Teaching and Learning with AI Conference

As AI tools make it easier for students to create polished work, it has become more challenging for teachers to assess what students have truly learned and to grade fairly when AI is used. In this session, you will explore a framework developed in secondary classrooms, for using AI purposefully while ensuring students remain responsible for their own ideas. You will learn how to redesign classroom tasks so that students’ thinking, revisions, and progress are visible at every stage. You will also leave with a practical grading approach for AI-rich classrooms that will not increase your workload or lower your standards.

As generative AI becomes part of everyday student writing, faculty are again facing familiar questions about academic integrity, now complicated by these new tools. This session shares a practical approach, developed in upper-division music history courses, for integrating AI into writing assignments without undermining learning. Fundamental to the model is an instructor-designed custom GPT chatbot, used only at the draft stage and limited to grammar and formatting feedback. When combined with a clear AI policy, scaffolded low-stakes writing stages, and process-focused assessment, this approach supports critical thinking while preserving student voice and ownership of ideas. (#Academic Integrity #Instructor-Designed AI)

I will share how I fostered AI fluency in my classes through authentic, discipline‑based assignments. Using the 4D AI Fluency Framework (Delegation, Description, Discernment, and Diligence) I guided students to ethically and creatively integrate AI into real‑world tasks such as media production, research analysis, and instructional planning. This approach empowered students to critically evaluate AI and reflect on their learning, developing technical skills and human‑centered judgment essential for responsible, innovative AI use in their fields.