Recently, I used the customGPT xAPI Reporting Assistant to analyze 1.8 million xAPI statements from a busy month of learning activities. We built our courses with Articulate StoryLine, utilizing its built-in xAPI reporting to an LRS.
What I discovered was significant, especially regarding the data structure of xAPI. While StoryLine’s handling of xAPI isn’t wrong, it lacks the customizability needed for enhanced learning analytics.
Years ago, I created a simple JavaScript library for use in StoryLine post-published courses. It allows you to call a function on a JavaScript trigger to build xAPI statements. I’ve recently revisited and updated this library, which is now available on GitHub for those interested in contributing.
The library currently supports Play and Pause verbs for video, and I’m working on adding the correct Video Profile structure soon.
For those using xAPI and StoryLine, or seeking better learning analytics, I welcome your thoughts and contributions. Once you get your xAPI structured and you want to report on it, use the tool at xAPI AI (https://xapiai.com/) to connect to your Learning Record Store (LRS) and fetch your xAPI, then upload the file to the customGPT xAPI Reporting Assistant to analyse your xAPI data.
Check out the GitHub Repository at https://github.com/juliandavis-xapi/StoryLine-xAPI-JS