Teaching and Learning with AI Conference

Discover how to navigate institution-wide AI implementation through the AI Strategy Compass (AISC): a human-centered framework balancing technical and cultural transformation. This interactive workshop explores six interconnected components: Urgency, Ambition + Strategy, AI Pioneer Team, Programmatic Approach, Communication, and Cultural Change. Drawing from practical implementation at Breda University of Applied Sciences, participants will engage in hands-on activities to apply the framework to their own institutional contexts. Learn how to move beyond fragmented AI initiatives toward strategic, comprehensive adoption that embeds AI literacy and ethical use across education, research, and operations.#AI-strategy #change-management #higher-education-transformation

Many institutions have adopted frameworks for AI in assessment, but translating theoretical guidelines into classroom practice remains challenging. This interactive workshop addresses the gap between policy and implementation using the AI Assessment Scale (AIAS), a five-level framework developed by Perkins, Furze, Roe, and MacVaugh (2024). Participants will engage in hands-on activities used successfully at Breda University of Applied Sciences: sorting assessment tasks by AIAS level and designing event-based assignments with appropriate AI integration. By workshop end, participants will have concrete strategies to communicate AI expectations clearly to both educators and students in their own context.#AIAS #learningactvities #ConstructiveAlignment #CurriculumIntegration 

AI can write our students' essays. It can solve their problem sets, answer their discussion posts, and pass a rubric with flying colors. So, what exactly are we grading?

This session makes the case for a radical shift: stop assessing the assignment and start assessing the student.  More specifically, let's start assessing student understanding of the work they submitted, instead of grading the work itself.  We'll discuss a cross-disciplinary toolkit for scalable, AI-resistant evaluation that reveals whether learning actually happened, regardless of how the work got done. With this framework, we can shift from "did AI write this?" to "what did my student learn?"

The presenter is recording this session for her professional portfolio. Participants will not be filmed during the session, though cameras may occasionally capture the back of the audience's heads from the rear of the room. This recording is not for commercial use or conference distribution.

A growing number of students use AI to complete assignments. Instructors should not wait until students violate AI policies to identify them for judicial review because it is a tedious, stress-filled process that results in students feeling anxiety and shame, and blaming the instructor. This presentation suggests strategies for instructors to implement AI in the classroom by requiring students to prove the provenance of their assignments. It also reviews the impact of AI on academic misconduct cases.

What if students could practice communication skills by roleplaying with an AI bot? Or engage with course concepts through personalized AI tutors? In this hands-on workshop, discover how to ethically integrate AI bots into your teaching practice through three practical approaches: First, learn three easy steps for building an AI bot. With careful planning and testing, an AI bot can bring discussion boards, classroom activities, and the process of learning skills to a new level. Second, explore ways to create meaningful activities with grading the process over product in mind. Helping students invest in their learning through AI tools is not only possible, but a way to bring their personal approach to learning to life. Third, leave this session with a game plan for developing a bot that not only meets the learning outcomes, but brings your students back time and again to continue learning.