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AI4Educators

Foundations

AI glossary for educators

Learn the AI terms that show up in classroom tools, professional learning, school decisions, and conversations with students and families. Each guide connects the concept to real educational work and practical next steps.

  1. Academic integrityAlso used: AI and academic integrityAcademic integrity is the commitment to honest, transparent, and responsible learning, including clear acknowledgment of help and sources.
  2. AI agentsAlso used: Agentic AIAn AI agent is a system that can plan steps and use tools, such as search, files, or software actions, to work toward a goal.
  3. AI bias and fairnessAlso used: Algorithmic biasAI bias occurs when a system produces consistently less accurate, less fair, or less helpful outcomes for some people or groups.
  4. AI chatbotsAlso used: Chatbot, AI chatbotAn AI chatbot is a conversational interface that lets a person exchange messages with an AI model and, in some tools, connected data or actions.
  5. AI detectionAlso used: AI writing detectionAI detection is the attempt to estimate whether text or other work may have been created or substantially changed by an AI system.
  6. AI hallucinationsAlso used: Hallucination, AI hallucinationAn AI hallucination is a response that sounds plausible but includes information that is invented, unsupported, or inconsistent with the available source material.
  7. AI image generationAlso used: Generative image AIAI image generation creates a new image from a text description, reference image, or combination of instructions.
  8. AI literacyAlso used: Artificial intelligence literacyAI literacy is the ability to understand, question, and use AI tools thoughtfully, safely, and for an appropriate purpose.
  9. AI policyAlso used: Artificial intelligence policyAI policy is a shared set of rules and guidance that explains how an organization expects people to use AI responsibly.
  10. AI promptsAlso used: PromptA prompt is the information and direction you give an AI system to shape what it produces.
  11. AI tokensAlso used: TokenA token is a small unit of text or data that an AI model reads and generates as it processes a request and produces a response.
  12. AutomationAlso used: AI automationAutomation uses software, sometimes with AI, to complete a repeatable task or move information between steps with less manual effort.
  13. Citation with AIAlso used: Citing AICitation with AI is the practice of documenting how AI contributed to research, writing, analysis, or other work while still citing the original sources that support factual claims.
  14. Computer visionAlso used: Vision AIComputer vision is AI that identifies patterns, objects, text, or other information in images and video.
  15. Context and context windowsAlso used: Context, Context window, Context limitContext is the information available to an AI model for the current response; the context window is the limited amount of information the model can consider at one time.
  16. Data privacyAlso used: Student data privacyData privacy is the practice of protecting personal information and giving people appropriate control over how it is collected, used, shared, and retained.
  17. Generative AIAlso used: GenAI, Gen AIGenerative AI is a category of artificial intelligence that creates new content—such as text, images, audio, video, or code—from patterns learned during training.
  18. Large language modelsAlso used: LLM, LLMs, Large language modelA large language model, or LLM, is an AI model trained on large amounts of text to predict and generate language one piece at a time.
  19. Machine learningAlso used: MLMachine learning is a way of building software that finds patterns in data and uses those patterns to make a prediction, recommendation, or classification.
  20. Multimodal AIAlso used: Multimodal, Multimodal modelMultimodal AI can work across more than one kind of information, such as text, images, audio, video, or documents.
  21. Natural language processingAlso used: NLPNatural language processing, or NLP, is the area of AI that helps computers work with human language in text or speech.
  22. Prompt engineeringAlso used: Prompt designPrompt engineering is the deliberate process of designing, testing, and improving prompts so an AI system performs a task more reliably.
  23. Responsible AIAlso used: Trustworthy AIResponsible AI is the practice of designing and using AI in ways that are safe, fair, transparent, accountable, and appropriate for people affected by it.
  24. Retrieval-augmented generationAlso used: RAGRetrieval-augmented generation, or RAG, is a system that looks up relevant source material before an AI model writes its response.