Artificial intelligence is changing how we teach, learn, and assess at Ohio State. Faculty are reconsidering what meaningful assessment looks like, while students are navigating new questions about how and when to use AI in ways that support their learning. These challenges affect all of us.
This space is built around the idea that we can learn from one another. By sharing questions, experiences, experiments, and reflections from members of the Ohio State community, we hope to create opportunities for conversation so we can collaborate and thrive in this rapidly changing educational landscape.
Questions We Are Exploring Together
Across campus, faculty, staff, and students are asking difficult questions about how AI is changing teaching, learning, and assessment.
- What does meaningful assessment look like when students have access to generative AI?
- How can AI support learning without replacing the thinking we want students to do?
- How do students understand when, why, and how they should use AI?
- What can instructors learn from students about how AI is affecting their learning?
- How can we design assessments that provide meaningful evidence of student learning?
Learning from the Ohio State Community
These scenarios share how members of our teaching and learning community are responding to these questions so we can learn from their experiences, reflections, and ideas.
AI-Enabled Text Analysis in Marketing Research
Instructor: Jeffrey P. Dotson
Department: Marketing and Logistics
Course: BUSML 4202: Marketing Research
Students in BUSML 4202 analyze a large sample set of customer satisfaction data using a multi-stage process that enables them to experience three distinct approaches: manual coding, computational text analysis, and prompting large language models to process the data. Learn how using AI as a collaborator (rather than a shortcut) expands students' understanding of AI’s role in the research process while preparing them for their future careers.
Exploring Target Audiences with AI
Instructor: Mary Sterenberg
Department: School of Communication
Course: COMM 3334: Strategic Message Design
In Strategic Message Design, an upper-level writing course, students identify target audiences and develop strategic messages for a real-life client. Initial brainstorming often leads student to select familiar or oversimplified audiences, but class time for deeper exploration with instructor input is limited. Learn how structured AI prompting exercises helped the instructor scale her ability to guide students to explore more complex audiences while practicing critical AI and information literacy skills.
How can AI help me assess what 300 students find confusing before class?
Instructor: Matthew W. Stoltzfus
Department: Chemistry and Biochemistry
Courses: CHEM 1210 and CHEM 1220 (General Chemistry I and II)
Students in CHEM 1210 and CHEM 1220 complete pre-lecture assignments by submitting questions about concepts they find confusing, generating hundreds of written responses before class. At this scale, manually reviewing and synthesizing enough responses to identify patterns in student thinking is impractical. Learn how generative AI can help organize this formative assessment evidence so instructors can identify areas of confusion and use class time to address concepts that most need clarification.
In the AI era, how well do students engage in critical thinking about their research?
Instructor: Jenny Patton
Department: Engineering Education
Course: ENGR 2301 Citizenship in Engineering Contexts
Students in ENGR 2301 present highlights of their weeks-long research projects in 3- to 5-minute Lightning Talks, but it's become increasingly difficult to assess whether they used AI, and, if so, how well they engaged in critical thinking about the findings. Learn how the addition of Q&A sessions gives students opportunities to demonstrate their knowledge and on-the-spot thinking while enabling the instructor to better assess their analysis of findings.
Show Your Work! Making the Process of Teamwork Transparent
Instructor: Liz Sanders
Department: Design
Course: Design 4200: Design Research Two
In Design 4200, students complete a co-design research project for which they plan, execute, analyze and present their research as a team. Learn how the instructor evolved this research assignment to place equal importance on the process and final product by requiring detailed project documentation on a virtual whiteboard—including explanations of how students used AI to complete research tasks.
Using AI to Foster Appreciation for Underrepresented Perspectives
Instructor: Steven Brown
Department: Philosophy
Course: PHILOS 1100: Introduction to Philosophy
In this introductory Philosophy course, students explore a variety of perspectives they may find unfamiliar or disagree with. Discussing unfamiliar and divergent viewpoints in class can place the burden of explanation on some classmates while others may be hesitant to ask questions. Learn how AI chatbots are helping the instructor remove obstacles to learning about, critically evaluating, and appreciating unfamiliar perspectives.