This interactive session invites faculty to share practical, creative ways they are using AI in their classrooms to support student learning. Rather than focusing on detection or restriction, the session centers on how instructors design meaningful assignments and activities that make student thinking visible. Participants will briefly share one strategy, activity, or approach that has worked in their teaching. The session creates space for cross-disciplinary learning, idea exchange, and collaborative problem-solving. This session is designed for faculty who are ready to move beyond introductory use and explore more intentional, creative, and student-centered applications of AI. Participants will leave with concrete, adaptable strategies, inspiration from across disciplines, and a clearer vision for how AI can enhance, rather than replace, meaningful learning experiences.
I redesigned my course’s final project of ethnographic assignment by shifting from a traditional academic paper to a digital storytelling format using the Adobe webpage. In the past semesters, I have noticed students were increasingly using AI generated narration in final projects, I chose not to restrict AI use but to refocus the assignment for deeper student engagement. The redesigned format encourages students to take creative ownership of their work through customized webpage layouts, integrated external links, blog elements, and original photos or videos. As a result, the final narrations have become more personalized and reflective of students’ authentic perspectives. I have noticed that the assignment redesign has improved the overall storytelling quality in the students’ submissions and strengthened their connection to the ethnographic process.
I am sharing an example of how students can use AI to engage with assigned course content, then demonstrate understanding and competency through a short video assignment. The assignment leverages AI as a support tool while preserving authentic voice, vulnerability, and connection. Students tend to be more genuine and reflective on video than in written assignments, often expressing insights that go beyond surface-level responses. It also allows faculty to see and hear students in a more personal way.
An assignment was created to help students move beyond simply understanding content to truly engaging with it on a personal level. The focus is on the history of racism in the US with particular attention to Black health and medicine, including the local context here in Louisville.
Students begin by working through a series of readings, recorded lectures, and videos that build foundational knowledge. As part of that process, they also complete two Implicit Association Tests, which often serve as a powerful entry point for self-reflection. For many students, this is the first time they’ve been asked to examine their own implicit biases in a structured way.
To demonstrate what they’ve learned, instead of a traditional paper or exam, students create a short 4–6 minute video. In that video, they respond to guided discussion prompts that ask them to connect the historical content with their own perspectives, reactions, and evolving understanding. The videos are then posted on a discussion board, where students are asked to view and respond to their peers' videos. This adds another layer of engagement, creating space for dialogue, shared perspectives, and deeper reflection. This balance is key.
Aș a Humanities instructor and a creative writer, I prize the messiness of human thinking. Since ChatGPT was first released in 2022, I’ve reclaimed my classroom and adapted most of my assignments so they now prioritize things LLM can’t do well, namely creativity and social interaction. I’ll offer some practical, easy to implement strategies for creating an unplugged classroom, everything from my “shoe organizer” cellphone policy to successfully assigning novels to a generation that many believe won’t read anything longer than a social media post. If you miss the sound of students talking, (hi!), please join me.
Students are conscious of the harmful effects AI has on learning, the environment, and society. Requiring them to use AI for an assignment, while well-intentioned, sends the message that AI is inevitable. By prioritizing critical thinking and student autonomy, giving students direct instruction on the variety of uses, types, and effects of AI and providing alternative assignments dispels this myth. Students should be encouraged to engage critically in how AI is shaping society, and instructors should cultivate a human-centered classroom culture of curiosity instead of compliance. While it’s increasingly harder to opt-out of AI, and not all AI is equally harmful, students who choose to resist AI should have opportunities to share and practice their views. Regardless of whether AI inevitability is true or not, this talk will pose important questions for students to consider when confronted with AI that encourage them to imagine a more equitable and sustainable future.
Generative AI tools are rapidly entering academic research and coursework, yet both students and faculty are still developing an understanding of how to use them responsibly and effectively. While many students have experimented with AI informally, they often lack experience applying it within an academic context. At the same time, many faculty are also navigating how AI fits into research practices, writing processes, and student assignments. This session introduces AI research appointments, a library-supported model that helps both students and faculty develop practical AI literacy through guided academic use. Modeled after traditional research consultations, these appointments provide individualized support for integrating AI tools into research workflows while maintaining ethical and scholarly standards.
NotebookLM is one of the tools that UofL faculty will gain with its new Google Gemini contract. This tool differs from other AI tools in important ways. For one, when writing answers to prompts, NotebookLM consults information that you import and control. You can import PDFs, text files, websites, or any relevant files. This process, known as Retrieval-Augmented Generation (RAG), increases the accuracy of its output, reducing the likelihood of "hallucinations" that are more common in AI chatbots. This presentation will introduce NotebookLM and show how it can be used for teaching updates and student support. We'll explore two focused use-cases: building searchable course notebooks that support students between office hours, and using web research features to efficiently audit and refresh course materials. No prior AI experience needed.
