Data

In an opinion piece for The Tech titled OpenCourseWare and the Future of Education, Ryan Normandin lays out MIT OCW’s funding breakdown. It’s the first time I’ve seen the numbers shared publicly. He begins by stating that MIT OCW’s budget is $4.1 million per year (though he notes that OCW cut $500,000 in costs for 2009), and then analyzes revenue by source: Since its creation, 22 percent of OCW’s expenditures have been covered by the Institute, 72 percent has been paid for through grants from the William and Flora Hewlett Foundation and the Andrew Mellon Foundation, and 6 percent has been covered by donations, revenue, and other sources. ...

I’ve always been impressed by the idea of the Large Hadron Collider. It’s an unthinkably expensive, large-scale experimental apparatus designed for the sole purpose of generating and collecting data. Why would countries spend so much money on data? Why would so many people dedicate the better part of their lives to a project like the LHC? Because the so-called “hard” sciences - fields like physics and astronomy - have made the remarkable progress they have in understanding the structure of matter and the nature of the universe because they really care about data. They care about data in a way that educators have a difficult time comprehending, let alone understanding. ...

Two exciting bits of news from the ongoing BYU Independent Study OCW trial. There’ll be loads more data / graphs / etc. in our presentation at Open Ed 2009 next week. First, things seem to be remarkably stable on the “conversion to paying customers” side of the study. Out of 9179 visitors to the OCW site, 270 have become paying customers of BYU IS (that’s 2.94%). This number is sticking right around 3%. ...

A student of mine, now DOCTOR Sean Duncan (congrats again!) has posted his excellent dissertation studying reuse of OERs online under a CC-BY license. This was one of the most enjoyable dissertations I have ever chaired. I’ll cover highlights below, but I encourage you to check out the full text of Patterns of Learning Object Reuse in the Connexions Repository for yourself. The study examined patterns and amount of reuse within the Connexions OER repository at Rice. CNX seemed like a great choice for examining reuse because the system is built specifically to support both adapting individual modules and remixing individual modules into courses / collections. Importantly, through system metadata that CNX also makes openly available, all these relationships can be explored programatically in a straightforward way. So CNX is in many ways a best-case scenario for studying reuse, adaptation, and remixing. ...

There’s an excellent article over on Wired right now with interesting implications for our field. The End of Theory reads in part: “All models are wrong, but some are useful.” So proclaimed statistician George Box 30 years ago, and he was right. But what choice did we have? Only models, from cosmological equations to theories of human behavior, seemed to be able to consistently, if imperfectly, explain the world around us. Until now. Today companies like Google, which have grown up in an era of massively abundant data, don’t have to settle for wrong models. Indeed, they don’t have to settle for models at all… ...