The flexibility of the xAPI specification is both its biggest strength and its greatest weakness. It's a strength, because xAPI is flexible enough to be used to track any type of learning experience, including those that have not been invented yet. In a world of rapid technological advancement, that's a vital trait. But it's also a weakness because that same flexibility opens the door to variation in how xAPI data is structured and the vocabulary used to describe different tracked events. As an organization, there's a risk that as you start to collect data from more and more sources involving more and more different people, these kinds of variation can creep into your data—making it much harder for you to report on that data consistently.

In this session, you'll learn the importance of creating, implementing, and maintaining an xAPI governance strategy. You'll explore how rules and processes provide a baseline so everyone in your organization knows what's right and what's wrong when it comes to data structures, formats, and vocabulary. You'll also look at why and what you should document to ensure future implementations follow a similar pattern. Next, you'll explore how to test, monitor, and enforce your rules and processes—which is vital, as the more data sources and people involved in your learning ecosystem, the more likely someone is to break those rules and processes. From there, you'll see what you can do about bad data that's already in your LRS. Whether it's duplicated completion verbs, activity ID reuse, or another issue, you'll look at some options to help tidy up when things go wrong. Finally, you'll explore flexible tools and options for technology that can help you work with imperfect data, reducing the impact of xAPI governance failures.

In this session, you will learn:

  • Why xAPI governance is vital to ensure the quality of your data
  • How to apply best data governance best practices to keep your data tidy
  • How to use tools and technology to clean up and maintain good data
  • How to create and document data governance rules and processes
  • How to test, monitor, and enforce those rules and processes
  • How to correct any existing bad data

Technology discussed in this session:

Learning management systems, learning experience platforms, video platforms, learning record stores, credentialing tools, authoring tools, learning analytics platforms