SoTL Mini-Grants
Scholarship of Teaching and Learning (SoTL) Mini-Grants 2026-2027 Academic Year
Purpose
The 2026 Scholarship of Teaching and Learning (SoTL) Mini-Grants support instructors in developing and studying the impact of generative AI on student learning, teaching practices, formative assessment, faculty workflows, and/or cross-disciplinary collaboration during the 2026–2027 academic year. The program is designed to advance well-developed, evidence-based explorations of how AI is shaping teaching and learning, with the goal of contributing to the broader canon of evidence-based practices. In addition to local impact, applicants are encouraged to consider how their work may contribute to broader scholarly conversations through SoTL dissemination.
Grants are available to individuals or small groups in the amount of $2000 per project. Collaborative proposals are encouraged where appropriate. An additional $1000 bonus will be awarded for peer-reviewed publication and/or conference presentation.
Suggested Categories of AI-Focused Teaching Innovation
To support diverse faculty interests while encouraging publishable SoTL scholarship, mini-grant proposals may align with one or more of the following project themes:
AI for Assessment and Feedback Innovation
Projects in this area explore how generative AI can enhance formative feedback, self-assessment, and student learning processes.
- Using AI tools to deliver formative feedback
- Improving grading efficiency
- Exploring reflective learning
- Designing hybrid feedback models
AI-Augmented Faculty Workflows
Projects in this area examine how generative AI can support instructional efficiency and faculty workflows.
- Automating course materials
- Generating student outreach
- Developing course-specific AI tools
Cross-Disciplinary AI Collaborations
Projects in this area explore how generative AI can support collaboration across disciplines in teaching, content creation, or research.
- Humanities and STEM collaborations
- Misinformation research
- Creative AI projects
NEW: AI-Supported Scaffolding and Student Support
Projects in this area explore how generative AI can support student learning through structured guidance, practice, and reinforcement.
- Providing step-by-step explanations of complex concepts
- Designing scaffolded assignments that build understanding over time
- Creating AI-supported practice opportunities
- Supporting students who benefit from additional guidance, structured practice, or alternative explanations
Application Process
Submit a proposal as a single PDF (maximum 6 pages) that includes the following sections:
- Experience with and interest in generative AI tools
- Course context and enrollment
- Description of the proposed project and AI integration
- Alignment with a focus area
- Expected impact on student learning or teaching practices
- Anticipated challenges
- Opportunities for supporting student learning, including scaffolding or practice
- Project timeline
- SoTL and Evidence of Impact
- Student work or data used to assess learning
- Additional methods to measure impact
- Approach to supporting a potential manuscript or conference presentation
- At least one appropriate peer-reviewed outlet or conference.
- Disclosure of AI use in proposal development (limited to planning, ideation, and/or editing)
Special Considerations
- Alignment between goals, AI use, and outcomes
- Feasible evaluation approach
- Potential contribution to SoTL or discipline
- Clear implementation plan
Participation and Dissemination
If selected, grant recipients must:
- Attend two Summer 2026 meetings and one Fall 2026 meeting
- Disseminate to the TTU community through a TLPDC workshop or Small Bytes blog post
Submission Information
Submit proposals to Lisa Du Bois Low, Director of AI Pedagogy and Policy, no later than 11:59 p.m., May 26, 2026.
Teaching, Learning, & Professional Development Center
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Address
University Library Building, Room 136, Mail Stop 2044, Lubbock, TX 79409-2004 -
Phone
806.742.0133 -
Email
tlpdc@ttu.edu