As organizations increasingly adopt cloud-based xAPI implementations to track and analyze learning experiences, understanding the associated costs becomes crucial.

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

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.

At the recent GIFTSym11, we presented recent applied research regarding the similarities between the function of AI-enabled intelligent tutoring systems and the process of Learning Engineering.

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.