Projects explore AI as a personalized tutor, role-playing simulations, and faculty instructional support tool
Sean Corp, Associate Director of Communications
The University of Michigan is funding 13 new faculty-led projects to explore how artificial intelligence can meaningfully improve teaching, learning, and student success at scale. The selected initiatives represent 11 schools and colleges across the university, including Social Work, Public Health, Information, Education, Business, Law, and Literature, Science, and the Arts.
The proposals highlight growing interest in how AI can support teaching and learning while addressing real educational challenges—from improving feedback and assessment to creating more realistic simulations and helping students practice complex professional skills.
The Center for Academic Innovation will provide funding and in-kind support for the projects, including the use of generative AI tools, conversational chatbots, and simulation platforms to create more interactive learning experiences. Other projects focus on supporting instruction through automated analysis of teaching practices or by giving students new ways to receive personalized guidance and practice professional decision-making via role-play simulations.
Across the proposals, several common themes emerged. Faculty are exploring how AI can scale personalized learning, help students practice difficult conversations or clinical scenarios, and provide timely feedback for both students and instructors. Other projects aim to reconsider assessments in the era of AI by providing instructors with new methods to evaluate learning.
“These projects reflect a shift from experimenting with AI to understanding how it can meaningfully improve teaching and learning at scale,” said James DeVaney, founding executive director of the center and the associate vice provost of academic innovation.“By supporting faculty across 11 schools and colleges, we’re generating the insight needed to move from isolated pilots to approaches that shape the future of education across the institution and beyond, while expanding access to more personalized, high-quality learning experiences.”
Project funding is made possible through the university’s Academic Innovation Fund. In-kind project support could include technical guidance on the technical architecture and integration of AI tools, learning experience design, and platform and hosting considerations.
Funded Projects
AI Role Play & Simulation
AI allows for role-playing and simulation environments that are safe and repeatable for students interested in building up their clinical and communication skills.
AI-Enhanced Clinical Simulation: Piloting Adaptive Motivational Interviewing Practice with Noodle Dialogue
Faculty: Barb Hiltz (School of Social Work)
This project will pilot the AI-powered Noodle Dialogue platform to help social work students practice motivational interviewing with simulated clients. The adaptive system enables students to engage in realistic, responsive conversations that build clinical communication skills.
Growing AI Competency Use with the AI-Driven Nurse Practice Advisor
Faculty: Barbara Medvec (School of Nursing)
This project will develop an AI-enabled Nursing Practice Advisor that presents leadership scenarios and simulations to help healthcare professionals build decision-making skills, ethical reasoning, and AI literacy.
Understanding the ICF Framework through Conversations with AI ChatBots
Faculty: Kara Palmer (School of Kinesiology)
Students in a pediatric health course will interact with AI chatbots that simulate patient interviews, helping them better understand the International Classification of Functioning (ICF) framework used in healthcare practice.
V-SP: Scalable and Integrated Virtual Patient Simulation and Debriefing for Medical Education
Faculty: Vitaliy Popov (Medical School)
The project will create an AI-powered virtual patient simulation that allows medical students to practice delivering difficult news to patients and receive feedback on their communication and clinical reasoning.
Improving Feedback Literacy through AI-Enhanced Role Play for Nursing Students, Graduates, and Preceptors
Faculty: Dana Tschannen (School of Nursing)
Using the Yoodli communication platform, nursing students and professionals will practice giving and receiving feedback through AI-supported role-play scenarios designed to strengthen coaching and communication skills in clinical settings.
AI as a Personalized Tutor
AI enables deep analysis, personalized tutoring, and a platform for discussion, personalized feedback, and refreshing key skills.
The Common Room: An AI-Enabled Collaborative Learning Space
Faculty: Michael Nebeling (School of Information)
This initiative will build an online collaboration environment where students work together alongside AI agents that help facilitate discussion, critique, and co-creation in project-based courses.
AI-Informed Advocacy: Deepening Critical Thinking in the Child Welfare Appellate Clinic
Faculty: Vivek Sankaran (Law School)
Law students will use a secure AI-powered database—described as a “Virtual Senior Partner”—that draws on the clinic’s past briefs and cases. The system will help students move from basic research to deeper legal analysis while working on real appellate cases.
The Dissertation Maizey: A Tool to Support Doctoral Writing Quality and Progress
Faculty: Simone Sessolo, (Sweetland Center for Writing, LSA)
This project transitions the established Dissertation ECoach into Maizey, the university’s secure generative AI platform. The tool will offer conversational guidance to help doctoral students structure their writing, track progress, and strengthen dissertation quality.
Integrating GenAI Tools into the BioSTART Program
Faculty: Matthew Zawistowski (School of Public Health)
The project will integrate Wolverine Tutor, a generative AI learning companion, into the BioSTART program to help incoming biostatistics graduate students refresh key mathematical skills before beginning their coursework.
Faculty Instructional Support
AI agents built with the intention of scaling key activities in large courses and providing instructors with detailed feedback on teaching practices.
Scaling Oral Assessments Through AI: An Autonomous Voice Agent for Student Evaluation
Faculty: Lindsey Gallo (Ross School of Business)
Researchers will develop a voice-based AI agent capable of conducting oral exams. The approach aims to make oral assessments—long valued for evaluating understanding and academic integrity—more scalable in large courses.
Using Automated Transcripts and GenAI to Provide Timely Feedback to Improve Instruction
Faculty: Kevin F. Miller (School of Education)
This project analyzes classroom recordings and transcripts using generative AI tools to provide instructors with detailed feedback on teaching practices, including how classroom discussions unfold.
Together, the funded projects represent a growing effort to thoughtfully integrate artificial intelligence into higher education. By focusing on practical applications across disciplines, the initiative aims to better understand how AI can enhance learning using tools that could be vital to building life-changing education.
