How do you measure microlearning?

Learning and development (L&D) professionals have been dealing with problems measuring the effectiveness of their programs for decades. Does this sound familiar?

First, you schedule people out of the operation to attend a class or complete an eLearning module. Then, to get to level 1 (reaction) measurement, you have to send them a survey and hope they respond. To hit level 2 (learning), you give them a test, but this only measures their knowledge at that specific moment in time. If you hope to achieve level 3 (behavior), you have to ask managers or trainers to schedule extra time for observations at specific intervals after the training event. By the time you even think about level 4 (results), the business priority has changed, and your focus is needed on the next project.

Most L&D pros can’t get past level 2 of the Kirkpatrick Model because measuring a traditional learning program takes SO MUCH effort. This is why so many L&D heads rest their reputations on weak metrics, like participation satisfaction (we got a 4.6 out of 5!) and test scores (if someone gets a 85%, what happens to the missing 15% when they get back on the job?).

Microlearning is built for measurement

Microlearning solves the problems with traditional measurement. In fact, meaningful measurement is one of the main reasons you should be considering the approach in the first place. Take a look at our microlearning definition:

Microlearning is content delivered in short, focused bites. To be effective, microlearning must fit naturally into the daily workflow, engage employees in voluntary participation, be based in brain science (how people actually learn), adapt continually to ingrain the knowledge employees need to be successful, and ultimately drive behaviors that impact specific business results.

I previously addressed the question, “How long is microlearning?” by explaining that the focus on a single topic is what makes it short. Focus is also what makes microlearning so measureable. It’s all about starting with the end in mind through a results-focused approach to content design.

Before you build a learning program, you have to know what problem you’re trying to solve. Is it increased sales? Decreased workplace injuries? Improved customer satisfaction? This result is already measurable because it’s tied to your business KPIs (key performance indicators).

Next, you must determine what employees will need to do in order to achieve the desired result. Define what good performance looks like so it can be easily assessed after training. You can then use behavior observation to determine if knowledge has transferred onto the job. When your learning takes a continuous approach, and isn’t based on a single event, this observation can be naturally embedded into the workflow. For example, if managers are already expected to coach employees on their performance, you are simply adding a means to capture these existing observations so the data can be used to improve the overall learning experience.

To change their behavior, employees must have foundational knowledge on the topic. They can’t do if they don’t know. Knowledge can be assessed through questions embedded in daily training sessions. This gives you a real-time understanding of what employees know and don’t know, which is a considerable improvement from one-time, post-training tests.

As you can see, this results-first approach not only helps you make the right decisions regarding content development, it also provides you with a measurement strategy. As employees learn, you can continuously measure their knowledge growth, behavior improvements and, ultimately, business results. And, if you want to go next level, you can also use machine learning to attribute the impact of training on those changes in your business.

The ultimate purpose of training is to solve business problems. You will only know whether you solved the problem if you can measure it. A modern approach can help you break free from the limitations of traditional measurement models and finally connect employee knowledge, behavior and results.

JD Dillon, Chief Learning Architect

JD Dillon became an expert on frontline training and enablement over two decades working in operations and talent development with dynamic organizations, including Disney, Kaplan and AMC. A respected author and speaker in the workplace learning community, JD also continues to apply his passion for helping frontline employees around the world do their best work every day in his role as Axonify's Chief Learning Architect.

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