Note: University leadership received multiple AI-related questions following this event; we鈥檝e broken them down by topic below.
Supporting faculty and exploring AI鈥檚 impact and opportunity across OHIO
Since Fall 2022, OHIO鈥檚 Center for Teaching, Learning and Assessment (CTLA) has been leading the University鈥檚 exploration of the opportunities and impacts of Generative Artificial Intelligence (GenAI) on teaching and learning in higher education. These efforts have been geared toward fostering an academic environment that is well-positioned to take a principled implementation and integrative approach to GenAI to promote student achievement and offer communities of support and practice for faculty, including the creation of assignments and assessments that are designed to address concerns surrounding academic integrity or plagiarism.
More specifically for faculty, the CTLA recently launched an asynchronous GenAI in Teaching and Learning Institute. This opportunity is open to all faculty and staff and is helping faculty to reflect on their personal beliefs regarding AI in academia, craft a syllabus statement that aligns with their pedagogical values and articulate their expectations for ethical AI use to support student learning and integrity. Additionally, it is providing faculty opportunities to identify and implement AI-driven tools or strategies in their own courses that can improve student outcomes or enhance their own teaching capacity.
The CTLA has also supported five faculty fellows who are exploring use cases and providing extensive training on GenAI. In addition to presenting their work on a variety of local, state and national platforms, they have also helped the CTLA construct a position statement on the use of GenAI in teaching.
These activities represent just a portion of the support the CTLA has provided faculty to help them individually determine the most effective implementation or mitigation of GenAI in their courses. Faculty who have engaged in CTLA professional development institutes have created their own well-considered course policies on GenAI that range from most restrictive (no GenAI use allowed) to least restrictive. They are also.
Any instructor concerned about GenAI use by students or seeking conversation about concerns are welcome to contact the CTLA to collaborate with CTLA staff or faculty fellows. The CTLA has also delivered sessions and workshops to departments and UC1900 instructors; their team is happy to visit with OHIO鈥檚 teaching teams, programs and colleges that interested in establishing their own approaches and policies related to GenAI.
Supporting academic integrity across online learning
There are many methods and approaches to enhance the design of online courses to support academic integrity. Of course, there are challenges specific to online courses, particularly asynchronous online courses. Moreover, past practices, such as requiring online students to take courses in person at the testing center is counter to the goals of online programs, which may attract students from across the nation and internationally.
The Office of Instructional Design and the Center for Teaching, Learning, and Assessment and its faculty fellows offer consultations and workshops on designing multiple choice questions and robust question banks that can be deployed with questions aligning to learning outcomes so that students do not receive the same test. They are also available to consult on alternative assessments and peer assessments that may promote student engagement with assignments while still satisfying instructors鈥 need for rigor. Some are available here.
The university is currently evaluating several online testing services to provide digital proctoring or testing solutions. For information on this process, contact the Office of Information Technology. The current solution is .
Addressing the environmental impacts of GenAI
As noted within the CTLA鈥檚 faculty-developed position on GenAI empowering AI literacy equally requires effective practices and ethical considerations. As such, many of the CTLA鈥檚 learning opportunities also help to provide a broad understanding of the ethical contexts in GenAI, including inherent biases embedded in programming or training, exploitation of human trainers of large language models (LLMs) and power consumption of servers.
Additionally, faculty experts across the University are researching and addressing the environmental impacts of GenAI and helping identify ways to more broadly improve AI鈥檚 energy efficiency.