# AI Glossary

Our comprehensive glossary for AI literacy in schools, made for teachers and students in K-12 education.

## Search glossary

[AI Accuracy](/content/ai-glossary/ai-accuracy/index.html)  [AI assistant](/content/ai-glossary/ai-assistant/index.html)  [AI Bias](/content/ai-glossary/ai-bias/index.html)  [AI Literacy](/content/ai-glossary/ai-literacy/index.html)  [AI Model](/content/ai-glossary/ai-model/index.html)  [AI Precision](/content/ai-glossary/ai-precision/index.html)  [AI Recall](/content/ai-glossary/ai-recall/index.html)  [Algorithm](/content/ai-glossary/algorithm/index.html)  [Artificial Intelligence](/content/ai-glossary/artificial-intelligence/index.html)  [Automation](/content/ai-glossary/automation/index.html)  [Chatbot](/content/ai-glossary/chatbot/index.html)  [Classification](/content/ai-glossary/classification/index.html)  [Context Window](/content/ai-glossary/context-window/index.html)  [Dataset](/content/ai-glossary/dataset/index.html)  [Deep Learning](/content/ai-glossary/deep-learning/index.html)  [Ethics in AI](/content/ai-glossary/ethics-in-ai/index.html)  [Generative AI](/content/ai-glossary/generative-ai/index.html)  [Image Recognition](/content/ai-glossary/image-recognition/index.html)  [Input/Output](/content/ai-glossary/input-output/index.html)  [Large Language Model](/content/ai-glossary/large-language-model/index.html)  [Machine Learning (ML)](/content/ai-glossary/machine-learning/index.html)  [Natural Language Processing](/content/ai-glossary/natural-language-processing/index.html)  [Neural Network](/content/ai-glossary/neural-network/index.html)  [Overfitting](/content/ai-glossary/overfitting/index.html)  [Prediction](/content/ai-glossary/prediction/index.html)  [Prompt](/content/ai-glossary/prompt/index.html)  [Prompt Engineering](/content/ai-glossary/prompt-engineering/index.html)  [Regression](/content/ai-glossary/regression/index.html)  [Speech Recognition](/content/ai-glossary/speech-recognition/index.html)  [System Prompt](/content/ai-glossary/system-prompt/index.html)  [Token](/content/ai-glossary/token/index.html)  [Training Data](/content/ai-glossary/training-data/index.html)  [Underfitting](/content/ai-glossary/underfitting/index.html)

## All Terms

[**AI Accuracy**  
  
Accuracy measures how often an AI model's predictions or answers are correct compared to the true results, showing its overall performance.](/content/ai-glossary/ai-accuracy/index.html)  
[**AI assistant**  
  
Learn what is an AI assistant, the digital tool that uses AI to help users complete tasks, answer questions, and enhance productivity.](/content/ai-glossary/ai-assistant/index.html)  
[**AI Bias**  
  
Bias in AI happens when a model unfairly favors certain ideas or groups, often because the data it learned from wasn’t fully balanced or fair.](/content/ai-glossary/ai-bias/index.html)  
[**AI Literacy**  
  
AI literacy means understanding how AI works, its uses, and its risks, helping people make smart, ethical decisions about AI tools and technology.](/content/ai-glossary/ai-literacy/index.html)  
[**AI Model**  
  
An AI model is a computer program trained on data to recognize patterns and make decisions, predictions, or generate content based on that training.](/content/ai-glossary/ai-model/index.html)  
[**AI Precision**  
  
Precision shows how many of an AI model’s positive results were actually correct, helping evaluate how exact the system’s responses are.](/content/ai-glossary/ai-precision/index.html)  
[**AI Recall**  
  
Recall measures how well an AI model finds all the correct answers, showing its ability to capture every relevant result from the data.](/content/ai-glossary/ai-recall/index.html)  
[**Algorithm**  
  
An algorithm is a step-by-step set of rules or instructions a computer follows to solve a problem or perform a specific task efficiently and accurately.](/content/ai-glossary/algorithm/index.html)  
[**Artificial Intelligence**  
  
AI is the ability of machines to perform tasks that typically require human intelligence, such as learning, reasoning, and decision-making.](/content/ai-glossary/artificial-intelligence/index.html)  
[**Automation**  
  
Automation uses technology to perform tasks with little or no human help, speeding up processes like grading, scheduling, or data entry.](/content/ai-glossary/automation/index.html)  
[**Chatbot**  
  
A chatbot is an AI tool designed to simulate conversation with users, answering questions, providing help, or chatting in a human-like way.](/content/ai-glossary/chatbot/index.html)  
[**Classification**  
  
Classification is when an AI sorts data into categories, like labeling emails as spam or not spam, based on learned patterns.](/content/ai-glossary/classification/index.html)  
[**Context Window**  
  
A context window is the amount of text or information an AI model can remember and consider at one time when generating responses or making decisions.](/content/ai-glossary/context-window/index.html)  
[**Dataset**  
  
A dataset is a collection of organized information—like texts, images, or numbers—used to train, test, or evaluate an AI system’s performance.](/content/ai-glossary/dataset/index.html)  
[**Deep Learning**  
  
Deep Learning is a branch of machine learning that uses layered neural networks to process large amounts of data and solve complex problems like vision and language.](/content/ai-glossary/deep-learning/index.html)  
[**Ethics in AI**  
  
Ethics in AI focuses on making sure AI systems are fair, transparent, safe, and respectful of human rights while avoiding harm and bias.](/content/ai-glossary/ethics-in-ai/index.html)  
[**Generative AI**  
  
Generative AI creates new content—like writing, art, music, or code—by learning patterns from existing data and producing original outputs.](/content/ai-glossary/generative-ai/index.html)  
[**Image Recognition**  
  
Image recognition is when an AI identifies objects, people, or scenes in pictures, helping with things like facial recognition or photo tagging.](/content/ai-glossary/image-recognition/index.html)  
[**Input/Output**  
  
A neural network is a computer system inspired by the human brain, made of layers that process data and learn patterns to make decisions or predictions.](/content/ai-glossary/input-output/index.html)  
[**Large Language Model**  
  
A Large Language Model is an AI trained on huge amounts of text to understand, generate, and predict human language across many topics and tasks.](/content/ai-glossary/large-language-model/index.html)  
[**Machine Learning (ML)**  
  
Machine Learning is a type of AI where computers learn from data and improve over time without being explicitly programmed for each task.](/content/ai-glossary/machine-learning/index.html)  
[**Natural Language Processing**  
  
NLP helps computers understand, interpret, and respond to human language in ways that are meaningful and useful.](/content/ai-glossary/natural-language-processing/index.html)  
[**Neural Network**  
  
In this guide, we’ll be covering the meaning of an **neural network**: what it is, its key aspects, and why its relevant to education.](/content/ai-glossary/neural-network/index.html)  
[**Overfitting**  
  
Overfitting happens when an AI model learns its training data too exactly, making it less accurate when working with new, unseen data.](/content/ai-glossary/overfitting/index.html)  
[**Prediction**  
  
Discover how AI prediction works in education. Learn how predictive tools forecast student needs, personalize learning, and support early intervention.](/content/ai-glossary/prediction/index.html)  
[**Prompt**  
  
A prompt is the text or question you give an AI to tell it what you want it to do, like answering, writing, explaining, or creating something.](/content/ai-glossary/prompt/index.html)  
[**Prompt Engineering**  
  
Prompt engineering is the skill of crafting effective instructions or questions to get better, more accurate results from an AI system.](/content/ai-glossary/prompt-engineering/index.html)  
[**Regression**  
  
Regression is when an AI predicts a continuous value, like forecasting a student’s score or house prices, based on input data.](/content/ai-glossary/regression/index.html)  
[**Speech Recognition**  
  
Speech recognition is when an AI listens to spoken words and converts them into text or actions, like voice typing or virtual assistants.](/content/ai-glossary/speech-recognition/index.html)  
[**System Prompt**  
  
A system prompt is an instruction given to an AI to set its behavior or role, guiding how it responds throughout a conversation or task.](/content/ai-glossary/system-prompt/index.html)  
[**Token**  
  
A token is a small piece of text, like a word or part of a word, that AI models use to read, understand, and generate language step-by-step.](/content/ai-glossary/token/index.html)  
[**Training Data**  
  
Training data is the information used to teach an AI model how to recognize patterns, answer questions, or make predictions based on examples.](/content/ai-glossary/training-data/index.html)  
[**Underfitting**  
  
Underfitting happens when an AI model is too simple to learn the patterns in its training data, leading to poor performance and wrong predictions.](/content/ai-glossary/underfitting/index.html)