Elkins Professorships for Academic Transformation
Overview
The Elkins Professorship for Academic Transformation is awarded competitively to faculty members in the University System of Maryland to support projects that can foster or illuminate improvements in access, affordability, quality of outcomes, and/or stewardship of people’s time, money, and other scarce resources. Work on “academic transformation” advances at least two of these goals. For AY 2026-27, faculty are asked to put forth projects focused on the use of Generative AI to advance these goals.
Three Fellowship awards of up to $10,000 each is for work to be carried out over the 2026-27 academic year, potentially as part of an academic leave/sabbatical. The awardee’s activities would be carried out in consultation with, and potentially in collaboration with, the staff of the William E. Kirwan Center for Academic Innovation. The scope of proposed projects should reflect scale beyond a faculty member’s own teaching practices or course design.
Work may be carried out in collaboration with colleagues from one’s own academic department or other academic departments, IT, Teaching and Learning, Instructional Design, Accessibility, Advising, Student Support Services, or other relevant units. Letters of support are expected from all partner units.
The proposed work involving Generative AI should advance and illuminate some aspect of academic transformation, directly or indirectly. More often than not, proposals will expand on inquiry or initiatives related to the use of Generative AI to enhance teaching and learning that are already underway. Proposals would typically outline some combination of study of existing research and evidence plus new research, development, and/or action supporting the use of Generative AI toward the solution of an educational need or challenge such as:
The need to educate students who differ substantially, for example in their perspectives, sense of themselves as learners, motives for learning, preparation, and abilities;
The need to demonstrate to potential students, taxpayers, employers, benefactors, and others that our graduates have been well-prepared and even transformed by their experiences in our institutions;
The need to make more productive use of information about students and learning to guide and improve instruction and advising;
The need to expand, extend, and sustain practices that have demonstrated their value and potential on a smaller scale;
The need for education to continually improve in its methods, content, and resources rather than treating change as an exception to normal practice; and/or
The need for more inclusive, useful strategies for helping large numbers of faculty gradually expand their repertoire of teaching strategies.
These are only examples. The funded work might focus directly on the use of Generative AI to support teaching and learning or on the role Generative AI can play to improve the conditions, policies, and infrastructure that support teaching and learning. Again, the scope of proposed projects should reflect scale beyond a faculty member’s own teaching practices or course design.
Eligibility
Faculty from any USM institution are eligible to apply. Faculty must be full-time faculty members with a rank of associate or higher. Deans, vice-presidents, and the president are not eligible to apply. Applicants may request that these eligibility requirements be waived for special circumstances of educational importance to USM. Collaborative proposals involving multiple departments or disciplines are highly encouraged.
The Elkins Endowed Professorships were created in part to honor the prior contributions of the recipient. The faculty team lead applicant should have a substantial track record of contributions to the education of students (such as innovations, teaching awards, participation in important initiatives to improve student learning). Elkins Professors must exhibit, at a minimum, all the following qualifications:
A solid record of achievement in a recognized academic or professional discipline;
Evidence of significant achievement outside traditional disciplines but linked in scholarly and professional ways to the work of the USM;
Demonstrated ability and continuing desire to lead and inspire undergraduate and graduate students in a range of learning situations – from the lab to the classroom, to the studio, to the community, to online; and
Demonstrated ability and intent to participate vigorously in programs and activities outside the USM.
Criteria for Assessing Proposals
Academic Transformation
The proposed activities should focus on the use of Generative AI in teaching and learning to address at least two of the following:
Enhancing access (how many and the variety of people who can be educated and/or deepening or extending learning for more people);
Increasing affordability for students;
Improving outcomes (what students know or are able to do by the time they finish their education).
Broad Influence
The proposed activity should address a widely felt need and therefore have the potential for broad influence across the USM institutions and beyond.
Built on Prior Experience and Research
The proposal should explain how the plan has built upon prior experience and research, both the applicant’s and also the experiences, achievements, and challenges encountered by others in the field.
Feasibility
The proposed work plan should be demonstrably feasible. For example, if proposal readers are likely to wonder how the work can be done in the time available, it would help to include a timeline. As noted above, letters of support are expected from all partner units. If the work will involve, for example, the institution’s teaching center, then the proposal should include a letter from the director of the center that explains what the center will provide.
Evaluation Plan
The proposal should include a plan for a final evaluation or peer review of the work.
Appropriate Budget
The proposed budget should be consistent with the activities described in the narrative and demonstrate good stewardship of these funds. Funding can be used for training workshops, software and hardware purchases, research activities, and the development of AI-based educational resources.
Preparing a Proposal
Applicants are encouraged to confer with Kirwan Center staff while considering and preparing proposals, for example, about ways in which the Kirwan Center might support or amplify the work. Please reach out to Nancy O’Neill, Executive Director of the Kirwan Center, at noneill@usmd.edu no later than Friday, May 1, 2026, if you are interested in conferring.
AI Use
Applicants may use generative AI tools to assist in proposal development. If AI tools are used, please include a brief disclosure statement indicating:
Which AI tool(s) were used (including version)
How they were used (e.g., brainstorming, drafting, editing)
Confirmation that all content has been reviewed and verified for accuracy
Digital Accessibility
Proposals should adhere to best practices in digital accessibility, such as the use of heading structure and meaningful alternative text for images. The USM Digital Accessibility Checklist is a helpful guide.
Proposal Outline
Please use the following outline to prepare your proposal. Sections IV-VI should be no more than 10 pages, double-spaced, 12-point font.
Cover sheet with applicant’s name, position title, department or unit name, institution name, phone number, and email address.
Nomination letter from the faculty member’s Provost or Dean supporting the faculty member’s candidacy. If the proposed project involves action within the institution, this nomination letter should also indicate support of that action.
Brief abstract that summarizes the essence of the project.
Explanation of the need or opportunity, and its importance.
A description of the proposed work, including an explanation of how prior work in the field has influenced the plan. Include a schedule of activities if appropriate. We recognize that work plans evolve, so give us your best guess now about how the work might unfold.
Planned deliverables. At minimum, this should include a final narrative report including some kind of external assessment of the work and a final financial report.
Budget.
References cited.
Any supporting documents needed, including at least:
Abbreviated c.v. (up to 2 pages and including only relevant publications) and a 250-word biographical sketch explaining the applicant’s relevant experiences for carrying out the proposed work.
Additional letters of support beyond the nomination letter, as appropriate.
Again, applicants are encouraged to confer with Kirwan Center staff while considering and preparing proposals, for example, about ways in which the Kirwan Center might support or amplify the work.
The nomination package should be submitted to faculty@umd.edu by no later than Thursday, April 30th, 2026.
The University will prepare a letter of nomination for the selected candidate to submit to USM directly by May 22nd, 2026. Contact the Office of Faculty Affairs regarding submission procedures at faculty@umd.edu or 301.405.6803.