Introducing Experience Paths

Completions don’t equal understanding. It’s proven every time someone randomly clicks through multiple choice questions until getting it right. What people get “right” may not provide as much insight as what they get wrong, and the routes they eventually take through content. Collecting and analyzing this kind of information has been cumbersome if not impossible, but with Wax LRS’s new Experience Paths Analysis, you’ll be able to uncover the hidden patterns in your learning data.

Gaining knowledge and developing skills aren’t linear processes. People going through learning activities may retrace content, skip optional components, access resources, and even start over and select different options. Experience Paths aggregate that information and give you a high-level snapshot of those flows in an easy-to-understand interface. It’s an interactive visualization that lets you filter and target people’s paths through content to help you answer specific questions.

This visualization helps identify the places people stumble, the parts people are avoiding, the frequency of restarts, and other events that can provide rich context to your learning data. You can even see the paths specific people are taking just by hovering over their name in the right pane. This feature works with the output of several popular authoring tools (really any authoring tool that sends xAPI registration data and includes parent activities). This is most useful when there’s sufficient branching and options for people to take, like a simulation or practice activity where they have to make choices.

As participants engage in learning experiences, Wax LRS captures their activity and illustrates the natural flow through content. It detects backtracking, optional content that is rarely used, the access of embedded resources, and unexpected learning barriers.

In the image above, you can see how many people are progressing between steps in the experience by hovering over the appropriate line. Meanwhile, the lines on the left side of the table show the flow of people backtracking to a previous step. Altogether, you will get a clearer picture of how people are arriving at a given behavior, and what they do after they reach it.

Experience Paths also give you the ability to isolate specific workflows by alt-clicking a step or path line to only show the paths people take exclusively. In the above example, everyone that correctly answered a knowledge check have been removed, leaving only those that answered incorrectly in the table. What steps or resources did these people tend to miss in their experience? Where did they go afterwards in order to get the necessary information? Who are the people who have taken a specific path? Where was there sufficient backtracking and skipping? Why and when are people accessing optional resources to help them progress through the content? Experience Paths can show you, quickly and cleanly.

The impact of Experience Paths can be far reaching and fruitful. Companies can improve employee learning experiences where there’s sufficient confusion or offer supplemental training and resources to people who are taking a certain path. People taking exemplary or unexpected paths can be identified and recognized or better supported. You can answer specific questions about people’s learning experiences in much greater detail and with higher certainty.

Experience Paths Analysis identifies what works, what doesn’t, and gives you the opening to act on it. In short, it empowers you to design more effective learning experiences.

Experience Paths Analysis is available right now in Wax LRS site, if you are on a paid monthly plan or the new free “Explore” plan. Give it a try, play around with it, and see what patterns are lurking in your data. If you’d like to learn more about the feature or give us any feedback, please leave a comment below or drop us a line.

We’d like to thank Sara Walters for partnering with us to develop this visualization. She provided the xAPI published CRM simulation training developed in Storyline and provided her exceptional instructional design expertise to improve the user experience.

Originally published at on October 16, 2015.