Curricular analytics: one project and many questions
What are curricular analytics and what can they add to higher education?
Yesterday the Future Trends Forum met with Gregory L. Heileman, associate vice provost for academic administration and professor of electrical and computer engineering at the University of Arizona. He’s also project lead for the Curricular Analytics effort, and that’s what we explored for an hour.
CA analyzes the different routes undergraduate students can take through university curricula, measuring relative complexity in order to better shape advising, majors, and course catalogs. It generates visualizations of student pathways, including metrics, such as:
You can find out more on the project site, including uploading your own curricular data for processing and visualization. There is at least one scholarly paper breaking down the approach and data. There is also a Github site with plenty of files to download.
Naturally we recorded the whole session:
I would like to say a few things about the session, which went differently than many Forum Thursdays. There was a good amount of presentation, as Greg needed to show people the various visualizations in order to explain what CA does. That’s a break from tradition, as the Future Trends Forum is normally focused entirely on face to face discussion, but it worked well here. Participants had plenty of perceptive questions and comments, which Dr. Heileman handled very well. Maria Anderson, founding CEO of curricular analytics service Coursetune and excellent Forum guest, weighed in. Overall it felt like a rich workshop or tutorial, and might point the way towards more Forum events along these lines.
I mentioned plenty of questions and comments and meant it. Yesterday was one of those sessions where we ran out of time before getting to all of them, so I’ll follow my usual practice of copying them here, lightly edited for anonymity and typos, and in the chronological order they appeared during the hour-long session:
Students often fail to see the larger point to their educational efforts. How can we leverage your project to encourage them to contextualize their education? What about opportunities for interdisciplinarity?
I might be jumping the gun, but how does bringing these insights forward allow institutions to make substantive curricular or policy shifts.
Students who go to elite schools have already learned how to succeed in academia no matter what you do to them. It’s not really a fair comparison to say that elite schools give students more freedom.
Has your work unearthed common reasons for curricular complexity? Governance? Faulty culture? Etc.?
Do you think the downward trend in high school graduates will push institutions to streamline curricula?
How might we move from a culture of “weeding out” students at the intro level & instead open the door for more opportunities for students more investment in completing a degree/getting an education?
Have career outcomes or paths of these graduates been mapped to the curricular complexity of their alma mater? And is there any relationship?
Did the restructuring and pathway of using an “Engineering 101” course also benefit students who might have had previous experience in math or engineering? Diversity and reinforcement sounds promising
How is Instructional Complexity calculated? How is it different than Structural Complexity?
I hope participants can use comments on this post, or comments elsewhere, to continue the discussion.
One more link to share: in response to questions about campuses running into restrictions imposed by disciplinary associations, professor Heileman referenced a paper he co-authored with the very perky title “ABET Won’t Let Us Do That!”
This is the first time the Forum has focused so clearly on data analytics. It won’t be the last.
Happy to hear your reactions in comments below!
