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Clarifying AI Expectations in Your Courses

Dear Colleagues,

As we prepare for the upcoming academic year, I am pleased to introduce the Executive Committee of UConn’s AI Council: Anna Mae Duane, Amit Savkar, Derek Aguiar, Arash Zaghi, and me as chair. The Executive Committee will work with the broader AI Council to help coordinate UConn’s university-wide AI efforts through AI for ImpaCT, including work related to teaching and learning, research and scholarship, academic programs, responsible AI, and infrastructure. A broader communication introducing the full AI Council and outlining our priorities and opportunities for engagement will be shared with the University community in the first few weeks of the semester.

In advance of that broader communication, there is one issue that is particularly timely as faculty finalize their courses and syllabi. In collaboration with Desmond McCaffrey from the Center for Excellence in Teaching and Learning (CETL) and Michael Morrell, Chair of the University Senate Executive Committee, we have put together the following recommendations and resources to help faculty communicate clearly with students about the use of artificial intelligence in their courses. These recommendations are not intended to establish a single University-wide course AI policy; rather, they are intended to help faculty make intentional choices about AI in relation to their course learning objectives and communicate those expectations clearly to students.

There is no single AI course policy that will be appropriate for every course, student, discipline, or assignment. However, a course policy should ideally help students understand:

  • What uses of AI are permitted and what uses are not permitted, including whether expectations differ across assignments;
  • Whether any uses of AI are required and, if so, for what purposes and how to access those tools as specified within a Course Materials section; 
  • What AI tools the course requires students to purchase and use?
  • Whether and how the instructor will use AI in course design, instructional materials, feedback, assessment, communication, or other course activities.

Any use of AI should be thoughtfully connected to the course’s learning objectives. Faculty should consider where AI meaningfully enhances learning as well as where students are better served by completing work independently in order to achieve the intended learning outcomes. When AI is incorporated into a course, students should understand how its use supports what they are expected to learn. Similarly, when its use is restricted, explaining how those restrictions support the learning objectives can help students understand the purpose of the course AI policy.  

We also encourage you to consider sharing how you as an instructor are, or are not, using AI in the design, implementation and assessment of course materials. It is, of course, entirely up to the instructor how AI is used to further the teaching objectives of the course.  Best practices indicate that being transparent about the role of AI in all aspects of the course will build trust and avoid any possible misunderstandings.  Clear communication can reduce uncertainty for students and help ensure that AI is used—or intentionally not used—in ways that support learning and academic integrity. 

CETL has developed extensive resources to assist faculty. The Generative AI in Teaching and Learning page contains guidance for communicating expectations about generative AI use, instructional strategies, and opportunities for consultation, which is a great place to start. Additionally, on the Creating Your Syllabus page, faculty can find sample syllabus statements for generative AI use and full syllabus templates

If you have any questions or need assistance, consultation services are available from CETL.

Thank you for considering how AI relates to your courses and their learning objectives, and your expectations for students.

Sincerely,
David

David Bergman
Professor of Operations and Information Management
Associate Dean for Faculty & Research, School of Business
Provost’s Special Advisor on AI

Kun Chen Named Academic Director of UConn’s M.S. in Data Science Program

The University of Connecticut is pleased to announce that Kun Chen, Professor of Statistics, has been named Academic Director of UConn’s M.S. in Data Science program.

Chen brings to the position an exceptional record of interdisciplinary scholarship, academic leadership, teaching, and mentorship. A professor in UConn’s Department of Statistics and a research fellow in the Center for Population Health at UConn Health, his research spans statistical learning, machine learning, optimization, health data science, bioinformatics, population health, and healthcare analytics.

An internationally recognized scholar, Chen is a Fellow of the American Statistical Association and an elected member of the International Statistical Institute. In 2024, he received the College of Liberal Arts and Sciences Innovative Scholarship Award, which recognizes outstanding interdisciplinary research addressing significant challenges to knowledge, human well-being, and society. His work exemplifies the collaborative, application-focused approach that is central to UConn’s vision for data science.

As Academic Director, Chen will provide intellectual and strategic leadership for the M.S. in Data Science program. He will work across UConn’s schools and colleges to guide the program’s academic direction, strengthen its curriculum, support faculty collaboration, enhance the student experience, deepen relationships with industry and external partners, and identify new opportunities for growth and innovation.

UConn’s M.S. in Data Science is a 30-credit, career-focused graduate program offered in both an intensive, cohort-based on-campus format and a flexible online format. Drawing on faculty expertise from five schools and colleges—the College of Agriculture, Health and Natural Resources, the School of Business, the College of Engineering, the College of Liberal Arts and Sciences, and the Neag School of Education—the interdisciplinary curriculum prepares students across the full data science lifecycle, including statistical analysis, computing, machine learning, data management, visualization, communication, research design, ethics, and responsible data use. The program culminates in a team-based capstone through which students work collaboratively to address consequential, real-world challenges, often in partnership with industry and organizational collaborators.

Chen’s appointment comes at a pivotal moment for the field. As data science and artificial intelligence rapidly converge, organizations increasingly need professionals who combine advanced analytical and AI capabilities with strong statistical foundations, ethical judgment, and deep domain expertise.

Under Chen’s leadership, the program will build on its strengths in statistics, computing, machine learning, and applied problem-solving while expanding opportunities at the intersection of data science and artificial intelligence. This next phase will strengthen connections with UConn’s growing AI research and educational ecosystem, deepen industry engagement, expand the program’s national visibility, and prepare graduates to lead in a professional landscape increasingly shaped by generative AI, advanced machine learning, and intelligent decision systems. At the same time, the program will preserve the qualities that distinguish it: its interdisciplinary structure, academic rigor, commitment to responsible practice, and focus on translating technical knowledge into meaningful real-world impact.

Chen succeeds Professor Jeremy Teitelbaum, who has served as Academic Director since 2023 and is stepping down from the role. As the program’s first dedicated director following its launch, Jeremy has led the M.S. in Data Science program through a formative period of growth and development. His leadership has helped establish the program’s academic identity, strengthen its interdisciplinary partnerships, expand enrollment, and build a strong foundation for continued success. We are sincerely grateful for Jeremy’s vision, dedication, and service, and we thank him for the lasting contributions he has made to UConn’s M.S. in Data Science program.

Announcing AI for ImpaCT: UConn’s University-Wide AI Initiative

Dear Colleagues,

Artificial intelligence (AI) is transforming the way we work, learn, and live. Over the past several months, I have been engaging with our community to shape a University-wide initiative to be responsive to AI advancements and coordinate AI-related work across units.  I have met personally with the University Senate and faculty, staff, and academic leaders in small groups and during school and college meetings. Those conversations have made clear that UConn has important strengths in AI, that we need a framework to build on our strengths, and to guide and coordinate our institutional strategy around AI in an ever-changing technological landscape.

Coordinated Leadership Around AI

Today, I’m pleased to announce AI for ImpaCT, a coordinated university-wide initiative designed to connect and advance AI efforts across our academic, research, operational, and public service missions. The goal of AI for ImpaCT is to support interconnectivity among teaching, learning, research, innovation, and societal impact and to encourage safe, ethical, and responsible use of AI. The vision for beneficial and ethical AI is beautifully articulated by one of our student clubs.

The leadership structure around AI for ImpaCT is taking shape. I have appointed David Bergman, Associate Dean for Faculty & Research and Professor of Operations and Information Management, as the Provost’s Special Advisor on AI to help coordinate AI for ImpaCT initiatives across the university and advise my office on emerging issues related to AI in teaching, research, workforce development, and university operations.

The Special Advisor will chair an AI Council comprised of representatives from across the university including faculty, staff, and students. The AI Council will help set priorities, identify opportunities and challenges, and support university-wide coordination as AI continues to evolve. Consistent with UConn’s commitment to shared governance, the AI Council will serve as a coordinating resource and work closely with the University Senate and other governance bodies on AI-related matters within their areas of responsibility.

The AI Council will work closely with university leadership, ITS, UConn Health, and administrative units as the university explores AI applications and technologies, institutional needs, training, and the use of AI tools across university operations. A smaller AI Executive Committee comprised of members of the AI Council will liaise with the Special Advisor to advance priority initiatives and coordinate work between meetings of the broader AI Council.

The AI Council will support development of a university-wide web presence to help share resources, updates, opportunities for engagement, and ways for members of the UConn community to participate in this work. I also encourage faculty, staff, students, and partners to share ideas and engage with the Council as opportunities emerge.

CURRENT INITIATIVES

The initiatives and work areas below reflect some of the important work being done at UConn to prepare our community for the AI transition.

Preparing Students for an AI-Enabled Future

Preparing learners for a world increasingly shaped by AI will be an important part of AI for ImpaCT. In partnership with the AI Council and in consultation with deans, faculty experts, and the University Senate, we will continue building academic programs and learning opportunities that align with both student interest and workforce needs.

Earlier this year, the Board of Trustees approved the university’s first graduate certificate built around an “AI + X” model with the launch of AI for Business through The Graduate School. We expect additional programs in other disciplines to follow in the next academic year.

The AI Council and AI Executive Committee will work closely with academic units to help guide the development of proposals for an undergraduate minor in AI, with the goal of launching as early as this fall, and a university-wide undergraduate AI major is targeted to launch in Fall 2027. We are in the process of evaluating how programs such as the M.S. in Data Science can help support and expand AI-related education and research opportunities across the university. There are also several existing programs across the schools and colleges that include concentrations in AI or have foundational AI topics infused in the curriculum.

In addition to degree programs, UConn will expand AI literacy and workforce development through online and non-credit offerings, employer partnerships, and micro-credentials that could potentially support both current students and members of the broader community.

Teaching, Learning, and the Use of AI

Faculty, staff, and students are already working through questions related to teaching, learning, assessment, academic integrity, research, privacy, fairness, and the use of AI applications across academic and administrative settings. We will continue building guidance and support in these areas by drawing on expertise that exists in our university community.

The Center for Excellence in Teaching and LearningThe Graduate School, and faculty and staff in the schools and colleges are helping support AI efforts through faculty development, course design support, guidance for graduate students and instructors, and ongoing conversations around appropriate and effective uses of AI in academic settings.

The AI Council will be charged with helping coordinate AI efforts in teaching and learning, identifying areas where additional support is needed, and sharing effective practices with the University community.

AI Research and Public Engagement

AI-related research and scholarship are being conducted at UConn in many disciplines. Faculty are advancing foundational AI research, applying AI across industries and professions, and examining the broader societal impact of these technologies in fields such as healthcare, business, engineering, education, the humanities, social sciences, and the arts. The Humanities Institute’s “AI and the Human” initiative is one example of interdisciplinary scholarship exploring the societal  implications of AI.

UConn’s partnerships with organizations such as Morgan Stanley, Intel, Eversource, Electric Boat, Pratt & Whitney, and many more, along with ongoing clinical, research and educational efforts at UConn Health, are creating new opportunities for applied research, workforce partnerships, and public engagement connected to AI.

Federal agencies and other major funders continue expanding investments in AI-related research in many sectors. The Office of the Vice President for Research is already leading campus-wide discussions about UConn’s strengths to identify opportunities for greater interdisciplinary collaboration and external partnerships.

Innovation, Entrepreneurship, and Workforce Partnerships

Connecticut’s workforce needs to adapt as AI reshapes industries and professions, and UConn will play a major role in preparing our state for a rapidly changing future by offering continuing education, online learning, non-credit programs, and employer partnerships. Earlier in this message, I referenced the potential for expanded micro-credentials and other flexible learning opportunities that can help both current students and working professionals build AI literacy and discipline-specific skills throughout their careers.

We also see strong connections between AI and UConn’s growing innovation and entrepreneurship ecosystem. Important work is already happening through schools and colleges, research centers, UConn Health, the Werth Institute, and other campus partners. As AI for ImpaCT develops, we want to connect these efforts and support opportunities related to startups, technology transfer, industry collaboration, educational technology, and other forms of innovation and revenue generation connected to AI.

Moving Forward

As Connecticut continues to establish policies and frameworks like the bill recently passed by the General Assembly, UConn and the AI Council have a responsibility to help guide the state through opportunities and challenges AI presents across education, industry, healthcare, and the workforce. UConn is well positioned to understand AI and anticipate what may come in the future to help inform policy decisions.

I’m excited about the conversations ahead and grateful for the thoughtfulness, creativity, and expertise that so many members of our community are already bringing to this space. I look forward to advancing the work of the AI for ImpaCT initiative with you and will continue to share updates on our progress.

Pamir Alpay, PhD
Interim Provost and Executive Vice President for Academic Affairs
University of Connecticut

Professor Deirdre Simmons

AI is a technological advancement that has been met with criticism and suspicion, especially in the academic arena.  COMM 2100 – Professional Communication, taught by Deirdre Simmons, is a redesigned course that embraces AI and promotes its practical and ethical use through contextual learning, Socratic questioning , and lectures within the context of professional communication.  The text used is “Clear Communication, Powerful Results,” and some of the course objectives are to:

• Identify and analyze ethical issues in AI through real-world professional case studies.

• Apply ethical decision frameworks to AI-driven crisis communication situations.

• Utilize AI tools to develop innovative solutions for communication challenges faced by organizations.

• Design and implement effective AI-powered social media campaigns to mitigate organizational crises.

• Create reports and cover letters that are AI-assisted, and student-edited to reflect their authentic voice

Posted in AI

PHYS 1201Q

Algebra-Based Introductory Physics, taught by Dr. Aslı Tandoğan, integrates AI-powered teaching tools developed using open-source generative AI models (Ollama), hosted on a server provided by CLAS IT (Eric Soares). The system includes custom-built Model Context Protocols (MCPs) that allow the AI to go beyond static answers by solving problems, triggering workflows, and interacting with external tools in real time.

Key Features:

• Real-time student interaction via custom User Interface

• AI functions as an in-class teaching assistant

• Covers algebra, kinematics, forces, and more

• MCPs extend AI capabilities beyond text generation

• Supports hands-on conceptual learning during lectures

Undergraduate student Jakub Pierog contributed to the development of the MCP servers used in this project.

Posted in AI

Dr. Luyi Sun, 2025 Board of Trustees Distinguished Professor

The Board of Trustees Distinguished Professor title is awarded annually following a university-wide nomination process and a rigorous review by a faculty and student committee. Final selections are approved by the UConn Board of Trustees, which confirmed this year’s awardees at its June 25, 2025 meeting.

Luyi Sun

Dr. Luyi Sun is a globally recognized materials scientist and professor in the Department of Chemical and Biomolecular Engineering at the University of Connecticut, where he also holds a joint appointment in the Institute of Materials Science. Since joining UConn in 2013, he has led an internationally renowned research program focused on nanostructured hybrid materials for functional, environmental, and energy-related applications.

Dr. Sun’s prolific contributions to science are evidenced by over 310 peer-reviewed journal articles in high-impact publications such as Nature CommunicationsScience AdvancesProceedings of the National Academy of Sciences, and Advanced Materials. His work has earned more than 23,000 citations and an h-index of 83, and has been highlighted by MIT Technology ReviewSmithsonian Magazine, and New Scientist, among many others. He is the inventor or co-inventor of 28 issued U.S. patents and more than 50 corresponding foreign patents, seven of which have been commercialized/licensed. The materials and devices invented in his lab have been featured in global exhibitions, including at the Material ConneXion Library in New York and the Penn Museum.

Dr. Sun is a Fellow of the National Academy of Inventors, the Royal Society of Chemistry, and the Society of Plastics Engineers. He has also been recognized with the Morand Lambla Award from the Polymer Processing Society and was elected to the Connecticut Academy of Science and Engineering.

A dedicated educator and mentor, Dr. Sun has taught rigorous and interdisciplinary courses such as Thermodynamics and Polymer Processing, and has advised dozens of Ph.D. students, M.S. students and postdoctoral researchers, and more than 160 undergraduate research assistants. His students have gone on to successful careers in academia and industry, and many have received prestigious fellowships and national honors.

Dr. Sun has also demonstrated sustained leadership in academic and professional service. As Director of the UConn Polymer Program from 2018 to 2021, he expanded faculty engagement and strengthened the program’s profile. He has held leadership roles in national scientific organizations and organized more than 80 symposia around the world. His editorial work includes serving as Associate Editor of Advanced Composites and Hybrid Materials.

Due to his outstanding record of research innovation, teaching, mentorship, and professional service, Dr. Luyi Sun strongly merits recognition as a Board of Trustees Distinguished Professor.

Professor Anne C. Dailey, 2025 Board of Trustees Distinguished Professor

The Board of Trustees Distinguished Professor title is awarded annually following a university-wide nomination process and a rigorous review by a faculty and student committee. Final selections are approved by the UConn Board of Trustees, which confirmed this year’s awardees at its June 25, 2025 meeting.

Anne Dailey

Professor Anne Dailey, Associate Dean for Faculty Development and Intellectual Life and the Ellen Ash Peters Professor of Law at the University of Connecticut School of Law, is a nationally recognized scholar whose work bridges constitutional law, family law, and psychoanalytic theory. A member of the UConn faculty since 1988, Professor Dailey has made transformative contributions to legal scholarship, education, and public service, with far-reaching influence across disciplines and institutions.

She earned a Bachelor of Arts in English from Yale University and a Juris Doctor from Harvard Law School, where she served as an Articles Editor of the Harvard Law Review. Following law school, she completed a judicial clerkship with Judge José Cabranes of the U.S. District Court for the District of Connecticut. She has since become a pioneering figure in integrating psychoanalytic theory into legal analysis, most notably through her acclaimed book Law and the Unconscious: A Psychoanalytic Perspective, published by Yale University Press. This work received three prestigious honors: the Book Prize from the American Psychoanalytic Association, the Book Prize from the American Board and Academy of Psychoanalysis, and the Faculty Book Award from the UConn Humanities Institute.

Professor Dailey’s scholarship is widely cited and influential. Her co-authored articles The New Law of the Child and The New Parental Rights, and her sole authored In Loco Reipublicae, all published in top-tier law journals, have shaped the national discourse on children’s constitutional rights, state responsibility for families, and evolving family structures. She is a member of the American Law Institute and the Association for the Study of Law, Culture and Humanities.

She has held visiting faculty appointments at Yale, Harvard, and Penn Law Schools and has been named an Erikson Scholar at the Austen Riggs Center and a Fellow at the Katz Center for Advanced Judaic Studies at the University of Pennsylvania.

Professor Dailey is a dedicated and inspiring teacher of family law and constitutional law. She is also a deeply valued mentor to students and junior faculty, and her efforts have helped elevate the national profile of the UConn School of Law.

Professor Dailey’s scholarly distinction, interdisciplinary innovation, and enduring contributions to teaching and service make her a truly worthy recipient of the University of Connecticut’s highest faculty honor.