1 The Nuts and Bolts of Grant Administration
When generative AI models hit the education scene in late-2022, it was immediately clear that teaching and learning would be impacted. While some instructors were worried about students offloading learning to a technology and the threats to academic integrity, others were enthusiastic about the potential for AI tools to support rigorous learning experiences and creative approaches to teaching. The College of Natural Sciences (CNS) at the University of Texas in Austin (UT) aimed to empower innovative instructors to test their ideas for using AI technologies in STEM teaching and learning contexts.
The Office of STEM Education Excellence (STEMx) at UT Austin was already administering an internal grant program to support innovative education practices. Therefore, our office oversaw a special call for proposals related to artificial intelligence in education. In line with the existing internal grant program we administer, the application form was brief to prevent overburdening faculty and encourage applications. We required only a 200–300 word letter of interest to start a conversation about the proposed project, which asked the applicant to describe: 1) the problem/challenge/opportunity being addressed, 2) how AI technologies can address this, and 3) an explanation of the value in sharing this idea with others.
One of the early goals for this grant was to create materials to share broadly through an Open Educational Resource (OER). However, due to the rapid execution of this grant program, details about how to best support and develop the projects were established in real time. Conversations with the first few applicants prompted program administrators to create collaborative documents to help applicants flesh out their ideas, which included:
- Additional details about the student population served,
- Potential AI tools needed for the project and subscription information,
- Refinement of specific project goals,
- A description of the content that the applicant planned to provide for this OER, and
- An opportunity to update their letter of interest based on new plans for their projects.
Following completion of the collaborative document, the grant administrators met with applicants to discuss their projects and suggest modifications to the initial proposal. Once the project scope and compliance with university policy was verified, the award was confirmed. The grant recipient was invited to continue conversations with the program administrators, or work independently as they saw fit.
Two rounds of grants were awarded, near the beginning of spring and fall semesters in 2024. The Cohort 1 award recipients (Spring 2024) were able to use nearly any AI tools they desired, as long as subscription costs were not prohibitive. Throughout 2024, the university began to adopt partnerships with specific AI providers and clarified policies around university-supported projects. This resulted in significant changes to guidance and requirements between Cohort 1 and Cohort 2, as we discuss in the next section.
