How to Optimise Learning Experiences? 3 Advanced Methods

Good and effective learning is not just about the content. Rather, it’s the sum of content, user experience and fit-to-purpose that defines the success of a learning experience. Nowadays, as we develop digital learning experiences, we need to pay increasing attention to how everything works. Frankly, there’s a lot of factors to take into consideration. Luckily, the prevalence of digital and web-based tools brings us the capability to optimise learning like never before. Therefore, we summed up three different methods for optimising learning experiences.

1. Using A/B testing to discover the best design or content

If you’ve ever done digital marketing, or UX design, you’re probably familiar with A/B testing. The underlying idea of A/B testing is to try out two versions of a piece of content or design, and measure the response. To optimise a learning experience, we could for instance measure:

  • Whether a text element or video conveys the required information faster
  • Which typeface/colour scheme/structure creates the most positive response
  • Task performance after using immersive simulations vs. a conventional e-learning module
  • Ease of use of navigation and user flow between two different design versions

By comparing different options with each other in live use, we can get a lot of data. This enables us to optimise the learning experience and get a little closer to the best solution. However, while A/B testing is a good tool, use it wisely. You should always make sure you’re only testing one variable at a time. Otherwise, you can’t be certain of the contributing factors.

2. Using web analytics to optimise the learning experience

Just like with A/B testing, if you’ve been involved with marketing, you’re likely familiar with web analytics. Nowadays, as a lot of the learning platforms out there are in fact “websites”, we can leverage web analytics to understand how a particular platform is being used.

The most famous web analytics tool is probably Google Analytics. But it’s not really about the tool itself, but rather how to use the data it collects. Some traditional web analytics data that can be used to optimise learning experiences include:

  • Device information. How many of the learners are using mobile? What about tablets? Desktop?
  • Bounce rates. How many learners don’t go beyond the first page? Where do they exit?
  • Time of usage. When are learners engaging on the platform? Are they learning during the workday or on their free time?
  • Frequency. How many times have your learners visited your platform? Are they coming back?

All of these data points, and many more, help us to further optimise the learning experience. While these types of web analytics are handy, you may also consider xAPI compatible platforms and analytics. The advantage of xAPI is that whereas e.g. Google’s data is largely anonymised, xAPI lets you drill down to the level of individual learners, and all their interactions within the platform.

3. Using heatmaps and user recordings to understand the flow of the learning experience

A handy new tool in the analytics space is the “heatmap”. While these tools collect largely similar type of data to web analytics, they go slightly further. With these types of heatmaps and user recordings, we can find out for instance:

  • The scrolling behaviour of our learners
  • Mouse movements / taps / clicks
  • The “flow” within the page or learning activity

This type of information helps us to further address problem areas, as we’ll know exactly where the learners tend to pause (perhaps there’s an unclear explanation?), where they progress to (does it happen linearly or as intended?) and how they flow through the activity. For instance, you might find out that only 25% of the learners reach the piece of content you spent a lot of time on. In such case, you might want to rework the activity.

Final words

Learning design as a process is becoming much more agile. We can no longer justify developing large amounts of content or designing in a specific way without validating the assumptions with data. By working to optimise learning experiences, we ensure that learners receive the right resources in the right way, which greatly contributes to their learning success. While the above are great methods and tools for optimisation, you can do quite well even with more traditional means, e.g. surveys or focus groups. In the end, it’s all about getting the right data and letting it guide your decisions.

If you’d like to explore more agile or learner-centric ways of designing workplace learning, feel free to drop us a note. Let’s optimise your learning experiences together!

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