Developed as part of the Extending the CS Pipeline: Enhancing Rigor and Relevance in Middle School CS Project.

Artificial Intelligence is increasingly embedded in the tools students use every day, from recommendation systems and search engines to image generators and design platforms. In this five-day unit, students explore how AI systems work, how they learn from data, and how those systems can both reflect and amplify patterns present in the data they are trained on.

Through interactive experiences such as Google’s Quick, Draw! and Code.org’s AI for Oceans, students investigate how machine learning models identify patterns and make predictions based on training data. As the unit progresses, students analyze how the quality, quantity, and diversity of data affect system performance and accuracy. They examine real-world examples of algorithmic bias and consider the ethical responsibilities of designers, developers, and users.

The unit culminates in a hands-on generative AI design project in which students use AI tools to redesign a book cover. In doing so, they explore how prompts shape outputs, reflect on questions of authorship and ownership, and evaluate the appropriate use of generative technologies. By the end of the unit, students develop both foundational AI literacy and the critical thinking skills needed to distinguish between what AI systems can do and what they should do. 

To support educators (especially those new to AI), the package includes a Key Concepts for Educators document that defines essential terminology such as machine learning, training data, models, large language models (LLMs), algorithmic bias, generative AI, and chatbots. It also provides practical guidance for accessing commonly used AI tools in classroom settings while emphasizing privacy and district policy considerations.

This lesson package includes:

1. A Lesson Plan Overview

2. A Document with Key Concepts for Educators

3. A Slide Deck on Generative AI