Learning-Analytics

I finally finished my brief statement on learning analytics for the panel I’m participating on at LAK12. Since I had to write it, I’m publishing it here. Perhaps it will put you to sleep; perhaps it will inspire you; perhaps you’ll experience an unexplainable pining for the fjords. Either way, here it is. As part of his 2 sigma work, Bloom (1984) challenged educational researchers to devise practical methods – “methods that the average teacher or school faculty can learn in a brief period of time and use with little more cost or time than conventional instruction” – that would help learners reach their academic potential. My personal interest in learning analytics lies in its potential to answer extremely practical and socially responsive questions such as, “What is the most effective thing a teacher could do with her next 30 minutes?” and “What is the most effective experience a learner could choose next?” In my view, learning analytics as a term simply describes the extremely interdisciplinary endeavor of providing this pragmatic support for learning. ...

As interest in badges continues to increase, it occurs to me that in their passion for gameification, innovation, and outright reinvention, many in the field are overlooking the place where badges make the most sense of all - the formal higher education institution. There are at least two high-level reasons why higher education is the perfect place for badging. First, universities are under ever-weightier mandates from accrediting agencies to (1) specify specific learning outcomes for courses and (2) gather and utilize data about student performance on these individual outcomes. Currently there is quite a bit of conversation - more frantic the closer your department is to an accreditation visit - about how to meet these external mandates. There are pedagogical, policy, political, social, and technical aspects to this question (among others). ...

I recently blogged about the Apple announcement and how it amounted to publishers ceding the “traditional” textbook market (whether print or digital) to OER makers. One way to interpret that concession is as a win for open education. And it is a win - temporarily. Another way to interpret the concession by publishers is to see it as electronics companies ending production of VCRs and doubling down on DVD players. In my previous post I asked, “If video-based, multimedia-rich, interactive textbooks are only worth $14.99 to the big publishers, what are relatively static, text-based books with a few photos worth to them?” Think about that for a minute. Sure, there are “traditional” OER textbooks available for free. But when you could have video, multimedia, simulations, and interactive assessments for $15, why would you take a traditional book (whether print or video) even if it is free? ...

I frequently describe openness and analytics as chocolate and peanut butter - both are tasty individually, but together their synergy is truly remarkable. Until recently we only had one example - CMU’s OLI - where this synergy was really running at full steam: openness providing permission to make improvements to curriculum and analytics providing empirical evidence about what changes are needed. (Note that neither the permission nor the evidence alone are nearly as powerful as the two together.) CMU OLI also leverages openness to increase the number of students using their material, which in turn generates more data, which in turn enables more powerful analytics, which in turn leads to better material, etc. CMU OLI’s openly available research shows the progress they’re making on using openness and analytics to improve student learning. ...

As part of my work on the NGLC-funded Kaleidoscope Project I’ve been thinking about practical learning analytics. Why “practical”? My goal with practical learning analytics is to provide access to data in ways that an average teacher, with no special training, can leverage in order to help her students succeed. This is, of course, an extremely tall order. As I began to mull over some common conventions that teachers could interpret without training (e.g., time flows left to right, scores move higher and lower) I realized that there’s already a tool available that provides visualizations like this - the Google Motion Chart Gadget. ...