Editor’s Note: I am pleased to announce that Bill has agreed to continue contributing blog posts from time to time. Therefore, he is now officially a “Featured Blogger” rather than a “Guest Blogger.”
Last week, I had the privilege of speaking at a workshop on online graduate education. At that workshop, Carnegie Mellon University Provost and Executive Vice President Dr. Mark Kamlet used the words “Learning Engineering” in his keynote which I built upon in my talk. In my previous post I referenced the need of semantic data and algorithms to support learning engineers to create and iteratively improve courses and courseware (among other things). I felt it was worth taking a little time to describe just what I believe that means.
For over 10 years, the Open Learning Initiative has been bringing together teams to develop online course materials. Carnegie Mellon is an ideal place to cultivate this work due to its multi-disciplinary programs and culture aside from its expertise in the related fields. During that time we’ve built a team of experts that are critical to the building of learning environments informed by research and capable of recording data for iterative improvement as well as creating dynamic reports for stakeholders.