Helping faculty teach 'more effectively, more joyfully, more efficiently'

During the 2024-25 academic year, the 2030 Teaching and Mentoring Excellence Committee was charged with improving how Duke defines, evaluates and supports effective teaching and mentoring practices. This effort is designed to uplift, support and celebrate the centrality of teaching and mentoring to Duke’s mission.

The committee – which comprised faculty from across the university – delivered recommendations to Provost Alec D. Gallimore over the summer, and Academic Council recently approved three key elements of the report: implementation of Teaching and Mentoring Excellence Frameworks and associated promotion standards; institutional support and management of a process for balancing unit-level flexibility with a baseline of consistency across the university; and adoption of new titles and career tracks for regular-rank faculty who are not on the tenure track. Individual departments and units will be contacted directly in the coming months with guidance on implementation and invited to help determine how best to apply specific recommendations within their academic context. Other recommendations included in the report will also be considered by individual units over the coming year. 

In a recent interview, committee co-chairs Bridgette Hard (Psychology & Neuroscience) and Jerry Reiter (Statistical Science) discussed the committee’s work and why it matters. 

How did the committee approach your charge?

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Bridgette Hard: We started with the assumption that Duke faculty care about teaching and mentoring, and that they want to be, and generally are, good at it. But without having clear definitions of what we mean by “good” teaching and mentoring, it’s hard to reward that effort. Having clear definitions is partly about making sure that faculty feel valued for the great work that they're already doing. But it is also about giving transparent guidance and support to our colleagues who are just starting out at Duke. New faculty want to be effective but may not know how. Having clear definitions of what our goals are as teachers and mentors is crucial to helping them to become successful. 

Jerry Reiter: This is going to be a process of experimentation – of piloting, refining, iterating and getting better. Something may not work for a unit, and maybe it does, but if it doesn’t, how can it be fixed? One thing we heard a lot in the conversations was how different the contexts are for different units. Medicine is different than Math, which is different than English, which is different than Nicholas. So having one set of criteria is not going to work. We viewed the frameworks as starting points for departmental conversations around effective teaching. 

How can faculty balance these recommendations with their research obligations? 

Reiter: No one is saying we're going to downgrade research. It's an opportunity to lift up, to better recognize people who make contributions in the teaching and mentoring space, and to give those contributions some good weight. And part of it, too, is hoping that, by having these guideposts, we can help faculty be more efficient with some of their teaching and mentoring. 

Hard: It can be really challenging for faculty to balance teaching alongside their research and that challenge is amplified if you aren’t even sure what you are trying to accomplish in your teaching. We all want to be good at what we do, and we want to enjoy what we do.  I think if people know what is expected, and how to do it well, they can be more efficient by focusing on what really matters, which leaves more time for them to do their scholarship. And the teaching, when it’s done well, is so much more fun and meaningful! It can really enrich your academic life. We really have a responsibility as a community to give current and future faculty the guidance they need to be successful, not just in research, but also in teaching—which is this huge thing that we’re obviously asking them to spend a lot of time doing. 

Did the committee discuss the impact of AI on teaching?

Hard: We don't mention it in the recommendations, but it's absolutely on everyone’s minds. Generative AI is transforming the landscape of education so rapidly that we really have to step back and think: What are we really trying to accomplish as educators? What should our focus be? What are our goals? And I do think having a clear picture of what effective teaching means is crucial in knowing how to make those decisions about what role AI should and shouldn't play in our classrooms. I think that makes the committee’s work incredibly timely—it is going to help us navigate this massive change. 

What is your message to units and faculty who are already focused on this challenge?

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Hard: As we were building our recommendations, we found that some Duke departments were already creating great examples or prototypes for thinking about and supporting teaching for their faculty. We think our recommendations will hopefully take everyone’s thinking a little further, but given the work some schools have already done, many should be in good shape. The fact that we're all going to be doing this as an institution is an opportunity for us to also be open-minded and learn from what other schools are doing that maybe we didn't think about. I hope that this will be both a customizable process, but also a collaborative process, of people sharing their great ideas and not feeling like they have to reinvent the wheel.

Reiter: This is a backbone, a spine, that units can build off and make their own. And if something is missing, they can add it. We just want to provide support for units to take a look at what they're doing, see if they want to change it or enhance it, but to provide a backbone for those discussions. 

What impact do you hope the committee’s work will have on the culture at Duke?

Reiter: These recommendations are designed to help everybody teach more effectively, more joyfully, more efficiently. We’re trying to create an environment where people are very interested and happy to talk with each other, as we do for research, about teaching and mentoring and the challenges that they face; get advice from people in and outside their departments; strategize about how to best teach particular concepts or what to do with AI. Creating that culture where those kind of conversations are rewarded and encouraged and incentivized is really what we're after. 

Hard: That's one reason why one of our recommended forms of assessment for teaching and mentoring is self-reflection. We're encouraging units to let faculty self-reflect and submit annotated syllabi and other kinds of reflections as a way to evaluate and show off their teaching. That self-reflective emphasis can get all of us thinking more about teaching and talking about it. We really think that will help move the needle toward a culture in which teaching is more valued and more fun for everybody.

I am really hopeful about how this will unfold. Over this past year, it was really inspiring to see that anytime we talked to stakeholders within the Duke community, our committee’s mission and ideas were met with such enthusiasm and positivity, which I think really reinforced for me that Duke is a place already that cares a great deal about teaching. I think we sometimes have this mistaken impression that at an R1 university, faculty don't care very much about teaching, they just care about their research, but that is not the impression that we got. People generally just seemed on board with these ideas. We saw that at all levels.

Reiter: This is a process, it's a long-run play, and there will be things that get tried that work great, and there are things that get tried that don't, that need to be made better. And it should be faculty-driven with support from administration, with the goal of how do we reward people for making these great contributions to teaching and mentoring? How do we recognize that? And for those who are inexperienced or maybe just learning the craft, how do we help them get to where they need to go faster and more efficiently?