Computer Science

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.

Introduces the concept of AI by distinguishing between a robot's physical body and its digital 'brain'. Students explore how AI 'thinks' differently than humans and machines.

A beginner-friendly introduction to the physical parts of a Chromebook and basic digital literacy for kindergarten students.

Students practice sitting correctly in a chair, facing the screen, and keeping their feet on the floor. The lesson utilizes a 'check your neighbor' activity to reinforce healthy ergonomic habits from a young age.

Students learn how to properly wear headphones and identify the volume control buttons. The lesson emphasizes keeping volume at a safe level and the correct way to plug in or store headphones when finished.

Students explore the cause-and-effect relationship between moving a physical mouse (or finger on a touchpad) and the movement of the cursor on the screen. Activities involve watching the screen while moving the hand to build hand-eye coordination.

Learning the function of the Enter key as the 'Go' or 'Done' button.

Locating and identifying numbers 1-9 on the top row of the keyboard.

Identifying the space bar and understanding its role in creating distance between words.

Identifying and locating the first letter of a student's name on the keyboard.

Introduction to the keyboard layout, comparing it to the alphabet order and matching blocks to keys.

Introduces the concept of 'Home' and 'Back' icons to help students navigate through apps and regain control.

Develops the skill of clicking and holding to move digital objects, practiced through virtual puzzles and organization games.

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.

Introduces the concept of AI by distinguishing between a robot's physical body and its digital 'brain'. Students explore how AI 'thinks' differently than humans and machines.

A hands-on STEAM lesson where emerging bilingual students use Ozobots to act out short scenarios, focusing on beginner-level English speaking, listening, reading, and writing skills.

A series of creative coding challenges designed for young learners using Scratch Jr. Students will explore basic programming concepts through open-ended, imaginative projects.

A dedicated hub for educators featuring a K-12 curriculum scope, professional development guides, and quick-reference AI cheat sheets.

High school students analyze the impact of generative AI on careers and society, mastering advanced prompt engineering and debating complex ethical dilemmas.

Middle schoolers dive into the mechanics of neural networks and the ethical implications of AI in daily life, focusing on digital citizenship and algorithmic fairness.

Middle elementary students investigate how training data shapes AI behavior, identifying bias in simple systems and experimenting with basic prompt engineering.

Students in grades 1-2 explore how machines learn to recognize patterns and assist humans, introducing basic classification and the idea of helpful technology.

Introduces Kindergarteners to the concept of AI as a 'thinking' tool that follows instructions and learns from examples, focusing on the difference between robots and AI.

A whimsical introduction to computer science loops through the magic of storytelling and nursery rhymes. Kindergarten and 1st-grade students learn to spot repeating patterns in their favorite songs and 'code' them using loop symbols, bridging the gap between literacy and computational thinking.

A foundational introduction to computer science for K-1 students, teaching algorithms and loops through visual and movement-based patterns. Students learn to see patterns as repeating sets of instructions, building the mental model for coding loops.

A hands-on introduction to algorithmic thinking for K-2 students, using the metaphor of recipes to explain how computers follow specific sequences of instructions.

Students assemble puzzles piece by piece to understand that large files are downloaded in small chunks called packets.

Students explore what happens when information is missing or a request cannot be fulfilled, introducing the concept of broken links and 404 errors.

Through physical simulation, students learn that 'loading' is the time it takes for data to travel from a server to their device.

Students act as clients searching for specific items while a 'Server' finds them, illustrating how search engines and information retrieval work.

Students play a 'Restaurant' game where 'Clients' order food (data) and 'Servers' fetch it from the kitchen (database) to learn about requesting information.

Students build 3D network models using playdough and straws to experiment with different network shapes.

Students use a world map to visualize how the internet connects people across oceans and continents.

Students map physical wires and cables in their local environment to understand the infrastructure of the internet.

Students identify 'nodes' and 'links' in their yarn web and explore what happens when a connection is lost.

Students use a ball of yarn to create a physical web, demonstrating how people and devices are interconnected.

Students move from a linear chain to a grid-based network. They explore how messages can take multiple 'hops' through different students to reach a destination.

Introduces the concept of a 'data packet' through a linear passing game. Students focus on speed and accuracy as they pass information along a chain.

Students learn about network protocols through a turn-taking game, understanding why order is necessary for clear communication.

Students learn that for a message to reach its destination, it needs a specific address. They practice drawing 'data' and assigning symbols to represent unique recipients.

The class builds a physical model of a network using yarn and paper devices to visualize how multiple units connect to a central point.

Students investigate invisible signals like Wi-Fi and Bluetooth using remote controls and blocking experiments.

Students explore physical connections using string telephones to understand how information travels through a direct path (wires).

Students identify computing devices in their environment and sort them based on their ability to process information and connect to networks.