What is a retention early warning system? What is it good for? What are its limitations? And how are its failings representative of the unfulfilled potential of so many ed tech products? You’ve got questions, we’ve got answers.
In this post, I explore the relationship between learning engineering and learning design, talk about language as a design artifact, and provide an example about how Caliper could be the centerpiece of a learning engineering process for developing better learning analytics.
One of the challenges facing higher education is a huge amount of tacit knowledge—things that we don’t know we know—about both our academic expertise and our teaching expertise. We need to make that knowledge explicit in order to make progress. This post unpacks a peculiar kind of literacy problem.
Eleven months ago, I wrote a post about Instructure entering its “awkward teenage years.” That was a setup for the inevitable alternative metaphor that was coming, along with Instructure’s inevitable fall from grace. Now that they’re off the pedestal, it’s time to address the crazy way we talk about ed tech companies.
The IMS has been amazingly successful. I take a deep dive into both the what and the why, and then look at how the next challenge of learning analytics is going to mean the next decade of interoperability work will be different from the last one.
As promised in my last post, I describe my model for creating a new economy of contribution and collaboration from ed tech vendors, and how I hope to pay for e-Literate (and part of my mortgage) in the process.
e-Literate is changing its URL, its look and feel and, most importantly, is morphing into a much broader organization with multiple functions. This post provides an overview of the new world.