Artificial Intelligence (AI) in Teaching and Learning


Participate in a mega-SoTL research project investigating the impacts of artificial intelligence tools on teaching & learning!

SCHEV Fund for Excellence and Innovation Grant

We are excited to share that we have been awarded a $75,000 Fund for Excellence and Innovation grant from the State Council of Higher Education for Virginia.

Learn more here.


What is the SoTL-AI project?

This research study exploring the use of artificial intelligence (AI) in higher education will bring together faculty, graduate students, and staff across institutions to join research teams investigating a variety of sub-topics.

The project is led by three co-principal investigators: Breana Bayraktar (George Mason University), Dayna Henry (James Madison University), and Jessica Taggart (University of Virginia).

2023-2026 projects

In academic year 2023-2024, faculty, staff, and students come together on several teams to develop research projects exploring faculty and student experiences with AI. In academic year 2024-2025, we have projects investigating the following topics:

  • Onboarding: What Do Students Need to Know Before Being Invited to Use AI? The purpose of this project is to evaluate which onboarding activities are beneficial to students to increase comfort in using text generators in college courses. Contact project lead, Amanda Bryan
  • OER for Teaching with AI. This study aims to design, develop, and evaluate an adaptable OER resource for faculty/instructors to aid in understanding the principles of AI, methodologies for incorporating AI into teaching, ethical considerations surrounding AI in education, examples of AI-driven assignments, recommended AI class policies, and a review of current AI tools available for teaching. Contact project lead, Fang Yi.
  • Measuring and Grading Learning Done with AI. How do we measure and grade the learning that’s done with AI? This includes the assessment of AI-assisted projects and (re)defining the work of cognition, what to assess as student-generated content and AI-generated content, (re)defining the unit of intelligence, AI as cheating vs. tool, and the effects on / changes to student learning objectives. Contact project lead, Kiera Alison.
  • AI-incorporating learning. This study seeks to (a) articulate what high-tech vs. low-tech learning looks like across classrooms and departments – including what forms of low-tech learning we consider worth keeping in the curriculum; and (b) outline a both/and approach where instructors are empowered to make use of the potentials of both analogue and AI-assisted modes of thinking and creation. Contact project lead, Kiera Alison.
  • Mapping AI-Proofness: A Preliminary Cross-Disciplinary Investigation. This study develops a typology of possible assignments and “grades” their AI-proofness on a continuum. Doing so will give instructors in various academic disciplines the information they need to weigh pedagogical goals against the cost of various options. Contact project lead, Rip Verkerke.
  • The Potential of AI for Personalized and Constructive Feedback. Exploring the potential of AI systems in providing personalized and constructive feedback to students on their written or spoken work. Contact project lead, Spyridon Simotas.
  • AI as a Support for Students with Disabilities. Exploring how artificial intelligence can support students with disabilities or learning differences in higher education contexts or settings. Contact project lead, Danielle Waterfield.

plans for 2024-2025

In academic year 2024-2025, project teams will work to develop educational resources to support students and instructors in navigating the ethical integration of AI in postsecondary education, including actionable guidelines, pedagogical strategies, and policy recommendations. The resources will focus on the key areas of student onboarding, assignment design, assessment, personalized feedback, accessibility, and open educational resources (OER). The educational resources, developed by a team of faculty and staff from institutions across the state, will be evidence-based, informed by cutting-edge pedagogical research on these topics as well as the evolving scholarly literature. Findings from the research projects conducted in AY 2023-2024 will be used to create faculty development materials to support synchronous and asynchronous workshops and learning opportunities for instructors across the state.

get involved

Potential roles for collaborators include

  • Participate in the design of future research studies, including: research questions being investigated, data collection instruments, and/or data analysis plan
  • Contribute to data collection in your courses (this may involve disseminating surveys, collecting student artifacts, coordinating interviews or focus groups with students, coordinating with class observations, and other data collection activities)
  • Contribute to data collection in colleagues’ courses (this may involve conducting interviews or focus groups with students, conducting class observations, and other data collection activities)
  • Contribute to analysis of the data collected by the research team
  • Contribute to publication/presentation of findings
  • Contribute to development of teaching + learning resources

what is AI

Artificial intelligence is a machine’s ability to perform the cognitive functions we usually associate with human minds: learning, reasoning, problem-solving, perception, and language understanding. AI systems are designed to analyze vast amounts of data, recognize patterns, and make decisions or predictions based on the information they have processed. These systems can be trained using various techniques, including machine learning, deep learning, and neural networks, to acquire knowledge and improve their performance over time.

For more reading . . .