Design Brief 3: AI Literacy & Fluency
With AI, educators are facing a tension I like to call the convergence of messy and the magical. While AI promises exciting innovation and efficiency, it also raises significant concerns.
🎙️ Podcast Focus
In Season 1, Episode 3 of the AI for Educators Design Lab podcast, we move from the question of what students should learn to a more immediate challenge: do students actually understand the AI tools they’re already using?
Adoption is high and growing across every education context, from K–12 through higher education and professional learning. But AI use and critical judgment about AI use are not the same.
In the episode, AI literacy is framed not as a one-time tutorial or an add-on module, but as a core learning outcome embedded in the learning experience. Students who use AI without understanding how it generates outputs, where it breaks down, or what ethical stakes are involved aren’t developing critical judgment. They’re outsourcing their thinking.
🤔 Learning Experience Design Challenge
The challenge for educators isn’t whether to address AI literacy. It’s how. A standalone AI awareness session might introduce the concept, but it rarely produces lasting critical thinking and application. Like any skill, AI literacy develops best when it’s embedded in the authentic moments where learners are already evaluating, deciding, and making judgments.
This episode explores what it looks like to design AI literacy as a thread running through your learning experience, rather than a separate destination. The AI Literacy Integration Map below is designed to help you identify where that thread could run in your course or learning experience.
📋 Your Design Decisions
This episode posed five design considerations in the form of questions to help you examine how AI literacy is showing up (or not) in your learning experience. These aren’t checklists or rules. They’re design considerations, and your answers will depend on your learners, your discipline, and your context.
🤔 Design Considerations
- What does AI literacy and AI fluency mean for your specific learners, in your discipline, at their stage of development?
- Are you creating opportunities for students to examine AI not just as a tool to evaluate but as a system built by people with human assumptions embedded in it?
- Where in your existing course do students already evaluate sources, weigh evidence, or question assumptions?
- Are your assignments and assessments building evaluative judgment alongside proficiency or primarily rewarding the polish of the result?
- What structures do you have in place that make AI use visible and reflective? And what are you modeling in your own practice about what a thoughtful relationship with these tools looks like?
📋 AI Literacy Integration Map
In this episode, we moved from asking whether AI literacy matters to asking how to design for it intentionally. AI literacy doesn’t develop in a vacuum or in a single lesson. It develops through repeated, contextualized practice in the moments where critical thinking already lives in your course.
The AI Literacy Integration Map worksheet is designed to help you identify two or three natural touchpoints in an existing learning experience where AI literacy could be embedded, and to describe what students would need to practice at each of those moments.
- 👉 Access the AI Literacy Integration Map Worksheet
- 🖥️ Save a copy of this document to complete on your own.
- If working in Google Docs: Go to File → Make a copy
- If working in another program: Go to File → Download and choose your preferred format (e.g., Word or PDF)
- 🧑💻 Select a learning experience where you’d like to build in AI literacy and work through each of the design considerations.
- ⏰ Plan for about 15–20 minutes to complete the map.
🎙️ Looking Ahead
In Episode 4 of the AI for Educators Design Lab Podcast, we take up a question many educators are asking. As AI takes on more of the logistical and informational work in a course, what happens to human connection? We’ll explore what it means to preserve the relational dimensions of teaching in a learning environment that’s increasingly shaped by AI.
🤖 Optional: S1E3 AI-Generated Podcast Edition
One way to develop your own critical eye for AI-generated content is to compare it with a human-curated analysis of the same topic. The podcast in THIS section is 100% AI-generated and covers the same subject matter as Episode 3 of the Educators Design Lab Podcast on AI literacy and fluency.
This AI-generated version was created by prompting five AI assistants with a literature review task and then using NotebookLM to synthesize their findings into this audio overview. The voices, images, and words were generated without human fact-checking or editing.
🫣 Behind the Scenes
1. Literature Review
Rather than relying on a single AI assistant, five were prompted, including ChatGPT, Claude, Copilot, Gemini, and Perplexity. They were each given the same task: to dig into the literature focusing on how educators could integrate AI literacy as a core learning outcome embedded throughout the learning experience. Each AI brought different strengths: some excelled at finding current statistics, others at synthesizing academic sources, and some at providing practitioner perspectives.
2. Synthesis
NotebookLM was then prompted to:
- Analyze all five reports
- Create a range of written summaries and the audio in the “podcast” you heard using AI voices
3. Video & Image Production
The image of the two “podcasters” was created in Gemini. Then, the transcript, slides with captions, and video were generated in Descript, an AI-based media editing app, using audio from NotebookLM.
🤔 Reflect
As you listen, think about what catches your attention and consider:
- What feels similar to or different from what was highlighted in the human-created version of this episode?
- What would it take to verify the claims and sources in this AI-produced version of the podcast?
- Could a tool like this be useful in your own learning or professional practice, and if so, where would you still need human judgment?
Thank you for being here. I look forward to engaging with you in this conversation!
Jennifer Maddrell, PhD
Next Path Design