This session is designed to help you use AI to jump-start creative course design—simulations, exercises, world-building, formative assessments, discussion prompts, and more. The focus is on keeping you in the creative driver’s seat while using AI to expand options, generate drafts faster, and improve variety and engagement.
Time and Location:
- When: Friday, January 9th
- Time: 10:00 am – 11:15 am
- Where: Law Library 300 & Remote Option via Zoom
- Who: Faculty/TA Focused
What to expect in this session:
- Case study walkthrough: See a real example of an instructor creating a multi-party negotiation simulation with AI
- Use case menu: Explore what’s possible—simulations, case studies, discussion prompts, formative assessments
- Hands-on building: Start creating a course material for your own teaching
- Shareout: See what others built and troubleshoot together
- Leave with: A working draft (or a clear plan to finish one)
What kinds of materials can you create?
- Simulations & role-plays: Multi-party scenarios with world-building and confidential instructions
- Case studies: Discipline-specific scenarios with analysis prompts
- Discussion prompts: Thought-provoking questions, debate frameworks, activity designs
- Formative assessments: Practice problems, self-check quizzes, rubrics with sample responses
What to bring:
A laptop, tablet, or mobile device for hands-on building. If you have a specific course or learning objective in mind, bring that context—but it’s not required. We’ll help you identify something useful to build during the session.
No prior AI experience is necessary. This session is designed for all comfort levels and emphasizes learning through doing.
Workshop Resources
Workshop Summary: Creating Course Materials with AI
January 2026 | BC Law Winter Ed Tech Training
Thanks for joining the final session of our winter workshop series! Here’s a practical summary of what we covered, along with next steps for those ready to dive deeper. This summary was created by the “transcript-processing” skill created by Kyle Fidalgo and used with Claude Code. Content was reviewed for accuracy by a human.
The Big Idea
Your expertise is the essential ingredient. AI doesn’t replace your subject matter knowledge—it amplifies it. Without your disciplinary expertise, pedagogical judgment, and understanding of your students, AI-generated materials fall flat. With your guidance, AI becomes a powerful tool for creating engaging course materials at scale.
Think of it this way: you bring the vision, context, and quality control. AI brings speed and scale. Together, you can create materials that would have taken weeks in a fraction of the time.
The Five Design Basics for Working with Generative AI
- Sentient Design Material: AI is a probabilistic, highly adaptable tool that’s context-aware, multimodal, and flexible for knowledge work
- Iteration as Real Work: Working with AI requires continuous refinement – it’s simple (just typing) but not always easy (requires thoughtful prompting)
- Meta-Prompting: When stuck, ask AI how to work better with it – use it as both vehicle and guide
- Context is Everything: AI needs your goals, audience, success criteria, and relevant background information to be effective
- Natural Language Interface: If you can write clearly, you can collaborate with AI – no technical expertise required
The Four Ds of AI Fluency (Anthropic Framework)
- Delegation – Knowing what to hand off to AI vs. keep for yourself vs. co-create
- Description – Clear prompting and context engineering (good communication = good prompting)
- Discernment – Critical evaluation of outputs for accuracy, quality, relevance, and ethical considerations
- Diligence – Taking ownership and responsibility for AI-generated output, including proper attribution
What You Can Create
Workshop participants explored creating:
- Simulations and role plays — Multi-party scenarios with confidential instructions
- Case studies — Discipline-specific scenarios with analysis prompts
- Discussion activities — Engaging prompts that spark critical thinking
- Formative assessments — Practice problems, self-check quizzes, feedback rubrics
- Visual and audio materials — Images, infographics, voice-overs
Case Study: What’s Actually Possible
Professor Raul wanted to create a multi-party contract negotiation simulation for his Contracts class. Here’s what happened:
The setup: Raul had already done the thinking—a detailed planning document describing a three-party negotiation scenario involving a high-end restaurant (“The Duck”) and a duck supplier, with interpretation issues and UCC provisions baked in.
The process: We combined his planning document with a 15-minute verbal narration of his goals, fed it all to Claude, and asked it to verify understanding before proceeding.
The result: In about 15 minutes of autonomous work, Claude generated:
- Historical invoices and purchase orders
- Technical specifications for duck breeds
- Marketing materials
- Communications between parties
- Confidential instructions for each student party
- A strategic guide with red flags and bad faith indicators embedded throughout
Raul reviewed everything, made minor adjustments (it was “95% there”), and ran the simulation successfully in class.
The takeaway: This level of comprehensive material creation—which might have taken weeks—happened in under an hour of focused collaboration.
Quick Wins: Try These This Week
Starter Prompt for Simulations
“I’m creating a [subject area] simulation for my [course name] class. Here’s the scenario: [describe]. Help me develop this into a full simulation with background information and instructions for each party.”
Starter Prompt for Assessments
“I’m teaching [topic] and want to create a self-check quiz for students. Here’s what they should know: [key concepts]. Generate 10 questions that test understanding, not just memorization.”
The Verification Prompt (Use This!)
Before AI starts generating, ask:
“Restate what you think we’re working on and the deliverables I’m looking for, so we can work on them incrementally.”
This simple step dramatically improves results by ensuring you’re aligned before work begins.
Tools at Your Fingertips
BC-Supported (Use These First)
- Google Gemini (gemini.google.com) — Sign in with BC account
- For serious work, select Gemini 3 Pro from the model dropdown
- Image generation available (Tools → Create Images)
- Limit: 3-5 image generations/day on BC accounts
Worth Exploring (Personal Accounts)
- Claude (claude.ai) — $20/month, excellent for document creation and autonomous tasks
- ChatGPT — $20/month, good all-around with image generation
- 11 Labs — $5/month, voice generation and cloning
Privacy tip: For Claude/ChatGPT, use a personal account and turn off model training in settings. Instructions at bc.edu/genai under “Additional Tools.”
Intermediate Next Steps
Ready to go deeper? Here’s your progression:
Level Up Your Prompting
- Add verification steps — Always ask AI to restate understanding before generating
- Break tasks into increments — Request deliverables one at a time for easier review
- Provide examples — Show AI what “good” looks like from your perspective
- Use meta-prompts — “What additional context would help you give me better results?”
Try Multi-Document Projects
Following Raul’s example:
- Write out your scenario/exercise in a document
- Record yourself explaining the nuances (use voice memos, then transcribe)
- Feed both to AI with clear deliverable requests
- Review incrementally, not all at once
Experiment with Images
- In Gemini, click Tools → Create Images
- Describe the style you want (provide a reference image if possible)
- Specify colors, aesthetic, and purpose
- Iterate: “Now create a [related icon] in the same style”
Advanced: Build Your Own Tools
The workshop featured Jake’s “Classroom Lecture Tools”—a full application suite he built with Gemini 3 including group creation, attendance tracking, cold calling, and anonymous Q&A. He’s not a coder. He just described what he wanted.
This is called “vibe coding”—building functional tools through conversation with AI.
Want to try it?
- Start with a simple, well-defined need
- Use Gemini 3 Pro or Claude
- Describe what you want the tool to do
- Let AI generate the code
- Test and iterate
Platforms purpose-built for this:
- Replit, Lovable, Bolt — Web-based, conversation-driven app building
Stay tuned for Jake’s tools being published for broader use.
On Attribution and Transparency
A question that came up: How do you handle attribution when AI generates most of the content?
The short answer: Transparency, not complex citation.
A simple statement works: “I used AI to generate these materials based on my course design. I’ve verified them for accuracy and pedagogical soundness.”
On the “do as I say, not as I do” tension: Learning foundational skills makes you a better AI collaborator. Students need to build expertise that enables effective AI partnership—that’s why we teach traditional methods even while using AI ourselves.
Resources
For AI Literacy
- Kyle’s AI Foundations Site — Self-paced course covering fundamentals
- Anthropic’s Fluency Course — Deeper dive including teaching applications
- Andrej Karpathy’s YouTube Deep Dive — 3-hour technical explainer (for the curious)
For Ongoing Support
- One-on-one consultations — Email or drop by Kyle’s office
- bc.edu/genai — BC’s guidance and privacy recommendations
- Each other — Share what’s working in your courses
Your Challenge
Pick one thing from this workshop and try it before the semester gets too busy:
- [ ] Create a draft simulation or case study for an upcoming class
- [ ] Generate a set of discussion prompts or quiz questions
- [ ] Use the verification prompt technique in your next AI session
- [ ] Experiment with image generation for slides or materials
The best way to build these skills is through practice. Start small, iterate, and reach out if you get stuck.
Questions? Ideas? Hit a wall? Contact Kyle Fidalgo — email, phone, or drop by. Happy to help you work through specific projects.