TEval is an NSF funded push to transform higher education.
We're advancing understandings of institutional change processes by studying and supporting the adoption and integration of new approaches to evaluating teaching.
Join NextGen TEval Alliance
Friday, October 16 2026, 12-2 PM ET
Join an international group of colleagues from institutions who are advancing more holistic, valid, and effective approaches to teaching evaluation. Building on the momentum from the NextGen Teaching Evaluation Alliance's launch summit in April 2026, this convening brings together academic leaders and faculty to exchange ideas, explore shared challenges, and find inspiration for transforming teaching evaluation in your own departmental and institutional contexts.
To seed our discussions and idea exchange, we'll feature three brief examples of what colleagues are doing in their institutional contexts, and we'll spend the remaining time discussing shared questions and strategies to advance teaching evaluation on our campuses/communities.In addition to brief presentations on these examples, we will have break-out groups where participants can discuss their own experiences, ideas, and challenges, and meet colleagues at other institutions involved in efforts to transform teaching evaluation.
Come ready to connect, share, and strategize.
Interested in keeping up but can't attend this session? Sign up for future events and announcements.
Check out our book from Harvard Education Press (Fall 2025): Transforming College Teaching Evaluation: A Framework for Advancing Instructional Excellence
Three institutions (UMass, KU, and CU) are incubating specific strategies and processes for effecting change.
This project includes a study of organizational change in regard to institutional evaluation, incentive, and reward processes pertaining to teaching excellence in faculty work. The overall project encourages the use of evaluation, incentive, and reward processes as a lever to promote greater use of evidence-based teaching within universities as complex systems.
This project is conducted in collaboration with and the support of the Association of American Universities and the Bay View Alliance.
This material is based upon work supported, in part, by the National Science Foundation, Award numbers: DUE 1725946, 1726087, 1725959, and 1725956.
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.