Capstone Project 3: AI Literacy Workshop Design

Overview

Here is the test of whether you truly understand something: can you teach it to someone else?

This capstone takes everything you have learned about AI — the technology, the social implications, the ethical questions, the practical skills — and asks you to make it accessible to people who have not taken this course. You will design a 90-minute AI literacy workshop for a specific audience, create all the materials needed to run it, and reflect on the choices you made.

This project matters because AI literacy is not just an academic exercise. It is a civic need. The senior citizen deciding whether to trust a medical AI recommendation, the middle school teacher figuring out how to handle ChatGPT in the classroom, the small business owner wondering if an AI hiring tool is worth the risk, the journalist trying to evaluate an AI company's claims — these people need exactly the kind of knowledge you have built over this course. But they will never take a college course on AI literacy. They need someone to meet them where they are.

That someone is you.

If your institution supports it, you may have the opportunity to actually deliver your workshop to a real audience. Whether you deliver it or not, the design process itself is a powerful exercise in synthesis, communication, and empathy.

Learning Objectives

By completing this project, your team will demonstrate the ability to:

1. Translate complex AI concepts into language and activities appropriate for a specific non-expert audience (Chapters 1–8, 14)
2. Design learning experiences with clear objectives, engaging activities, and appropriate pacing
3. Select the most important AI literacy concepts for a given audience — what to include, what to leave out, and why (all chapters)
4. Create materials that are accurate, accessible, and free of unnecessary jargon
5. Anticipate audience questions, misconceptions, and anxieties about AI (Chapters 1, 8, 10, 20)
6. Reflect critically on pedagogical choices and their effectiveness

Audience Selection

Choose one of the following audiences. Each presents distinct challenges and opportunities. Your workshop design must demonstrate that you understand who your audience is, what they already know, what they need to know, and what will engage them.

Audience A: Senior Citizens (ages 65+)

Context: Community center, public library, or senior living facility. What they likely know: Many use smartphones and email; some use voice assistants; most have heard about AI in the news. Comfort with technology varies widely. What they need: Practical understanding of AI they encounter daily (voice assistants, recommendation algorithms, scam detection, healthcare AI); confidence to ask good questions; ability to spot AI-generated misinformation. Privacy and surveillance concerns are often paramount. Key challenges: Variable tech literacy; potential technophobia; accessibility needs (large fonts, slower pacing, hearing considerations). Avoid condescension — these are adults with decades of life experience and sharp critical thinking skills. Relevant chapters: 1 (what is AI), 7 (decision-making/recommendations), 8 (errors), 12 (privacy), 14 (using AI effectively), 15 (healthcare AI)

Audience B: Middle School Students (ages 11–14)

Context: School assembly, after-school program, or classroom visit. What they likely know: Many are digital natives who use AI daily without thinking about it (TikTok algorithm, autocomplete, game AI). Some have used ChatGPT. What they need: Understanding that AI is not magic; critical evaluation of AI-generated content; awareness of data privacy; tools for thinking about fairness and bias in age-appropriate terms. Key challenges: Short attention spans; need for interactive, hands-on activities; wide range of maturity levels. Must be engaging without being simplistic. Relevant chapters: 1 (what is AI), 3 (how machines learn), 5 (LLMs — they use these), 8 (errors/hallucinations), 9 (bias — age-appropriate framing), 14 (using AI effectively)

Audience C: Journalists and Media Professionals

Context: Newsroom training session, journalism conference workshop, or professional development seminar. What they likely know: Broad awareness of AI issues; some experience covering AI stories; varying technical depth. What they need: Technical literacy sufficient to evaluate AI company claims; understanding of common AI hype patterns; frameworks for covering AI responsibly; ability to identify bias and fairness issues in AI systems they report on. Key challenges: Skeptical, time-pressed audience; want immediately applicable skills; may resist "being taught" by non-journalists. Respect their existing expertise while filling genuine knowledge gaps. Relevant chapters: 1 (what is AI), 2 (hype cycles — essential for journalists), 5 (LLMs), 8 (errors and failures), 9 (bias), 11 (creativity/deepfakes), 13 (governance)

Audience D: Small Business Owners

Context: Chamber of commerce event, small business development center, or industry association meeting. What they likely know: Some are using AI tools already (marketing, customer service, bookkeeping); others have heard they "should be" using AI but do not know where to start. What they need: Practical assessment framework — when is AI worth the investment? What are the risks? How to evaluate AI vendor claims. Understanding of data privacy obligations. Basic prompt engineering for common business tasks. Key challenges: Want practical ROI-focused advice, not abstract discussion; time is money; may be frustrated by "it depends" answers. Balance practical value with critical thinking. Relevant chapters: 1 (what is AI), 5 (LLMs — tools they might use), 7 (decision-making), 8 (errors), 10 (AI and work), 12 (privacy obligations), 14 (using AI effectively)

Audience E: K–12 Teachers

Context: Professional development day, teachers' conference, or school district training. What they likely know: Directly experiencing AI's impact through student use of ChatGPT and similar tools; varying levels of personal AI use. What they need: Framework for setting classroom AI policies; ability to detect AI-generated student work (and understanding of its limitations); ideas for teaching with AI rather than just against it; understanding of student privacy implications. Key challenges: May feel overwhelmed, anxious, or even angry about AI's disruption of education; need validation before they can absorb new information. Must acknowledge the real difficulties they face. Relevant chapters: 1 (what is AI), 5 (LLMs), 8 (errors/hallucinations), 11 (creativity and authorship), 14 (using AI effectively), 16 (AI in education)

Audience F: Local Government Officials

Context: City council briefing, county commissioners' workshop, or municipal government training. What they likely know: Aware of AI as a policy issue; may have encountered specific proposals (predictive policing, automated permit review, chatbot services). Policy-literate but not tech-literate. What they need: Enough technical understanding to ask good questions of vendors; framework for evaluating AI procurement proposals; awareness of civil rights and equity implications; understanding of governance best practices from other jurisdictions. Key challenges: Political considerations are always present; need nonpartisan framing; want to appear competent without admitting knowledge gaps. The CityScope Predict and ContentGuard examples are directly relevant to their world. Relevant chapters: 1 (what is AI), 7 (decision-making), 9 (bias), 12 (surveillance), 13 (governance), 17 (justice and accountability), 19 (how other jurisdictions are handling this)

Workshop Design Template

Your final deliverable is a complete workshop package. Use the following template, adapting it to your chosen audience.

Part 1: Workshop Overview Document (2–3 pages)

1.1 Workshop Title Choose something engaging and appropriate for your audience. Not "AI Literacy Workshop" — that is a course catalog entry, not a title that makes someone want to show up on a Saturday morning.

1.2 Audience Profile Describe your specific audience in detail: - Demographics and context - Prior knowledge assumptions (be specific: what do they know, what do they think they know, what do they not know?) - Motivations for attending (why would they show up?) - Potential anxieties or resistance (what might make them tune out?)

1.3 Learning Objectives (3–5 objectives) By the end of this workshop, participants will be able to: - [Objective 1] — use action verbs (identify, evaluate, explain, distinguish, apply) - [Objective 2] - [Objective 3]

💡 Remember the difficulty ratchet from this course. Your 90-minute workshop cannot take people from zero to "Evaluate." Aim for Understand and Apply. If your audience already has some foundation, you can push toward Analyze.

1.4 Materials and Equipment Needed List everything required to run the workshop: - Technology (projector, speakers, WiFi, devices) - Physical materials (printed handouts, markers, sticky notes, props) - Backup plans if technology fails

Part 2: Detailed Session Plan (3–4 pages)

Design a minute-by-minute session plan. Every activity must include timing, instructions, and purpose.

Suggested structure (adapt as needed):

For each segment, provide:

• Facilitator script or talking points — not a word-for-word script (that leads to stilted delivery), but key points, transitions, and specific examples to use.
• Activity instructions — detailed enough that another facilitator could run the activity from your description alone.
• Anticipated questions and responses — what will the audience ask? Prepare at least five likely questions with suggested responses.

Part 3: Interactive Activities (design at least 3)

Each activity should be described in full detail:

Activity Name: Duration: X minutes Format: Individual / pairs / small group / full group Materials needed: Setup instructions: Step-by-step facilitation guide: Debrief questions: Adaptation notes: How to adjust if the activity runs long/short, or if participants struggle.

Here are some activity types to consider (you are not limited to these):

• "AI or Not?" game: Present examples and have participants guess whether AI was involved. (Builds on the Chapter 1 framework.)
• Prompt engineering exercise: Give participants a task and have them write prompts, compare results, and discuss what worked. (Builds on Chapter 14.)
• Bias detection exercise: Show participants outputs from an AI system across different demographic inputs and have them identify disparities. (Builds on Chapter 9.)
• AI decision-mapping: Walk through a specific AI decision (e.g., a content moderation call, a loan approval, a medical recommendation) and have participants trace the inputs, the process, and the stakeholders. (Builds on Chapter 7.)
• "What would you do?" scenarios: Present ethical dilemmas involving AI and have small groups discuss and present their reasoning. (Builds on Chapters 9, 11, 17, 20.)
• Live demo: Show an AI tool in action, demonstrating both its capabilities and its limitations. (Demonstrate hallucinations, bias, or the gap between confidence and accuracy from Chapter 8.)

Part 4: Handout Materials (2–4 pages of participant-facing materials)

Create materials that participants take home. These should:

• Reinforce key concepts from the workshop
• Provide practical tools they can use immediately (checklists, questions to ask, resources to explore)
• Be visually clean and inviting — not walls of text
• Include sources for further learning

Suggested handout content:

• One-page "AI Literacy Quick Guide" summarizing the key concepts covered
• A "Questions to Ask About Any AI System" checklist (adapted from the framework introduced in Chapter 1)
• A "Recommended Resources" list — specific articles, videos, podcasts, and books for further learning
• Any activity worksheets used during the session

Part 5: Facilitation Guide (1–2 pages)

Write advice for someone else who might run your workshop. Address:

• Tone and approach: How should the facilitator present themselves? (Think about the voice of this textbook — curious, honest, not condescending.)
• Common pitfalls: What should the facilitator avoid? (Jargon, fearmongering, cheerleading, lecturing for too long without interaction.)
• Handling difficult moments: What if a participant is hostile to AI? What if someone is anxious? What if a participant knows more than the facilitator? What if the live demo fails?
• Accessibility: How to adapt for participants with visual, hearing, or mobility needs; for participants with limited English proficiency; for mixed-literacy groups.

Reflection Component

Each team member individually writes a 1,500-word reflection addressing:

If You Delivered the Workshop:

1. What worked: Which activities engaged participants most? What concepts resonated? What moments surprised you?
2. What didn't work: Where did participants lose interest, get confused, or push back? What assumptions about your audience were wrong?
3. What you would change: If you ran this workshop again, what would you redesign? Be specific — do not just say "I would make it better."
4. What you learned about AI literacy: How did the experience of teaching change your own understanding? What concepts did you realize you understood less well than you thought?
5. Connection to course themes: How did this experience connect to the course's recurring themes — particularly "AI Literacy as Civic Skill" and "Durable Frameworks"?

If You Did Not Deliver the Workshop:

1. Design choices: What were the hardest choices you made in designing the workshop? What did you include, what did you leave out, and why?
2. Audience empathy: What did you learn about your chosen audience through the research process? What assumptions did you have to revise?
3. Translation challenges: Which course concepts were hardest to translate for a non-expert audience? What strategies did you develop?
4. Anticipated challenges: What do you think would go wrong if you delivered this workshop? How have you designed around those challenges?
5. Connection to course themes: How did this experience connect to the course's recurring themes — particularly "AI Literacy as Civic Skill" and "Durable Frameworks"?

Assessment

This project is assessed using the AI Literacy Workshop rubric in the Capstone Rubric document. The rubric evaluates six dimensions: Audience Understanding, Content Accuracy and Selection, Activity Design, Materials Quality, Facilitation Planning, and Reflection Depth. If the workshop is delivered, a "Delivery and Adaptation" dimension is added.

This project is worth 20% of your final grade.

Submission Guidelines

Submit the following as a single bundled PDF (or a zip file if handouts include images or designed layouts):

1. Workshop Overview Document (Part 1)
2. Detailed Session Plan (Part 2)
3. Interactive Activity Descriptions (Part 3)
4. Handout Materials (Part 4, ready to print)
5. Facilitation Guide (Part 5)
6. Individual Reflections (one per team member, 1,500 words each)
7. AI Use Disclosure (same requirements as Capstones 1 and 2)

If you delivered the workshop, also include: - Photos or video (with participant consent) if available - Any participant feedback collected (surveys, comment cards, informal notes) - Revised session plan incorporating what you learned from delivery

File naming: TeamName_WorkshopDesign_[Audience].pdf

A Final Thought

There is a version of this project where you design a workshop and never think about it again. And there is a version where the materials you create actually help someone — a grandparent who is less afraid of AI after your workshop, a teacher who finally has a framework for their classroom policy, a local official who asks better questions of the next AI vendor who walks into their office.

The second version is not just a better project. It is AI literacy doing what it is supposed to do: moving from the classroom into the world.