Unit Title: Educating with Integrity – Translating AI Knowledge into Impact
Level: Advanced Communication and Public Engagement
Duration: 120–180 minutes (best delivered over 2–3 sessions)
🎯 Learning Objectives
By the end of this week, you should be able to:
- Translate complex AI processes into understandable, accessible lessons.
- Apply principles of instructional design, scaffolding, and user empathy.
- Build simple tutorials, demo walkthroughs, or live coaching scripts.
- Choose the right formats and platforms for teaching (in-person, video, documents).
- Reflect on your role as a responsible AI educator.
🧭 Lesson Flow
| Segment | Duration | Format |
|---|---|---|
| 1. Why and How to Teach AI | 25 min | Motivations and Responsibilities |
| 2. Structuring Knowledge for Others | 35 min | Learning Models and Lesson Design |
| 3. Demo-Based Instruction | 30 min | Building and Narrating Tutorials |
| 4. Tools and Platforms for Teaching | 20 min | Delivery Options |
| 5. Exercises + Knowledge Check | 60–90 min | Drafting Your Teaching Materials |
🧑🏫 1. Why and How to Teach AI
📖 Teaching Script:
Teaching AI isn’t about showing off—it’s about empowering others safely.
You become a filter between complex tools and real-world value. Whether you run a class, write a blog, or mentor one person, your impact multiplies.
📘 Motivations for Teaching:
| Reason | Description |
|---|---|
| Democratising AI | Help non-tech users benefit ethically and confidently |
| Consolidating your knowledge | Teaching deepens your own understanding |
| Professional identity | Teaching elevates you as a thought leader or coach |
| Ethical urgency | You can prevent misuse or misunderstanding by guiding others early |
🧠 Three Example Roles:
- Workshop Facilitator – Leads local training for charities or schools
- Internal Company Trainer – Builds “AI use playbooks” for colleagues
- Content Creator – Posts explainers, prompt libraries, or tutorials online
📐 2. Structuring Knowledge for Others
📘 Instructional Design Basics:
| Concept | Description | Example |
|---|---|---|
| Scaffolding | Start simple, build complexity in layers | Intro prompt → refined prompt → automation |
| Chunking | Break info into digestible units | 3-minute video on each tool step |
| Feedback loop | Include reflection, testing, or practice | Quiz + example rework task |
| Learning objectives | State the goal before you start | “By the end, you’ll create a chatbot prompt flow” |
✏️ Sample Teaching Structure:
- Goal: “Teach how to summarise a legal text using AI”
- Step 1: Explain document types (legal vs narrative)
- Step 2: Show prompt options for summarising
- Step 3: Run a demo, refine output
- Step 4: Invite students to create their own
- Wrap-up: Review risks, ask for feedback
🧠 Tools for Visual Scaffolding:
- Diagram: “Prompt → Output → Review → Adjust”
- Table: “Prompt Examples + Use Cases”
- Timeline: “3 levels of prompt sophistication”
🎥 3. Demo-Based Instruction
📘 Formats That Work Well:
| Format | Best Use |
|---|---|
| Live walkthroughs | Real-time interaction, dynamic adjustments |
| Screen recordings | Step-by-step guidance on tool usage |
| Printable guides | Shareable handouts with key workflows |
| Prompt cards | Quick reference cards for field users |
🛠️ Components of a Great Demo:
- Clear task goal (e.g., “Create a 3-slide summary from report”)
- Verbal explanation of each step
- Pause for reflection or checking
- Highlight risk or common error
- Show final result and link to broader context
🎙️ Example Teaching Scenarios:
- “Using AI for Email Tone Shifting” (3-tone example: formal, warm, assertive)
- “Ethical Redactions Before Prompting” (live input cleaning)
- “Designing Visuals with Text Prompts” (compare 3 versions, review prompts)
🌐 4. Tools and Platforms for Teaching
📘 Choose Based on Audience:
| Platform | Strength | Use Case |
|---|---|---|
| Notion | Structured lessons and templates | Internal learning hubs |
| Loom / OBS | Screen and voice walkthroughs | YouTube, LinkedIn learning |
| Canva / Google Slides | Slide decks, visual flowcharts | Workshops, keynotes |
| Substack / Medium | Articles, explainers | Public education, thought leadership |
| Zoom / Teams | Live sessions | Coaching, in-house training |
🛠️ Tips for Engagement:
- Use real-world tasks, not abstract theory
- Invite Q&A, troubleshooting, or challenge tasks
- End with “what’s next” or follow-up links
- Keep tone friendly but precise
🧪 5. Exercises + Knowledge Check
✅ Exercise 1: Build a Mini-Lesson
Pick one AI tool you use well.
Design a 10-minute lesson:
- Goal
- 3 steps to teach
- 1 prompt example
- 1 risk warning
- Optional visual aid (sketch it out)
✅ Exercise 2: Record or Write a Demo
Choose one micro-task (e.g., “turn bullet points into marketing copy”)
- Write a 300-word step-by-step
OR - Record a 2–3 min screen demo
Bonus: Add captions and ethical note
✅ Exercise 3: Create a Prompt Card
Make a printable or digital reference:
- Name of use case
- 1–2 example prompts
- When to use
- Warning sign (e.g., avoid bias, tone drift)
🧠 Knowledge Check (10 Questions)
- What is scaffolding in lesson design?
- Give one reason why teaching AI matters.
- List 3 formats for AI teaching.
- What makes a demo effective?
- How would you chunk an AI writing workflow?
- Give an example of a “prompt card” use case.
- Why include risks in your lesson?
- What tool would you use for creating a shareable explainer deck?
- What’s one way to make a live session more interactive?
- Create a one-sentence lesson objective about AI in your field.
📝 Wrap-Up Assignment (Optional)
Title: “My AI Teaching Toolkit”
Deliverables:
- Mini-lesson script or deck
- 1 short screen demo or walk-through
- 1 printable guide or reference card
- Reflection: How did you simplify for others? What was hardest to teach?
📦 End-of-Week Deliverables
- ✅ Mini-lesson planned
- ✅ Walkthrough or script created
- ✅ Prompt card or guide produced
- ✅ Knowledge check completed
- ✅ Reflection written (optional)