AI literacy

This article by Tara Nattrass urges educators to shift the focus from merely adopting AI tools to envisioning how AI can catalyze transformational learning experiences. It emphasizes the importance of prioritizing durable skills like critical thinking and creativity, integrating AI into competency-based learning, and teaching both with and about AI. The piece advocates for using AI as a means to reimagine education, rather than just enhancing efficiency.

This research paper analyzes outputs from popular AI lesson-planning tools and reveals that AI-generated content often reinforces passive, teacher-centered instructional models. The findings highlight the need for educators to critically evaluate AI outputs rather than rely on them blindly. This is exactly why teacher discernment and pedagogical awareness are essential when integrating AI into the classroom.

The AI Literacy Framework (AILit) defines the technical knowledge, durable skills, and future-ready attitudes required to thrive in a world influenced by AI. The framework aims to empower learners to engage with, create, manage, and design AI, while critically evaluating its benefits, risks, and ethical implications. The initiative includes practical resources such as infographics, customizable slide decks, and a guidance toolkit to support educators in integrating AI literacy into primary and secondary education. Also available at https://ailiteracyframework.org/

This guide offers practical strategies for integrating generative AI into literacy instruction while preserving student cognitive engagement. It helps educators identify when GenAI can support learning, where productive struggle matters, and how to avoid replacing critical thinking. Use cases span foundational skills, knowledge building, and writing.

Part of MIT's "An Exploration of Generative AI" series, this article outlines how K–12 education can respond to the rise of AI with a balance of caution and curiosity. It encourages schools to support teacher and student experimentation beyond classroom boundaries, remain skeptical of AI-powered edtech products, and adopt an iterative approach to implementation. The piece emphasizes the need for clear, coherent policies that evolve alongside the technology.

This article explores how comparing multiple AI-generated responses—also called comparative transcript analysis—can help students critically evaluate AI output. It encourages deeper engagement with AI as a tool rather than a truth source. Ideal for teaching fact-checking, bias detection, and source comparison in middle and high school classrooms.

This article reframes how we approach AI in education by flipping Bloom’s Taxonomy—focusing on critical thinking over tool mastery. It argues that teaching students how to think with AI is more important than teaching them how to use specific tools. A powerful read for educators designing inquiry-based or future-ready curriculum.

This article from The Washington Post reports on a Sun-Times education supplement that unknowingly published AI-generated content containing factual errors. It highlights the growing risk of AI hallucinations in public-facing materials and the need for stronger editorial review. A cautionary example of how AI misuse can slip into mainstream media and education outreach.

In this practical article, educator and researcher Ethan Mollick outlines common, effective ways to use AI in educational and professional settings—along with key situations where it's best avoided. The list emphasizes efficiency, exploration, and feedback while cautioning against offloading core thinking or ethical decision-making. It’s a useful framework for setting classroom and staff norms around AI use.

This 18-minute video offers a clear, engaging overview of generative AI—what it is, how it works, and how it’s changing the way we live and learn. It’s ideal for beginners looking to quickly grasp foundational concepts and real-world implications. Great as a staff kickoff or introduction to AI in PD sessions.

This concise article by Tobias Zwingmann demystifies essential AI terminology using clear language and relatable analogies. It covers core concepts like machine learning, neural networks, and generative AI in a way that’s approachable for non-technical readers. A strong entry point for educators, students, or families new to AI.

This article simplifies AI concepts using kid-friendly metaphors and analogies, making it accessible for both students and adults. It breaks down how AI learns, makes decisions, and differs from human intelligence in a playful, conversational tone. A great resource for introducing AI in upper elementary or middle school classrooms. Or anyone else!