Teaching and Learning with AI Conference

This session presents a set of evidence‑informed guidelines for integrating AI‑supported case history interviewing practice into communication‑focused clinical education. Drawing on insights from an applied research project that compared AI‑facilitated simulation with traditional instructional methods, we summarize the primary conclusions supported by the data about designing effective prompts, structuring practice sessions, and supporting student performance. This presentation highlights practical, scalable strategies educators can adopt to enhance student confidence and competency in foundational interviewing skills. #clinicalskills #aienhancedclinicaleducation #competencybasedsimulation

Artificial intelligence is rapidly reshaping higher education, yet many faculty struggle to move beyond policy statements into meaningful classroom implementation. This session presents a practical framework for embedding AI tools and agents directly into course assignments, using a Health Data Analytics course (HLTH 212) as a case study. Participants will explore how AI can support data analysis, critical thinking, and skill development while maintaining academic integrity. The session emphasizes assignment design, transparency, and transferable strategies that can be adapted across disciplines.#AIinTeaching #AssignmentDesign #PracticalAI

Faculty are increasingly expected to integrate AI into teaching while preserving academic integrity and authentic student learning. This session offers a faculty-centered discussion of the lived classroom realities of student generative AI use—particularly the “AI confidence problem,” in which AI-generated writing can sound polished and authoritative while containing oversimplifications and missing nuance. Participants will reflect on common faculty challenges including uncertainty about student authorship and the emotional labor associated with trust and accountability in AI-enabled classrooms.Rather than framing AI as simply “allowed” or “banned,” this presentation proposes a values-driven approach to responsible AI use grounded in three core principles: transparency, verification, and student ownership of learning. The session shares a case study of redesigning an undergraduate writing assignment on culturally informed end-of-life communication. The redesign requires students to generate an AI response (Part 1) and then complete a structured credibility audit (Part 2) by identifying missed nuance or inaccuracies using five academic sources and a “claim → source → correction” method.

Despite decades of empirical research in multimedia learning, many higher ed videos often suffer from "Death by PowerPoint"—cluttered, cognitively taxing, hindering learning and learner engagement. This session introduces the Multimodal Video Evaluator (MVE), a custom AI bot designed to close the research-practice divide by translating scientific research into an automated, systematic pedagogical auditor. The MVE codifies a 15-year synthesis of the Cognitive Theory of Multimedia Learning (CTML) and video engagement studies into 127 actionable design guidelines.
By replacing pedagogical guesswork with a systematic approach to rapid design-revision cycles, the MVE empowers educators to systematically transform passive, distracting slides into high-impact visual tools that significantly improve student comprehension, memory retention, and learner engagement.
To foster institutional adaptation, I will reveal the MVE’s full design architecture, including its specialized knowledgebase and system prompt. I will discuss calibration features used to ensure accurate and consistent auditing and prevent hallucinations of generic AI. By sharing these internal blueprints, I provide attendees with the technical and pedagogical insights needed to replicate and refine this work at their own institutions, moving AI from an efficiency tool to a framework for quality assurance and competency building for faculty, instructional designers, and students.

My Substack Publication "eLearning Expert": https://elearningexpert.substack.com/  
My LinkedIn: https://www.linkedin.com/in/k0ichisat0/