Harte Center AI Toolkit
Teaching and Learning with AI, by Design
In this era, we simply cannot pretend AI doesn’t exist. Teaching methods that worked in the past may not work today. Our goal is to support teaching and learning in ways that do not contribute to cognitive surrender.
Where would you like to start?
Set a course-level policy, or focus on particular assignments and class activities.
Syllabus Statement Builder
Build a ready-to-paste course AI policy from AI-generated, human-reviewed suggestions.
- 5–10 min · PDF or Word
- Scope, rationale, where AI is and isn’t allowed, and responsible-use expectations.
Assignments in Practice
Real assignments from faculty wrestling with how to teach in an AI-saturated world.
- Each includes
- Student instructions, explicit AI guidance, and honest faculty reflection.
Assignment Mapper
Break an assignment you teach into parts, name what each teaches, and decide AI’s role.
- You’ll create
- Guidance for your assignment instructions that shows students which parts they do themselves, where AI can help, and why.
Share Your Assignments with Us
Working beautifully or still iterating, your design thinking helps all of us teach better. Email JT Torres
More Resources
- AI in Education Cheat Sheet (Padlet)
- AI Bytes (Padlet)
Assignments in Practice
Explore real assignments from faculty across disciplines. Each includes complete student instructions, explicit AI guidance, and honest faculty reflection on design choices and outcomes.
What Makes Thoughtful AI Integration?
These assignments vary in structure and approach, but they share key characteristics that distinguish pedagogically sound AI integration from permissive chaos or blanket bans.
📋 Explicit Guidance
Students are told where AI use is permitted, prohibited, or required, and for which parts of the work. Rather than a general instruction to use AI responsibly, the boundaries are tied to what each task is meant to teach.
🔄 Intentional Sequencing
AI permissions change across different phases of the assignment based on the cognitive work students need to do. Students build foundational skills first, and AI enters at the point where it can extend work they are already able to do themselves.
🎯 Learning-Centered Design
AI permissions are driven by what students need to learn, not by what’s easiest to assess or police. The design ensures students do the intellectual work that matters for their development.