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Demonstrating care, empowering TAs, and cultivating opportunities for peer connections are just a few ways that relationships show up in your large-enrollment courses. Use these resources for a clearer view on how to make the most of human interactions in large courses.

This collection contains resources for educational developers interested in supporting faculty engagement in Scholarship of Teaching and Learning (SoTL).

The Making Teaching Matter for Civic and Intellectual Life project started in 2024 at UVA's School of Education and Human Development. This collection features essays from students involved in the project with advice for instructors on cultivating civic engagement, ethical decision-making, and more.

First time teaching your own course? In this collection, you'll find foundational resources to begin your teaching journey. Each resource is from my own bookshelf that I use over and over again!

Gathering evidence in SoTL requires careful choices about what kinds of student learning to make visible. This collection offers practical resources—from survey design tips to a compendium of validated scales—to help you plan for and collect the right data to answer your SoTL research questions.

Research shows that text-to-speech (TTS) is a prominent use of generative AI by students with disabilities. This collection features ideas for using AI to support students with disabilities in a variety of educational contexts and points to two AI-powered TTS tools.

Designing a SoTL study requires thoughtful decisions about study design, methods, and disciplinary approaches to inquiry. This collection introduces a range of accessible resources to help you choose a study design that aligns with your research questions and scholarly goals.

In pedagogical partnerships, students and teachers contribute collaboratively “to curricular or pedagogical conceptualization, decision-making, implementation, investigation, or analysis” (Cook-Sather et al., 2014). This collection explores the question: Why do pedagogical partnerships matter?

Generative artificial intelligence has made longstanding questions about academic integrity more urgent and complex. How does genAI change our understanding of plagiarism? What can or should instructors do to motivate students to complete graded assignments without unauthorized assistance?

Do you find that your course learning objectives don't fully capture the goals you and your students have for their learning and development? This collection points to a variety of frameworks for developing more holistic learning, where the humanity of our students is at the center.

This collection explores a digital media project in a general chemistry course. Included are the assignment description, a sample student project, and resources to support students' work and instructor assessment efforts. Be sure to read the annotations on the linked files.

How can you help develop students’ AI literacy, even when you’re not an expert in AI? In this collection, you'll find articles and activities that articulate and develop key AI competencies for educators and your students.

This collection features frameworks for understanding AI literacy—including one framework developed here at UVA—as well as classroom activities that support the development of AI literacy in both students and instructors.

Are fostering civil discourse and dialogue across difference teaching goals for you? Don't wait until potentially controversial topics emerge and hope for the best. Start cultivating community on day 1 by using some of the activities described in this collection.

Faculty are adapting to AI in complex ways beyond simple adoption or resistance. This collection provides educational leaders with frameworks to understand faculty decision-making, identify change barriers, and facilitate inclusive AI integration conversations.

Generative AI has brought new urgency to longstanding assessment challenges. How do we grade individual contributors within a collaboration? What belongs to the human, and what to the technology? This collection offers new approaches to assessing human-AI collaboration in educational settings.