The standards the course is measured against, the readings behind each unit, and the tools you will use. Every entry says where it is used and whether its link has been checked.
About the link badges. 6 of 20 entries were opened and read while this page was built. The rest are well-known sources whose links have not been click-tested, so confirm each opens and says what is described here before you rely on it. Books, papers and decks without a public link are marked.
The most widely used K-12 AI framework in the US: Perception, Representation & Reasoning, Learning, Natural Interaction, Societal Impact.
Four domains: Engaging with, Creating with, Managing, and Designing AI. This link is press coverage of the May 2025 draft; look up the OECD page for the final text.
Four dimensions (human-centred mindset, ethics of AI, AI techniques and applications, AI system design) across Understand / Apply / Create.
Community-built list of what every K-12 student should learn about AI. Not yet mapped on the crosswalk.
The engineering-design standards behind the Projects and the capstone Problem. Page shown is HS-ETS1-4; the others are linked from it.
Common engineering learning goals, preschool through high school. Not yet mapped on the crosswalk.
Free classroom modules, e.g. How Do Machines Learn?, ChatGPT in Schools, Careers in AI. Used for topical comparison, not as a standards list.
Seven student standards from Empowered Learner to Global Collaborator.
The source curriculum for most Activities, Projects and the Problem. The PLTW lesson-by-lesson crosswalk is on the Crosswalk page.
Frames which job tasks AI absorbs and which skills keep value. Anchor reading for the career thread in Unit 3. No public link; ask your teacher.
Real workplace cases used for sorting tasks and for Task X-Ray examples. No public link; ask your teacher.
Shannon builds English-like text by picking each next word from observed frequencies. The idea behind Next-Word Dice, 70 years before chatbots.
Michie's matchbox machine that learned to play noughts and crosses, the model for Matchbox Nim. Search the title for the Computer Journal paper.
The paper that proposed model cards, the format students use to report accuracy and failure cases honestly.
Industry list of how LLM apps get attacked, with prompt injection first. A model for the Red-Team Report.
A critical, widely cited argument about what language models do and do not understand and where their training text comes from.
Primary source on who owns AI-assisted work and how training data is treated. Check the date of each report.
The task-based way of studying automation: jobs are bundles of tasks and technology takes some of them. The idea behind Task X-Ray. Search the title for the Quarterly Journal of Economics paper.
Browser tool for training image, sound and pose classifiers without code.
Free database of tasks, skills and knowledge for each occupation. A real starting point for Talent Stack and Task X-Ray interviews.