Learning Analytics - What Does It Mean?

Incestuous, homogeneous fiefdoms of self-proclaimed expertise are always rank-closing and mutually self-defending, above all else.

- Glenn Greenwald

I recently attended the Learning Analytics Summer Institute sponsored by SoLAR (the Society for Learning Analytics Research) and EDM (the International Educational Data Mining organization). The event was very well organized and extremely informative, with thought-provoking panels and in-depth workshops.

I was there presenting a poster about my dissertation research. I'm interested in how students use Internet-based knowledge resources for research and learning, and I am exploring the learner x resource networks that emerge to see if the patterns of resources used can tell us anything about how well the students are learning or how effectively they're making use of those resources. To my mind, that topic fits right in with the concept of Learning Analytics, where Analytics is defined as "a method of logical analysis." The organizers of the event seemed to agree, as doctoral students had to apply and were accepted based on the applicability of the workshop to their research and vice versa.

Apparently, though, some people had a very different definition of Learning Analytics. One person asked, on the afternoon of the first day of the workshop (and after the graduate students had done a 1-minute overview of their research and presented their posters during lunch), about methods to keep out impostors. Yes, that's the actual term used. This person suggested that there were people at the workshop who could not "do" learning analytics and suggested implementing badges that could only be obtained by passing rigorous tests. (My assumption is that this person was actually focusing only on educational data mining techniques, and not on the more broad field of Learning Analytics.)

George Siemens (@gsiemens) did an excellent job of responding to this question (and veiled criticism). Dr. Siemens stated that he was well aware that there was a tension between the different fields represented at the workshop, but that he felt that tension was an asset that led to innovations and the growth of the field. I agree wholeheartedly. The best part of the workshop was the variety of research and the exchange of ideas between all participants.

If, as researchers, we want to be silo'ed and only talk to others who have the same expertise as we do, then we will miss out on new opportunities, novel collaborations, and innovative explorations. If "impostors" can bring new ideas to the table, then they should be welcomed instead of weeded out. I applaud Dr. Siemens for his tact as well as his understanding that, in this networked age, creating silos of expertise is a recipe for isolation.