s no denying the pros of adaptive training techniques, but they have limitations and challenges, too.
Namely, it requires buy-in from stakeholders, strong data analysis skills, and technologies to facilitate it. While none of these is an impossible ask, it’s not an overnight solution by any means.
Examples of adaptive learning
Here are three examples of organizations that use adaptive technology and techniques to create world-class learning experiences.
Duolingo
Duoling is a free app for learning languages. Learners complete bite-sized classes and earn points as they go.
It also uses AI to adapt lessons to each learner’s level and pace.
Learners begin their journey by completing an assessment to gauge their current level. Duolingo then uses this data to create a personalized learning path and a starting level.
As learners move through the lessons, Duolingo’s AI identifies weak areas and common mistakes, integrating regular built-in reviews.
Learners get weekly performance updates based on this data to keep them motivated and to mark their progress.
LinkedIn Learning
LinkedIn Learning is one of the most popular learning platforms out there. And the reason behind this popularity is the personalized learning experiences it offers.
Learners can choose from over 16,000 training courses, creating their own skill paths depending on their career goals.
While it doesn’t take a fully adaptive approach, it does use data to create personalized learning paths and track progress.
It differs from a fully adaptive learning model in that it doesn’t specifically adjust the learning content or pathway based on user performance.
Instead, the LinkedIn Learning algorithm auto-suggests courses based on the skills learners want to learn and their professional aspirations.
The interactive exercises and quizzes complement the video lessons for higher engagement and supplemental resources are available for learners who need them.
Khan Academy
Khan Academy is a nonprofit organization that provides free education to learners across the globe.
The Khan Academy also borrows some core adaptive techniques to better serve its students.
For instance, it offers adaptive assessments to ensure learners only progress through instructional materials when they have demonstrated their mastery of the subject.
It also uses adjustable learning paths based on students’ performance, assigning targeted exercises for both high and low achievers.
Its knowledge maps closely monitor learner performance, so instructors can provide the most relevant materials based on that individual student’s needs.
Next steps
- Adaptive learning acknowledges the fact that training is best served in a personalized setting.
- It leverages AI and technology to pull detailed data on what learners know, how they interact with training, and their needs.
- Then, it uses the findings to adjust training content to suit learners’ unique requirements and goals.
The result is more engaged learners, better training outcomes, and less time wasted on creating ineffective or unnecessary training.
Want to learn more about instructional design? Browse the blog.
By Nicola Wylie
Nicola Wylie is a learning industry expert who loves sharing in-depth insights into the latest trends, challenges, and technologies.
- https://www.peoplemattersglobal.com/amp-training-development-are-employees-really-busy-or-are-your-learning-programs-disengaging-33155 ↩︎