Do you have the right data to make adaptive learning work?

We’ve said it before, but I’ll say it again here: If your approach to microlearning isn’t adaptive, you’re only halfway there. These two strategies go hand-in-hand and place one important, common element at the very center: the employee.

Group of diverse employees

Adaptive learning is a key component of an overall microlearning strategy because it’s the part that captures and analyzes learning data continuously to truly personalize content to the individual—and this is absolutely crucial for providing impactful training for your employees. Why? Because the one-size-fits-all approach simply falls short. It doesn’t provide the training employees really need to overcome their own weaknesses and build on their strengths. Because of this, it doesn’t help the business target and overcome problem areas, let alone engage employees. But if you need further convincing, have a look at the recent research results from The State of Workplace Training report.

Adaptive learning starts with the employee

Truly effective workplace training should have one consideration at the very heart of every approach—the employee. Organizations need to enable their employees, their people, to solve business problems. But first, you have to understand everything there is to know about an individual to inform what kind of training they actually need. And, as we know, providing the right support will result in the right actions to drive your business forward.

In the Making Sense of Adaptive Learning webinar, Chief Learning Architect, JD Dillon offered up a simple, high-level definition of adaptive learning that’s applicable to many circumstances and industries:

Adaptive learning definition: Using everything we know about a person to provide a personalized, targeted, value-add support experience

For the purpose of today’s post, we’re going to focus on the employee by zeroing in on the first part of this definition: “using everything we know about a person” and the kinds of data gathering that’s necessary in providing and supporting a valuable training experience.

Sure, the concept of compiling employee data isn’t anything new. Many companies already collect all sorts of data and may even have learning management systems (LMSs) that help with this. But, as JD explains in the webinar, learning leaders must evolve beyond simple learning data or learning analytics that just focus on completions and test scores. It’s time to progress. If you want to provide more relevant training that suits today’s demographic and fast-paced industries—then you must advance, and that includes evolving the data profile of an employee.

6 key employee data points to build an adaptive learning experience

To develop a multi-dimensional data profile for your employees, JD suggests capturing six key areas of data to provide a more holistic, meaningful picture of the employee. Some data you may already be collecting, and some you’ll have to find a way to capture. This data can then be used to ask better questions and determine what kind of targeted training an employee needs to achieve success.



Let’s start with the easy one. Who is this person? What job do they have? When did they get hired? Who do they work for? What department are they a part of? You probably already have a lot of this information stored internally. All of these basic, but fundamental elements are the foundation of an employee’s data profile that you can continue to build on.


An employee’s past experiences also play an important role in shaping their performance. This means the training they consume now is just as important in influencing future on-the-job behavior as training that they received in the past. What kind of activities has this person engaged with? What kind of content have they consumed? This information isn’t enough on its own, but JD explains there’s value in understanding an employee’s consumption pattern. Take notice the next time you’re online, browsing. We’re targeted by these types of data-driven recommendations on the internet every day.


Context data can’t be tracked through traditional systems like an LMS. This kind of data takes into account the surrounding environment of the employee. What is happening around this person that could inform what they need from a learning and performance perspective? Maybe a shift in leadership or team structure? Potential layoffs? Understanding all the factors that could be influencing a person can better inform what kind of support they need to perform.


I know, we’re really trying to drive this point home but it’s important to keep in mind—the employee sits at the center of truly impactful training. So, by having a channel in which a person can communicate their preferences and opinions on what they need to be successful, you’re providing an opportunity to help them inform and shape their own training experience. What information or content did they enjoy engaging with in the past? What did they find to be valuable, or not? Providing opportunities for an employee to provide input into their profile provides valuable performance insight.


This is different than test scores. Here’s where we look at employee knowledge growth and gaps. But, in the webinar, JD described how this means more than just testing an individual at a particular moment in time. We need to measure knowledge continuously. If you got a great score on a test in school, it’s probably because you spent time studying for it. But what if you were tested on that material a few weeks later? Things might not play out the same way. So, are people retaining the knowledge they need to influence behavior positively? Is knowledge declining in a critical area that needs targeting?


Behavior data informs how an employee’s knowledge translates into real world actions. How does s/he behave on the job? Does s/he take the actions necessary to help drive business results? This kind of data can be tracked through observing employee behavior on the job, say in a retail environment, or through other mechanisms like recording and evaluating calls in a contact center.


Last, but certainly not least—results. What is this person achieving? Is Joe from sales hitting his quota? Is Maria from the shop floor practicing the proper safety procedures? Is Jamie bagging the customers’ groceries properly and delivering service with a smile? This data provides insight into whether or not employees are learning what they need in order to make the right decisions and perform the kinds of actions that will drive your business forward.

So, coming back to the first part of our definition for adaptive learning—this is the type of data that is necessary for rounding out an employee’s data profile and providing a more holistic view of ‘everything we can know about a person.’ And, it is critical to the adaptive learning experience.

We’re not going to lie—a true adaptive learning experience can’t be accomplished without the help of technology. And, to be blunt, Axonify is the only platform out there that can provide a truly adaptive continuous learning experience. We’d love to explain why, so please contact one of our experts to learn more.

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