✨Guide: Crafting Your Syllabus' AI Policy

How to set norms for both student and professorial AI use in your college course.

[image created with Dall-E 3 via ChatGPT Plus]

Welcome to AutomatED: the newsletter on how to teach better with tech.

Each week, I share what I have learned — and am learning — about AI and tech in the university classroom. What works, what doesn't, and why.

In this fortnight’s Premium edition, I present a guide to help professors develop and express their overall stance on AI use in their courses. This guide covers both student use of AI and professorial use.

🖼️ The Big Picture

In this guide to developing AI policies for university-level syllabi, I recommend that you, the professor, take a holistic approach that addresses both student AI use and your own professorial AI use. This not only creates an equitable culture of honesty and trust but also the opportunity for a dialogue between you and your students about the evolving role of AI in our collective learning experience.

When you develop and refine your student AI use policy, I recommend aligning your views on AI integration, institutional policies, departmental and field standards, and course objectives. I suggest that professors need to consider how students would ideally use AI to achieve their courses’ objectives, before turning to incentivizing students to use AI in those ways (or, perhaps, incentivizing them to not use AI at all). I discuss providing guidelines demarcating responsible AI use from AI misuse, as well as the importance of assessing students' familiarity with AI, ensuring equitable access, and providing AI training opportunities if needed.

Regarding your development of your professorial AI use policy, I advocate you start by clearly defining the scope of your AI use cases in connection with your course, ranging from brainstorming to using personally identifiable student data. I discuss a range of data use strategies, such as restricting AI use to non-student data or obtaining explicit consent when sensitive student data is involved. Throughout, I stress the importance of transparency and flexibility depending on the context.

In both cases, I provide two generic examples of AI use policies, one AI-inclusive and one AI-exclusive, that incapsulate the lessons of the guide and that can act as starter policies as you develop your own.

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