Tools, Curriculum, and Resources – A Teacher’s AI Starter Pack

A Teacher’s AI Starter Pack

Teaching artificial intelligence (AI) in K–12 classrooms doesn’t require an advanced degree, complex software, or a coding background. What it does require is a thoughtfully curated set of accessible, age-appropriate, and ethically grounded resources that help educators feel empowered—not overwhelmed.

This fifth installment in our AI education series focuses on what teachers need to start teaching AI today. Whether you’re introducing pattern recognition in elementary school or facilitating ethics discussions in high school, this starter pack highlights practical tools, curriculum options, and supports that make AI instruction approachable and meaningful.

Part 1: Free, Teacher-Friendly AI Tools

These tools are browser-based, low-lift, and classroom-ready—ideal for schools with varying levels of access and technical support.

Google Teachable Machine allows students to train simple image, sound, or pose-recognition models in minutes, with no coding required. It works well on Chromebooks and is especially effective for demonstrating how AI learns from examples.

Scratch with Machine Learning Extensions combines block-based coding with AI concepts, making it ideal for storytelling, simulations, and game design in upper elementary and middle school.

MIT App Inventor with AI Extensions enables students to build real mobile apps that incorporate AI features such as text classification or image recognition, helping older students see real-world applications.

ChatGPT, when used intentionally and with clear expectations, can support brainstorming, modeling, and critical comparison between human- and AI-generated responses. Teacher guidance is essential to ensure ethical and developmentally appropriate use.

Part 2: Ready-to-Use Curriculum and Lesson Resources

For educators seeking structure, these curricula offer scaffolded, standards-aligned pathways for AI instruction.

MIT RAISE and Mozilla’s AI + Ethics Curriculum provides multi-week modules centered on fairness, data labeling, and facial recognition, with a strong interdisciplinary and discussion-based approach.

The AI for K–12 Framework (AAAI & CSTA) outlines five “big ideas” in AI and includes sample activities across all grade bands, mapped to CSTA standards.

ISTE’s AI Explorations for Educators focuses on classroom integration and responsible AI use, offering plug-and-play lessons and optional certificates.

Rex K–12’s AI curriculum is project-based, interdisciplinary, and equity-focused, with built-in rubrics, slide decks, and teacher guides aligned to CSTA standards.

Part 3: Project-Based Assessment Tools

Because AI learning is applied and iterative, project-based assessments are often more effective than traditional tests. Strong AI projects evaluate not only technical understanding, but also creativity, ethical reasoning, real-world relevance, and communication.

Teachers can support this work with simple planning tools such as lesson templates, student project planners, and peer-feedback forms. These resources help students articulate the problem they’re solving, consider ethical implications, and reflect on their learning process. Many educators create and share these materials easily using Google Docs or Canva.

Part 4: Ongoing Supports and Professional Learning

AI instruction is most successful when teachers are supported beyond a single lesson.

For teachers just starting out, introductory slide decks, short weekly AI tips, and PLC discussion prompts can build confidence over time. School leaders can support sustainable implementation by including AI in technology plans, budgeting for teacher time, and creating opportunities for student showcases.

More advanced educators may choose to launch AI electives or clubs, mentor peers, or build capstone pathways in partnership with local industry or higher education.

Tips for Classroom AI Use

Start small—one tool, one lesson, one class period. Teach foundational concepts before introducing tools, especially around bias and data. Always include reflection or discussion, and encourage creativity through games, apps, or storytelling. Most importantly, normalize iteration and “failure”—AI learning thrives on testing, revision, and curiosity.

Final Thoughts: The Tools Are Here

We don’t need to wait for a perfect curriculum or national mandate to begin teaching AI. The tools, lessons, and supports already exist—and they’re accessible to educators across grade levels and backgrounds.

Whether you’re piloting a short activity or planning a full AI pathway, you have what you need to begin. More importantly, your students need you to begin—because how they understand, question, and create with AI will shape not just their futures, but all of ours.