📖 Module 1: Essential Resources
What is GenAI?
How to Use This Resource Library
This resource library is organized into three tiers — Essential, Recommended, and Optional — to help you plan your available class time and your students’ needs. Essential materials form the core of the module and directly address the learning outcomes for this module. Recommended materials add depth. Optional materials extend the module or offer additional support to students.
There are 2 sections: Instructor Preparation and Student Materials.
The materials below are the Essential resources for Module 1. Each entry includes a brief description to help you decide how and when to use it.
💻 Instructor Preparation
Review these materials before teaching Module 1. You are not expected to use all of them, consult what is most useful for building your own familiarity and confidence with the content.
The AI Pedagogy Project 🔗 [https://aipedagogy.org]
This site offers a comprehensive and brief introduction to what GenAI is, how it works, and what it can and cannot do. There is also a library of curated assignments which can be searched by theme, subject, tools, or skills.
Understanding AI: Large Language Models Explained 🔗 [https://www.understandingai.org/p/large-language-models-explained-with]
A comprehensive but accessible introduction to GenAI, how large language models work, and key terms and principles related to GenAI and teaching. Includes a self-guided tutorial. A good starting point if you are new to the topic or want a solid conceptual foundation before teaching the module.
How Large Language Models Work (Financial Times Interactive) 🔗 [https://ig.ft.com/generative-ai]
An interactive visual essay that explains how large language models work using engaging visualizations. Breaks down technical concepts in accessible language: word vectors, transformers, and how these models understand context and predict text. This resource also appears in the Student Materials section below; it works equally well as instructor background reading and as an in-class demonstration or assigned reading.
A New Direction for Students in an AI World (Brookings Institute, January 2026) 🔗[https://www.brookings.edu/wp-content/uploads/2026/01/A-New-Direction-for-Students-in-an-AI-World-FULL-REPORT.pdf]
An extensive report offering a comprehensive framework for understanding how GenAI is affecting student learning and development. Based on a year-long global study involving interviews with over 500 students, teachers, parents, and education leaders across 50 countries, plus a review of over 400 studies. The report’s central finding is that at this stage of GenAI’s development, the risks of using generative GenAI in education currently outweigh the benefits, as these risks can undermine foundational developmental capacities in learners.
Instructors are not expected to read the full report. The executive summary, key data, and visuals are most useful for grounding your own understanding and for informing class discussions about GenAI’s role in education.
aiEdu Intro to GenAI Slide Deck 🔗 [https://www.aiedu.org/intro-to-ai-download]
A slide deck and accompanying materials from aiEdu, a nonprofit focused on GenAI literacy. Useful as a ready-made presentation resource or as a model for structuring your own introduction to GenAI concepts. You can download the slide deck for your use. Student-facing materials are included in the download.
📝 Student Materials
The following materials can be assigned before class, used during class, or processed through small group or full class discussion. There are suggested readings, videos, and websites. Each entry notes suggested use.
📚Readings
How Large Language Models Work (Financial Times Interactive) 🔗 [https://ig.ft.com/generative-ai]
(See full description under Instructor Preparation above.) This interactive visual essay can be assigned as out-of-class reading or used during class time to supplement or replace a lecture explanation of how large language models work. Because it is visually driven and self-paced, it works well for students with varying levels of prior knowledge.
Artificial Intelligence (Encyclopedia Britannica) 🔗 [https://www.britannica.com/technology/artificial-intelligence]
The Encyclopedia Britannica’s current overview of artificial intelligence. Relatively brief and accessible, covering the key concepts students need for Module 1. Can be assigned as pre-class reading or completed independently during class.
📽️ Videos
What Is AI? (Scott Galloway ~4 minutes) 🔗 [https://www.youtube.com/watch?v=xmdR0Jvm2EY]
NYU Marketing Professor and serial entrepreneur Scott Galloway explains the GenAI technology behind chatbots like ChatGPT. Using clear language and supporting animations, Galloway defines and illustrates the two key technologies at the core of how GenAI works. Can be shown in class or assigned as homework.
What Is AI? (Museum of Science ~4 minutes) 🔗 [https://www.youtube.com/watch?v=NbEbs6I3eLw&t=4s]
Defines artificial intelligence in simple terms using animation. A significant portion focuses on the ethical risks of GenAI — specifically how human prejudices and incomplete data can produce dangerous systemic biases. Pairs well with Module 2 content on ethics. Can be shown in class or assigned as homework.
What Is AI (Simplilearn ~5 minutes) 🔗 [https://www.youtube.com/watch?v=ad79nYk2keg&t=7s]
Explains artificial intelligence in simple terms using animation. Covers deep learning and includes a quiz question at the end, making it a useful tool for checking comprehension. Can be shown in class or assigned as homework.
What is Artificial Intelligence? (Crash Course and PBS AI Video Series ~12 minutes) 🔗 [https://www.youtube.com/watch?v=a0_lo_GDcFw]
An educational video series from PBS providing a foundational overview of GenAI and its global implications. The first episode is a general overview; subsequent episodes address more specific topics including unsupervised learning, robotics, and video games. Additional episodes can be assigned as homework and used as the basis for in-class discussion or activities.
Vectors Explained in 60 Seconds (@SystemDR ~60 seconds) 🔗 [https://www.youtube.com/shorts/T3MxBE09Cxs]
A brief explainer on vectors and their role in how GenAI models operate. Recommended as a quick in-class resource to use before or after the Vector Activity in the Student Activities document.
AI 101: What Is A Vector? (Learn with Ben ~2 minutes)🔗 [https://www.youtube.com/watch?v=BJwovFSJHBQ&t=1s]
Explains vectors using coordinate axes. A useful companion to the Vector Student Activity, particularly for students who benefit from a more visual or mathematical explanation of the concept.
🕸️ Websites
Code.org — Student Resources 🔗 https://code.org/en-US/students
Code.org is a global leader in computer science education and organizer of the Hour of GenAI campaign. All resources are free to students and educators and supported by major institutional donors. Can be used as a supplementary in-class resource or assigned for independent exploration.
Khan Academy — How AI Works 🔗 https://www.khanacademy.org/computing/code-org/x06130d92:how-ai-works
A free, student-facing video and lesson series covering GenAI fundamentals across seven topics: What is GenAI, Machine Learning, Computer Vision, Neural Networks, Large Language Models, Generative GenAI, and GenAI Ethics. Originally designed for grades 6–12 but adaptable for college students. Useful for students who want or need additional scaffolding on foundational concepts outside of class.
