I try to spend most of my time living in the present, but in practice, I end up spending a little too much of my time alternately planning for and worrying about the future. Winter break is a time for looking back and gleaning some lessons from the past. In this article I try articulate some lessons learned from an intense 18 months running my department’s Active Learning Initiative.

In February of 2017, I got my dream job when the Cornell Department of Economics won an internal grant to transform our entire undergraduate core curriculum using evidence-based active learning methods. We had written a comprehensive proposal that detailed the process we would use: pairing teaching-focused postdocs with faculty to transform one class at a time and carefully estimating the impact of the new methods on student learning. Since we started work in earnest that summer, our students have learned a ton, and so have we:

• Hire great postdocs. Our two postdocs (George Orlov and Daria Bottan) have been amazing. The key was to look for someone who has a real passion for teaching, has some knowledge of modern pedagogy, and has good quantitative skills. Specialized expertise in the area of the classes they will be transforming is a plus. This kind of candidate is absolutely out there.

• Choose the right first class. If I could do it again, I’d pick a class that’s taught as a pure lecture by a faculty member who is open and even excited about trying active learning. This maximizes the probability of seeing real improvements in student outcomes, and it’s always nice to start with some success.

• Draft learning goals for courses early and get a broad group of department faculty involved in reviewing those learning goals. It turns out faculty often have strong opinions about what should be taught it in a course, even if they don’t normally pay much attention to it.

• Communicate clearly with the instructor early on about the transformation process. A lot of measurement happens during the semester (e.g., COPUS, focus groups, student assessment), and it’s important to get instructor sign-off before it starts.

• Assess entering students skills as best you can at the beginning of the semester. This is critical for controlling for differences when comparing outcomes across classes. We invested heavily in developing an economic statistics assessment that we gave our Applied Econometrics students. We gave our math-intensive introduction to economic statistics students a basic math skills assessment. And we gave our intermediate micro students the same math assessment as well as a micro principles assessment that we developed.

• Assess exiting students skills as best you can. This is primarily how we measure impact of our transformation effort. We’ve developed assessments for the Applied Econometrics course as well as the math-intensive intro stats course. Our intermediate micro assessment is still in development. Our plan is to eventually publish all of our assessments so instructors everywhere can use them.

• Get demographic data on students. You can either collect your own or (if possible) get access to university administrative data. This is crucial for controlling for differences in student populations as well as estimating sub-population specific effects. There’s evidence that active learning is even more effective for URM’s and women, and using these teaching methods will reduce performance gaps–This data lets us see if that’s happening in our classes.

• Create an explicit transformation plan for the class you’re transforming so it’s clear to everyone involved what’s going to be done. People have very strong (and different) ideas about what active learning is.

• Communicate regularly with the whole department. The past few months I’ve been maintaining a shared folder of ALI documents for the whole department and sending a monthly update email. We also give occasional 5 minute updates at faculty meetings.

• Share what you’re doing and what you’re finding with folks outside the university (e.g., conferences, invited talks and journals). This lends the effort credibility, and that’s crucial when you are trying to convince faculty to do something uncomfortable. Also, once you have good measures of student learning and are gathering all this other data, it enables really interesting research projects. We ended up submitting abstracts for four new projects to the AEA Conference on Teaching and Research in Economic Education (CTREE) this year.

• Get the best TA’s you can in your ALI classes, especially if you are changing what happens in discussion sections. A TA in an active classroom doesn’t just sit there—they spend a lot of time interacting with students and guiding them in activities.

While we’ve learned a lot and accomplished a lot in our first 18 months, our focus has been on process and measurement. The next 18 months will be about reaping the benefits, and I couldn’t be more excited!