There are many xAPI implementations that have been invested in over the last few years that for one reason or another are now in need of an update and you find that you need to move from one vendor’s LRS to another. But what do you do about all of that data that you’ve collected?

One of the most frustrating things about xAPI is that it is difficult to gauge how much an implementation is going to cost. In order to account for xAPI statement size, volume and throughput, and data design quality when pricing an xAPI solution, we recommend building a synthetic data set representative of the data that you expect to run through your system.

Whereas an xAPI data statement describes an action or activity, xAPI Profiles combine xAPI data statements to describe experiences. They are fundamental to unlocking the power of xAPI. And they are notoriously difficult to design. Fear not. We’ve designed a presentation to help you to understand how to design perfect xAPI Profiles.

We recently wrapped up a project that offered teams building a dozen different Unity-based extended reality (XR) applications the ability to have engagement data from each application populate a mission-control style engagement dashboard in real time. So rather than one team / one dashboard, the goal here was all teams / one dashboard.

In the same way that Learning Engineering itself is developing into a sort of bridge between these disciplines in the pursuit of scaling meaningful and measurable learning experiences, likewise, as a data broker between the worlds of synthetic training and distributed learning analytics, GIFT serves as a sort of AI-enabled technological bridge.

April 2023 — Yet Analytics is looking for a curious and solution-oriented full stack software engineer to help us build cutting-edge learning data products and open source offerings.

With an objective to provide “a data strategy for measuring the longitudinal impact of synthetic, semi-synthetic, and live training experiences on individual and team competency development,” STEEL-R brings together a variety of standards-based capabilities from the world of synthetic scenario design with the core standards-based capabilities of ADL’s Total Learning Architecture (TLA).

Within a research context, there is a need for large and relevant activity data sets to test hypotheses regarding competency assertion. But where do these data sets come from?

In this webinar hosted by the Advanced Distributed Learning Initiative, Shelly Blake-Plock reviews best practices in xAPI-related cybersecurity and talks about the development of a new IEEE standard to support the secure implementation of xAPI.

If xAPI is the way to describe and track learning activities, xAPI Profiles is the way to describe and track learning experiences. Check out this recorded webinar from the xAPI Cohort to learn all about the power of xAPI Profiles.

Open Source for the TLA. Including: Learning Record Stores and xAPI Filters for TLA business logic

We asked, and this is what you had to say. So without further ado, here are the top five things we learned from all of you about SQL LRS.

Yet Analytics has released two new open source libraries for xAPI Profile validation. The first is called Pan and is used to validate xAPI Profiles. The second is called Persephone and is used to validate xAPI statements against xAPI Profiles. Both libraries are distributed under the Apache 2.0 license.

Join us in securing xAPI’s future. The IEEE P9274.4.2 working group on xAPI Cybersecurity meets monthly.