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It started with a class.

When Tim McKay, Arthur F. Thurnau Professor of Physics, Astronomy and Education at the University of Michigan, announced his Coursera MOOC (massive open online course) entitled “Practical Learning Analytics,” those of us at Northwestern who’d seen him speak on the topic were very interested. The work Dr. McKay has done at Michigan to identify trends in classroom outcomes is so compelling that many other universities are getting on board with the initiatives he’s started.

Rather than simply take the course, Academic and Research Technology’s Bill Parod, former Director of Northwestern Institutional Research Bill Hayward, and I thought we could use the MOOC as a way to jumpstart a community of people across different areas at Northwestern with a shared interest in analytics.  We put out a call to gauge interest, thinking we might get five or six people to respond.  We were shocked when 24 people from eight departments enthusiastically replied. 

There was nothing overly planned in our approach.  Each week, we would meet to discuss the lecture and homework from the previous week.  Several times, group members presented on learning analytics work they had done in their course work or studies. 

“The best thing about the MOOC was learning how to think about the data and to start formulating questions we might be able to approach that will be of real use for our faculty and students,” said Victoria Getis, manager of Northwestern Information Technology’s Faculty Support Services.

But the experience was greater than the MOOC itself.  It was, as Associate Director of Institutional Research, Administration, and Planning Debbie Crimmins said, “very valuable to meet people across campus doing similar work.” 

When the class concluded, no one was eagerly looking for the door.

To apply what we learned, four subgroups formed to explore the following topics:

  • It’s well known anecdotally that certain courses are “obstacle courses” — those that are the pivot point for a student to declare or drop a major. One project aims to look at such courses, and the relationships between grades in those courses and declared majors at graduation.
  • Are there grade penalties in Science, Technology, Engineering, and Math (STEM) courses for women, minorities, low income, and first generation students?  How do we recognize and address them?
  • The Canvas learning platform was delivered with a cloud based data warehouse which is very basic.  Using Northwestern’s data warehousing tools, a third project will identify data, measures, and methods for visualizing the data.
  • Experimental Teaching and Learning Analytics Workgroup project: Comparing engagement and outcomes in sample Medill courses taught on-campus and online.

These projects are still in their early phases.  If you are interested in one of them, or have additional topics you would like to explore, consider becoming part of the small but passionate community of learning analysts at Northwestern.  We welcome the company.