Key Terms

AICE (AI-Integrated Computing Education) – A districtwide framework that builds three universal habits – computational thinking, data fluency, and responsible AI use – into every subject for every learner, while offering elective pathways in Computer Science, Data Science, and advanced AI.

AICE Hub – Red Wing Public Schools’ central support team charged with turning the Flight Paths 2030 plan into action by coordinating tools, training, pilots, and feedback.

AI literacy – Knowing what AI can (and can’t) do, how it works at a surface level, and how to use it responsibly, safely, and ethically.

Computational literacy – Feeling comfortable using computing tools – spreadsheets, block code, Python, dashboards – to explore ideas or create artefacts in any subject.

Computational thinking – Breaking a big problem into smaller parts, spotting patterns, building step-by-step solutions, and checking for efficiency.

Computer science – The study of algorithms, programming, hardware, and theory of computation.

Data fluency / data literacy – Reading, questioning, and communicating with data to make sound, ethical decisions.

Data science – Collecting, cleaning, analyzing, and visualizing data to uncover insights.

Generative AI – Models (ChatGPT, DALL·E, Gemini, etc.) that create new text, images, code, or audio from prompts.

Human‑in‑the‑loop: A responsible employee supervises AI use, remains the decision-maker and verifies outputs.

Traditional AI – Rules-based or classic machine-learning systems that classify, predict, or optimize (e.g., spam filters, recommendation engines).