Teaching and Learning with AI Conference

This study explores how personalized Generative AI can transform entrepreneurship education through deeper cognitive engagement and experiential learning. We introduce the Business Model Canvas Coach, an AI-driven chatbot designed to guide hospitality and tourism students through inquiry-based prompts, Socratic dialogue, and iterative reflection while applying the Business Model Canvas. Our research examines whether AI-mediated scaffolding enhances problem identification, business model integration, and critical thinking. Findings aim to inform educators on designing AI as a cognitive partner, empowering learners to move beyond passive use toward active, creative entrepreneurial practice.

Stop the "app hop." Faculty are currently drowning in a fragmented tech stack, juggling multiple AI subscriptions for research, drafting, and slide generation. This interactive session demonstrates how to collapse that friction into a unified, secure ecosystem using NotebookLM and Gemini.We will showcase a "source-first" workflow: grounding AI in your specific syllabi and research to eliminate hallucinations, then instantly transforming those insights into course assets. Participants will leave with a practical blueprint to reduce costs, ensure academic integrity, and reclaim prep time using a streamlined Google workflow.

Faculty at teaching-intensive institutions are constantly balancing the need to create engaging, rigorous learning activities with limited time and heavy teaching loads. This interactive session shares a practical, step-by-step approach to using AI to transform basic course materials into narrative-based case studies. Using an insulin signaling case study from my introductory biology course as an example, I will show how a simple Q&A activity evolved into an engaging case study that incorporates clinical data. Participants will learn to refine AI prompts, evaluate outputs, and make pedagogical choices that support student engagement while maintaining scientific rigor, with applications across STEM disciplines.

This presentation shares practical lessons learned from designing and delivering an AI-enhanced library research workshop for students, faculty, and staff across disciplines. It examines how the GUIDE model emerged from instruction, organized around five strategies: (1) selecting appropriate AI tools, (2) using intentional prompting informed by the CLEAR framework, (3) investigating and refining research topics, (4) verifying information using SIFT, and (5) navigating citation practices. Aligned with the ACRL Framework for Information Literacy, the session highlights what worked, unexpected outcomes, and ongoing challenges from teaching AI in practice. Attendees will leave with adaptable approaches for supporting responsible AI use, academic integrity, and research instruction alongside traditional scholarly resources.
#AIinResearch #InformationLiteracy #FacultyDevelopment

The Metadata Creation and Management Department, in collaboration with the Digital Scholarship Department at the University of Central Florida (UCF) Libraries, is exploring the integration of Artificial Intelligence (AI) into digital collections management and workflows. Leveraging the OpenAI API and a custom FAST (Faceted Application of Subject Terminology) vector database, the project generates subject headings and semantic enrichment for collections within UCF’s repository and library management system. These efforts, combined with linked data enrichment from external knowledge bases, enhance resource discovery and user engagement. Together, they demonstrate a scalable, collaborative approach to enriching metadata and advancing discovery through responsible AI.

AI can do a lot of the heavy lifting in course improvement—but what happens when efficiency starts eroding the nuance that makes teaching effective? This session uses a real-world case study of 17 social work learning materials to explore the tension between scaling instructional design work with AI and preserving the human judgment that gives courses their integrity. Through a brief before-and-after example and structured discussion, participants will wrestle with questions that don't have easy answers: What must stay fully human? How do we keep AI from standardizing the complexity out of courses? Leave with one concrete guardrail and a framework for thinking more critically about where AI belongs—and where it doesn't—in course improvement work.

In this session, I share an assignment from my media literacy teaching methods course that positions generative AI as a starting point, rather than a shortcut, for instructional design. I show how my pre-service teachers used AI to generate unit plans, then revised, curated, and personalized those plans to align with standards, teacher-produced Essential Questions, and student-centered texts. Using student reflections and sample artifacts, this session offers a practical generate, adapt, curate framework for helping novice instructors use AI to reduce cognitive load while preserving pedagogical expertise and creativity.

What does it mean to build AI fluency in an introductory college course, and where should instructors begin? This short presentation explores how AI was embedded into the course content of an introduction to psychology course. Students were also provided with a specially designed AI assistant, allowing them to practice AI use and prompt engineering while learning about bias and limitations of broader AI tools. The session invites discussion about teaching students about how AI works, when its use is appropriate, and where human judgment, reflection, and disciplinary thinking must remain central to learning.

Let's be real: AI isn't going anywhere, and neither is the panic about student voice. But what if we stopped treating AI like the villain in our writing classrooms and started using it as the world's most patient revision buddy?This session is for instructors who want practical strategies—not philosophical hand-wringing—for teaching writing in the age of ChatGPT. We'll explore how to position AI as a tool that sharpens student voice rather than erases it, using side-by-side comparisons, revision exercises, and authorship conversations that actually stick.You'll leave with classroom-ready approaches that help students recognize what makes their writing theirs—and why that matters more than ever. Come curious, leave equipped, and maybe even a little less stressed about the robots.

Online discussion boards often suffer from low participation and surface-level engagement, even when instructors apply best practices in discussion design. Large language models (LLMs), however, were designed to support sustained conversational interaction. This session asks: what happens when students are given the choice between discussions with a LLM or traditional peer-to-peer interaction on a discussion board? Drawing on early experimentation in an online freshman seminar, the session examines unexpected outcomes, student reactions, and lessons learned about the evolving role of discussion boards in the AI era.