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Initiatives: Generative AI Pedagogy

Generative AI Initiatives

Generative AI Pedagogy Fellows Program

The Generative AI Pedagogy Fellows Program is a comprehensive year-long initiative launched by the Kirwan Center and funded by the ϡȱ Center for Computing Education (MCCE) for the 2025-2026 academic year. This program selected 1-2 faculty members from each of our 12 ϡȱ campuses to become champions for integrating Generative AI into teaching and learning practices. Fellows participate in a structured curriculum during September and October, 2025, followed by an in-person session in November to finalize and present workshop plans. In the spring semester, fellows will offer workshops on their campuses in coordination with their Centers for Teaching and Learning. The program covers essential topics such as utilizing AI in course design, lesson planning, rubric development, student feedback and bot building for teaching and learning. 

Our 2025-2026 fellows were nominated by their provosts and have tremendous experience using Generative AI in their own classrooms. We anticipate deep collaboration and new research projects stemming from this fellowship program, in addition to enhanced peer-to-peer workshops for faculy interested in Generative AI in their teaching practices at each of our campuses.

The ϡȱ 2025-2026 Generative AI Pedagogy Fellows are: 

Antonia Charles-Strowbridge, Assistant Professor, Teaching, Learning, and Professional Development, Bowie State University 

Andrew Mangle, Associate Professor, Management Information Systems, Bowie State University 

Jeronda Burley, Associate Professor, Social Work, Coppin State University 

Denyce Watties-Daniels, Associate Professor and Director of Simulation and Learning Resource Centers, College of Health Professions, Coppin State University 

Kris McGee, Associate Professor, Educational Professions, Frostburg State University 

Wenjuan Xu, Professor, Computer Science and Information Technologies, Frostburg State University 

Casey Stratton, Assistant Professor, Communication, Salisbury University 

Jessica Walter, Associate Professor of Exercise Science, Salisbury University 

Amanda Jozkowski, Associate Professor and Graduate Program Director, Occupational Therapy & Occupational Science, Towson University 

Benjamin Zajicek, Associate Professor, History, Towson University 

William Carter, Associate Professor, Management and International Business, University of Baltimore 

Rachel Zeleny, Associate Professor and Writing Program Director, English and Integrated Arts, University of Baltimore 

Scott Riley, Instructor, Pharmaceutical Sciences, University of ϡȱ, Baltimore 

Cory Stephens, Assistant Professor, School of Nursing, University of ϡȱ, Baltimore 

Yasmine Kotturi, Assistant Professor, Information Systems, University of ϡȱ, Baltimore County 

John Schumacher, Professor and Director of Public Health Research Cener, Sociology, Anthropology, and Public Health, University of ϡȱ, Baltimore County 

Matt Fitzpatrick, Professor, Appalachian Lab, University of ϡȱ Center for Environmental Science 

Zach Zbinden, Assistant Professor, Appalachian Lab, University of ϡȱ Center for Environmental Science 

Jacob Coutts, Lecturer, Psychology, University of ϡȱ, College Park 

Dane Grossnickle, Lecturer, Institute of Applied Agriculture, University of ϡȱ, College Park 

Michael Yao Wodui Serwornoo, Associate Professor, English, Languages and Media Studies, University of ϡȱ Eastern Shore 

Victoria Volkis, Professor, Chemistry, University of ϡȱ Eastern Shore 

Mary Crowley-Farrell, Collegiate Faculty, Integrated & Professional Studies, University of ϡȱ Global Campus 

Rony Thakur, Program Director and Associate Professor, Cybersecurity and Information Technology, University of ϡȱ Global Campus 

AI, Unscripted Podcast Limited Series

AI, Unscripted is a podcast limited series co-sponsored by the ϡȱ Kirwan Center for Academic Innovation, the ϡȱ Council of University System Faculty, and ϡȱOnline, produced as part of the University of ϡȱ, Baltimore's  podcast. The series features converesations with innovative educators from diverse disciplines and insitutions across ϡȱ who share their journeys from being AI-curious to AI-confident. Each episode provides detailed explanations of classroom implementations, student feedback, and practical strategies that faculty cam implement immediately in their teaching.

Hosted by Mary Crowley-Farrell (UMGC), Michael Mills (Montgomery College), and Jennifer Potter (ϡȱ Kirwan Center), the podcast showcases faculty discussing practical applications of AI that deliver tangible improvements to teaching, including time-saving grading approaches, increased student engagement, personalized feedback, simplified creation of case studies, and enhanced critical thinking exercises. The first episode launches on August 25, with new episodes released bi-weekly through December 15 on  and . The series aims to meet faculty where they are in their AI journey, whether just beginning to explore these tools or already building confidence in their application. 

To learn more about this project, visit the AI, Unscripted Podcast Limited Series page.

Our Work in Generative AI Pedagogy

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Projects, 2022

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Projects, 2022
May 11, 2015

UMCP is in their second year of partnership with Coursera to offer MOOCs ranging from Quantum Physics to Women and Civil Rights. With over 800,000 students registered and ~13,000 signed up for the verified “signature track” option (for a fee), they are not only showing our educational leadership, but also directly improving their on-campus classes.

July 24, 2014

UMUC is among the experimental sites that will be allowed to offer competency-based education with financial aid.

July 24, 2014

UMBC participates in Learning Analytics (LA) primarily by focusing on student and faculty use of the Learning Management System (LMS). Since 2007, the University has observed that students earning a final grade of D or F use the LMS 40% less than students earning higher grades. While correlation does not equal causation, UMBC has built a "Check My Activity" (CMA) feedback tool that allows students to compare their own activity against an anonymous summary of course peers earning the same, higher or lower grade for any assignment -- provided the instructor uses the online grade book.

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