AI jargon can be overwhelming. Here’s every term you’ll encounter as a teacher using AI tools, explained without the tech-speak.

A

AI (Artificial Intelligence) — Software that can perform tasks that normally require human thinking: writing, analyzing, creating, and answering questions. ChatGPT, Claude, and Gemini are all AI tools.

Algorithm — A set of rules a computer follows to solve a problem. When people say “the algorithm,” they usually mean the system deciding what content to show you.

API (Application Programming Interface) — A way for software to talk to other software. When MagicSchool generates a quiz, it’s using an API to communicate with an AI model behind the scenes. You don’t need to understand this to use AI tools.

C

Chatbot — An AI you interact with by typing messages. ChatGPT is a chatbot. So is Claude. The “chat” format is just the interface — the AI behind it can do much more than chat.

Context Window — How much text an AI can “remember” in a single conversation. A larger context window means you can paste longer documents. Claude has one of the largest context windows.

Copilot — Microsoft’s AI assistant built into Word, Excel, PowerPoint, and Teams. If your school uses Microsoft 365, you may have access to Copilot.

D

Data Privacy — How your information is stored and used. When you paste student information into an AI tool, that data may be stored or used to train the model. Always check a tool’s privacy policy. See also: FERPA.

Differentiation (AI-assisted) — Using AI to create multiple versions of the same content at different reading levels or complexity. One of the most practical uses of AI for teachers.

F

FERPA (Family Educational Rights and Privacy Act) — US federal law protecting student education records. Pasting identifiable student information into consumer AI tools like ChatGPT may violate FERPA. Use anonymized data or FERPA-compliant tools like MagicSchool’s school plan.

Fine-tuning — Training an AI model on specific data to make it better at a particular task. MagicSchool is fine-tuned for education. You don’t fine-tune models yourself — tool companies do this.

G

Generative AI — AI that creates new content (text, images, code) rather than just analyzing existing content. ChatGPT generates text. DALL-E generates images. Both are generative AI.

Gemini — Google’s AI assistant. Available free and integrated into Google Workspace (Docs, Slides, Sheets). Useful for teachers in Google-based schools.

GPT (Generative Pre-trained Transformer) — The technology behind ChatGPT. GPT-4 is the current advanced model. You don’t need to know how it works — just know that GPT-4 is more capable than GPT-3.5.

H

Hallucination — When AI generates information that sounds correct but is completely made up. AI can fabricate quotes, statistics, book titles, and even research studies. Always verify factual claims.

I

Iteration — Refining AI output by giving follow-up instructions. “Make it shorter,” “add an example,” “change the tone to more formal.” Iteration is how you get good results from AI.

L

Large Language Model (LLM) — The type of AI behind ChatGPT, Claude, and Gemini. It’s trained on massive amounts of text and predicts what words should come next. It doesn’t “understand” — it generates statistically likely responses.

M

MagicSchool — An AI platform built specifically for teachers. Has pre-built tools for lesson planning, quiz generation, rubrics, and more. Offers FERPA-compliant school plans.

Model — The AI “brain” that generates responses. GPT-4, Claude Sonnet, and Gemini are all models. Different models have different strengths.

P

Prompt — The instruction you give to an AI tool. “Write a quiz on fractions for 4th grade” is a prompt. Better prompts = better output.

Prompt Engineering — The skill of writing effective prompts. Includes being specific, giving context, specifying format, and iterating. Not as complicated as it sounds.

R

RAG (Retrieval-Augmented Generation) — A technique where AI searches a database before generating a response, reducing hallucinations. Some education tools use RAG to ensure answers are based on actual curriculum standards.

S

Scaffold — In AI context, providing structure in your prompt so the AI follows a specific format. “Write 3 paragraphs: first about strengths, then growth areas, then next steps” is scaffolding your prompt.

T

Temperature — A setting that controls how creative or predictable AI output is. High temperature = more creative, more random. Low temperature = more focused, more predictable. Most tools set this for you.

Token — The unit AI uses to process text. Roughly, 1 token ≈ ¾ of a word. Token limits determine how much text you can input and how long the response can be.

Training Data — The text an AI was trained on. ChatGPT was trained on internet text, books, and articles. It doesn’t have access to your school’s data unless you provide it.

Z

Zero-shot — Asking AI to do something without giving it examples. “Write a rubric” is zero-shot. “Write a rubric like this example: [example]” is few-shot. Few-shot usually produces better results.

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Bookmark this page and come back whenever you encounter a term you don’t recognize. We update this glossary as new AI tools and concepts emerge.