Enterprise Technology Launches the ET Faculty Fellows Program
A new partnership program will embed a small cohort of UT Austin faculty with ET staff each year to investigate, prototype, and share the future of teaching and learning with technology.
Faculty as genuine partners in what comes next for teaching and learning at UT.
Starting this fall, Enterprise Technology will invite applications for its inaugural Faculty Fellows cohort — a structured, funded working partnership between faculty and ET staff focused on the most consequential questions in technology-enhanced education.
Enterprise Technology is launching the ET Faculty Fellows program — a new annual initiative that funds a small cohort of UT Austin faculty to work alongside ET staff on questions that matter for the future of teaching and learning. The program is not a grant, an advisory panel, or a consulting arrangement. It is a genuine working partnership: faculty embedded with ET staff teams, with shared project goals, mutual accountability, and real resources on both sides.
Each cohort will be organized around a set of focus areas reflecting current opportunities and institutional priorities. For the inaugural 2026–27 call, those themes span generative AI in course design, AI literacy and critical thinking, learning analytics and student success, accessible and inclusive digital learning, research-integrated teaching, and human-AI collaboration across disciplines.
ET works with thousands of faculty every year through the tools we support and the training we offer. The Fellows program goes deeper — bringing a small group of faculty into direct partnership with ET staff to build knowledge, create replicable models, and share what they learn with the broader UT teaching community.
What fellows receive
Each funded fellow receives a $20,000 baseline award, paid as direct funds or a course buyout based on what works for the fellow and their department. Fellows are also matched with a dedicated ET staff team for the duration of the project, given access to ET facilities and data resources, and supported with travel and software as appropriate to their work. Sabbatical-period arrangements are considered on request.
The fellowship runs from summer through the following fall. The summer intensive — typically six to ten weeks — is the core working phase. The fall semester extends the partnership into active sharing: public presentations, Fellows' Hour sessions with the cohort, and the publication of a replicable case study on this site.
The inaugural cohort and timeline
The program will fund three fellows in its first year. The call opens in fall 2026 with published focus themes and application guidelines. Faculty interested in discussing a project idea before the formal call opens are encouraged to reach out informally — early conversations are welcome and have no effect on a subsequent application.
- Fall 2026 — Program launches, call announced with focus themes and application guidelines
- Winter 2026–27 — Applications due, including project outline, CV, proposed timeline, and department chair letter of support
- February 2027 — Awards announced; finalists may be invited for a brief conversation
- Summer 2027 — Fellowship intensive begins; fellows embedded with ET staff teams
- Fall 2027 — Outcomes shared publicly; case studies published; Fellows' Hour series runs
What ET asks of fellows
Fellows are expected to contribute to the broader UT teaching community — not just complete individual projects. That means at minimum: a public talk or appearance on the ET Talk podcast, a published case study co-authored with ET staff, active participation in the cross-cohort Fellows' Hour series, and light ongoing engagement with ET through the full 12-month term.
Fellows aren't consultants or advisors. They work with us — and they help us build the kind of knowledge the whole UT teaching community can use.
Proposals that span multiple focus areas or take unexpected angles are welcome. The program is looking for faculty who have a genuine project question, want to work directly with ET infrastructure and expertise, and are willing to share what they find.
This story was developed with AI support as part of the writing and editing workflow.