A hands-on investigation into the global journey of microplastics through ocean currents, where students simulate marine gyres and design localized reduction strategies.

An introductory lesson on evolution covering natural selection, adaptations, fossils, and genetic mutations using visual and accessible formats.

Master the art of resolving conflict with educational stakeholders through structured case study analysis frameworks.

Explore Mendelian inheritance and master Punnett squares through interactive reference guides and practice problems.

Une leçon d'introduction à la puberté pour les élèves de 4ème, se concentrant sur les transformations physiques et le passage de l'enfance à l'âge adulte.

Une leçon complète sur les transformations physiques, physiologiques et hormonales lors de la puberté, adaptée au programme de SVT en 4ème.

Students culminate their AI literacy journey by designing an AI solution for a real-world problem. They focus on responsible design, identifying potential biases, and ensuring societal benefit.

Students analyze the ethical implications of AI on privacy and identity. They explore deepfakes, facial recognition, and the balance between security and personal freedom.

Middle school students dive into the mechanics of Large Language Models (LLMs). They learn about tokenization, probability, and how AI "predicts" the next word in a sequence.

Students explore the "ingredients" of AI: datasets. They learn how biased or incomplete data can lead to unfair or inaccurate AI systems and practice creating a balanced dataset.

Students learn to critically evaluate AI outputs by identifying "hallucinations" and factual errors. They explore why AI sometimes makes mistakes and how to verify information.

Students explore Generative AI and the importance of prompt engineering. They learn how to communicate effectively with AI to create specific images and text.

Students discover how AI works as a "smart assistant" in daily life. They identify AI in common devices and reflect on how it helps people solve problems.

Students explore the foundation of AI learning: pattern recognition. They learn that computers need many examples (data) to understand rules and make predictions.