Teaching and Learning with AI Conference

Why do students use AI blindly? Because it’s easy, just like most of the information they consume every day. This session gives educators practical ways to help students slow down, test AI’s answers, and recognize where the “easy” approach falls apart and why the shortcut rarely beats actually thinking. Attendees will leave with practical strategies, from full lessons to quick, bite‑sized tasks, that make this exploration engaging, eye‑opening, and just a bit entertaining.

Introducing the AI Alt-Text Helper, a tool designed to enrich accessibility in LMS course content. Currently being rolled out to all Canvas courses at the University of Michigan, this solution leverages LLM and Canvas APIs to apply efficient alt-text suggestions while keeping instructors in control. We will demonstrate the development journey from a Flask proof-of-concept to an LTI-integrated solution and highlight how to balance generative AI with proper oversight. Join us to explore how AI tools can improve equitable student outcomes. #Accessibility #GenerativeAI #EdTechDevelopment

In a hybrid biotechnology course (wet-lab + computational), we redesigned a mini-grant innovation pitch so GenAI accelerates ideation and critique without outsourcing thinking. The model pairs scaffolded inquiry (claim → evidence → mechanism → limits → feasibility) with two chatbot tutors: a Socratic evidence tutor that interrogates primary-paper figures and prompts counterarguments, and a workflow coach that guides protocol and pipeline execution (controls, parameter choices, troubleshooting, and “why this step” reasoning) while refusing to write graded text or analyses. We share tools, policies, and student outcomes. #critical-thinking #responsibleAI #chatbot-tutors

In this session, I argue that educators should build custom, purpose-built AI tutors rather than rely exclusively on enterprise AI tools. I will discuss my own effort to build a transparent and responsible AI tutor for my Fall 2024 Ethics and Artificial Intelligence course (see here and here for articles that describe the project). I will present my views about how bounded, deterministic instructional logic can be used to constrain AI tutor behavior, such that these that these tutors enhance student reasoning rather than replace it. I will also describe my IRB-backed plans to rigorously assess the impact of this tutor on student learning outcomes in my Fall 2026 version 2.0 of the course. 

For those interested in my earlier work on AI and education, including applications that allow students to have conversations with philosophers and play various types of educational games, I also invite you to view this video lecture: https://youtu.be/yXJ0b2_6C6s?si=NfQcMSjJuwbEzvjl

As AI becomes an essential workforce competency, students need assignments and experiences that teach them to use generative tools ethically, transparently, and effectively. This session highlights how librarians can partner with faculty to connect course‑based AI tasks to real‑world career preparedness. Through new or redesigned assignments, ethical use guidance, and scaffolded activities, students learn to evaluate, question, and responsibly apply AI in ways employers now expect across industries. Participants will leave with adaptable models for teaching AI literacy that benefit both academic success and career readiness.Keywords: #AIfluency #CareerReadiness #EthicalAI

This session positions AI tools as an essential mechanism for supporting students with learning and attention differences, grounded in theories from Vygotsky’s zone of proximal development to distributed cognition. It distinguishes cognitive barriers arising from peripheral demands from those related to conceptual understanding. Drawing on scaffolding, cognitive offloading, and translation, the session argues for equity through intentional task design rather than individual exception. It concludes by examining the pedagogical trade-offs between AI-supported cognition and the pursuit of tool-independent mastery.

This practice session demonstrates how futures thinking and generative AI can be integrated into community college classrooms to strengthen adaptability, resilience, and creativity. Developed collaboratively by the Business Innovation & Technology Center and Learning Resources at Miami Dade College, the initiative includes faculty workshops, student-focused experiences such as the “Career Lab powered by AI,” and interdisciplinary presentations on the future of arts, libraries, and life sciences. In this session, participants will engage in hands-on activities and AI-assisted exercises that can be embedded into existing courses without full redesign, leaving with practical tools grounded in futures pedagogy.

This presentation showcases a series of AI‑driven roleplaying bots designed for an Introductory Mythology course. Each bot embodies a classic mythological trickster, engaging students in interactive dialogue that blurs the line between mischief and wisdom. Through these conversations, students investigate whether these figures are truly malicious or simply navigating their journeys with wit rather than force. The project demonstrates how AI‑supported roleplay can deepen engagement, encourage critical interpretation, and create dynamic learning experiences within the humanities.

As institutions grapple with AI’s impact on teaching, faculty development models reliant on one-off workshops or tool training often fall short. This session shares findings from a collective, lab-based model in which instructors experiment with AI in courses, learn from peers, and receive guidance from pedagogical and technical experts. The lab is an active collaboration between faculty and staff and operates as a sandbox for co-creation, reflection, and sensemaking, centering student learning while generating data to inform institutional AI strategy. Participants will explore key patterns, tensions, and design insights and consider how this approach builds capacity for AI-rich, human-centered teaching.

AI can now generate detailed stakeholder analyses, harm-benefit calculations, and ethical recommendations in seconds. This session explores what happens when students begin outsourcing ethical reasoning itself to AI - and what that means for the future of workplace decision-making. Drawing on examples from business ethics, organizational behavior, and cross-cultural management courses, the presentation shows how AI acts as a “moral calculator” while humans remain responsible for judgment, justification, and accountability in organizations. (#AI-ethics #moral-agency #decision-making)