Use the AI Literacy Framework to clarify decisions

Completed

In this unit you practice using the AI Literacy Framework to clarify AI-related decisions before any tool discussion begins. Explore all four domains and 22 competencies using the field guide. Then apply what you learned using the Microsoft tool activity and reflection prompts.

Role pathways

Review the pathway that reflects your professional role.

For teachers

Focus on classroom decisions that affect learning norms, feedback, and student use. Use the framework to clarify what you want students to learn and what counts as their work.

For coaches

Focus on building shared language across your team and helping staff slow down enough to name the decision before selecting a tool. Use domain first questions to guide coaching conversations.

For administrators

Focus on school wide decisions that involve privacy, communication, and trust. Use the framework to name accountability and safeguards before any adoption moves forward.

Framework field guide-Engage and create with AI

How this works: Select a domain and discover what it means and how it appears in K-12 education.

Engage with AI

"Engaging with AI in daily life involves using AI as a tool to access new content, information, or recommendations." — AI Lit Framework

This is the foundational domain. Everything else depends on it. You can't make responsible decisions with AI if you don't first understand what it is, recognize when it's present, and develop habits for evaluating what it produces. Engagement starts before any tool is opened.

		In your school
Recognize AI's role and influence in different contexts	Spotting AI in the tools around you is the first move. Once you can see it, you can start asking better questions about what it's doing and why it was built that way.	The task description names exactly what AI is being used to produce—comment starters, not final comments. This precision matters because it keeps the boundary between AI drafting and human judgment visible from the start.
Evaluate whether AI outputs should be accepted, revised or rejected	Not all AI outputs are equal. Evaluating means actively deciding whether what the AI produced is accurate, appropriate, and complete enough to use as-is, or whether it needs revision or rejection.	A coach reviews an AI-generated summary of classroom observation notes and finds three key teaching moments were omitted. The coach revises it before the feedback meeting rather than sending it as produced.
Examine how AI recommendations can inform and limit perspectives	AI recommendation systems are designed to surface content you're likely to engage with. That can deepen familiarity in some areas while quietly narrowing what you encounter in others.	A librarian designs a lesson around students comparing what an AI book recommender suggests for them versus books chosen by a trusted person who knows them well.
Explain how AI could be used to amplify societal bias	AI learns patterns from human-created data, and that data carries the gaps and biases of the society that produced it. Understanding this helps educators and students ask whose experiences are represented.	A history teacher uses an AI image generator during a lesson and students notice historical figures from non-Western cultures are depicted less accurately than Western ones, sparking a discussion about training data.
Describe how AI systems consume energy and natural resources	Training and running AI models requires significant computing power, which consumes electricity and water for cooling. A complete understanding of AI includes understanding its physical footprint.	A school sustainability club researches the energy consumption of the district's AI-powered learning platform and presents a cost and environmental comparison to the school board.
Analyze how well the use of an AI system aligns with ethical principles and human values	Every decision to use AI involves ethical trade-offs about fairness, transparency, and accountability. Analyzing those trade-offs is a core professional skill for educators, not just a philosophical exercise.	An administrator evaluates two AI attendance-tracking tools and selects the one with clearer privacy disclosures and a transparent data retention policy after analyzing both against the school's equity values.

Create with AI

"Creating with AI consists of collaborating with AI in a creative or problem-solving process." — AI Literacy Framework

Creating with AI isn't the same as generating with AI. This domain centers on authorship, learning purpose, and integrity. When AI is involved in producing work, the question isn't just "did it work?" but "whose thinking does this represent, and what did the creator actually learn?"

		In your school
Use AI to explore new perspectives and build on original ideas	AI can act as a thought partner—generating alternatives and surfacing angles you hadn't considered. The key is that creative ownership stays human. The AI generates possibilities; the person makes decisions.	A teacher uses Copilot to brainstorm 20 different project prompts for a unit, then refines three of them into something distinctly her own, grounded in what she knows about her students.
Visualize and prototype ideas using AI tools	AI tools can help turn rough ideas into visible, testable forms—from generated images to drafted plans—making the gap between idea and artifact smaller and iteration faster.	A student uses an AI image tool to generate three visual concepts for a school mural proposal before deciding with the art teacher which direction to develop into a real design.
Collaborate with AI through iteration and reflection	Productive use of generative AI is iterative. You prompt, evaluate, revise, and repeat. The quality of the output depends heavily on the quality of the thinking the person brings to the process.	A teacher uses multiple exchanges with Copilot to refine a differentiated lesson plan, and keeps a short reflection log noting what she changed at each step and why—turning the process itself into professional learning.
Analyze how AI affects content authenticity and intellectual property	AI can generate content that looks original but is derived from others' work. Understanding this helps educators teach students about attribution, authenticity, and the real value of original thinking.	A writing teacher designs a unit around the question "What makes this your work?" after students submit AI-generated essays without attribution, using the situation as a teaching moment rather than just a disciplinary one.
Talk about AI without treating it like a person	When we say AI "thinks," "decides," or "knows," we give it human characteristics it doesn't have. Precise language—AI "generated," "predicted," "suggested"—keeps accountability where it belongs: with people.	A coach runs a short activity at a staff meeting where teachers rewrite three common AI phrases—"the AI decided," "the AI understood," "the AI knows"—into accurate, tool-focused language.