Sometimes, you want to define relationships. Other times, you want to add context. When describing time, direction, location, and spatial relationships, we depend on prepositions. But that’s been a difficult task in the realm of xAPI.

Until now.

Meet xAPI Prepositions — a set of 150 machine-readable xAPI concepts delivered in a conformant xAPI Profile.

Track video engagement during offline learning experiences with the new xAPI VLC plugin capability from Yet Analytics. Distributed under the GNU Lesser General Public License, it provides the ability to track activity and generate xAPI data directly from VLC Media Player.

Announcing the inaugural publication of YetToDiscover — the Learning Data Management Report and Catalog from Yet Analytics.

Every training event could be represented in a digital data profile.

The Experience API (xAPI) has transformed the landscape of learning technology, enabling the capture of diverse learning experiences across various platforms. However, designing xAPI Profiles has traditionally been a cumbersome and labor-intensive process.

As an Apache 2.0 open source Learning Record Store built on SQL, our LRS provides significant advantages in terms of deployment, integration, and data querying capabilities.

xAPI implementation has become even easier for U.S. Federal Government stakeholders. A Certification to Field (CtF) has been granted for SQL LRS on USAF’s Platform One.

Reactions is a method of applying conditional logic to things happening within SQL LRS.

Reactions — the first xAPI-based assertion generator built directly into a Learning Record Store.

One of the most interesting aspects of xAPI is the ability to model time.

It makes sense that when looking for a technology solution, you’d start by looking at technologies. But xAPI is — in many ways — less about technology than it is about process, design, and problem solving.

For the last few years, we’ve gotten a steady stream of calls asking us to design xAPI Profiles for business needs. Eventually, we thought to ourselves — what if we just gave people the power to author xAPI Profiles themselves?

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.

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