The “AI Literacy Lessons for Grades 6–12” collection from Common Sense Education is a set of classroom-ready resources designed to help middle- and high-school students understand artificial intelligence and develop the critical-thinking skills needed to use and evaluate AI responsibly. The collection connects AI literacy with digital citizenship, media literacy, ethics, privacy, bias and responsible technology use. Common Sense also provides broader AI literacy materials for educators and families, with an emphasis on age-appropriate and responsible engagement with AI.
Why it matters for ENACT-AI
The collection is directly relevant to AI Literacy & Critical Thinking and is particularly useful for helping young people understand how AI affects information, decision-making and everyday digital experiences. It also connects AI literacy with media literacy, misinformation, privacy, bias and responsible digital behaviour. Common Sense's broader Grades 6–12 materials explicitly encourage students to question online information, examine bias and consider whether content should be shared, which strongly complements AI literacy.
Learning outcomes
Learners will be able to:
Explain basic concepts related to artificial intelligence and generative AI.
Understand how AI systems can influence the information and digital environments they use.
Identify potential benefits and limitations of AI.
Recognise bias and inaccuracies in AI-generated content.
Critically evaluate information produced or recommended by AI systems.
Understand privacy and data-related risks associated with AI.
Reflect on the ethical and social implications of AI.
Make more responsible decisions when using AI tools.
Apply critical-thinking and media-literacy strategies when interacting with AI-generated content.
Suggested activity
Ask students to use an AI chatbot to answer a question relevant to their subject or everyday life. Students then investigate the response and compare it with reliable external sources. In groups, they identify accurate information, errors, unsupported claims, bias and missing context. Each group presents its findings and develops a short set of “rules for checking AI answers” that could be used by other students.