1. Artificial Intelligence (AI)

Definition: A field of computer science focused on creating systems capable of performing tasks that typically require human intelligence, such as decision-making, pattern recognition, and language understanding.

Classroom Example: An AI-powered writing assistant gives students real-time suggestions to improve grammar and clarity in their essays.

2. Machine Learning (ML)

Definition: A subfield of AI where algorithms learn from data to improve performance on a specific task without being explicitly programmed for every scenario.

Classroom Example: A learning platform uses ML to adjust reading levels for students based on their past performance and growth.

3. Large Language Model (LLM)

Definition: A type of AI model trained on massive text datasets to understand and generate human-like language, often used in chatbots and writing tools.

Classroom Example: Students use an LLM to rephrase research findings in simpler language for a middle school audience.

4. Generative AI

Definition: AI systems designed to create new content—such as text, images, music, or code—based on patterns learned from training data.

Classroom Example: A teacher has students evaluate the accuracy of an AI-generated science explanation compared to textbook information.

5. Prompt Engineering

Definition: The process of crafting effective inputs or questions to guide AI systems in producing accurate, useful, or creative outputs.

Classroom Example: A teacher shows students how small changes in wording can produce different responses from an AI chatbot.

6. Prompt

Definition: A user’s input to an AI system, often in the form of a question or command, that determines the system’s response or output.

Classroom Example: A student types “Summarize this article in 3 sentences” into an AI tool to help with note-taking.

7. ChatGPT

Definition: An AI chatbot developed by OpenAI that uses a large language model to understand and generate natural language responses, often used for educational assistance, writing, and conversation.

Classroom Example: Students use ChatGPT to brainstorm ideas for persuasive essays and compare them to their own drafts.

8. AI Literacy

Definition: The ability to understand, evaluate, and responsibly use artificial intelligence tools and systems, including awareness of their limitations, potential biases, and ethical implications.

Classroom Example: A digital citizenship unit teaches students how to fact-check AI-generated content and understand the risks of overreliance.

9. Ethical AI Use in Education

Definition: The practice of using AI tools in ways that protect student data, promote fairness, support equity, and ensure human oversight in decision-making.

Classroom Example: A school chooses an AI tutoring platform that avoids collecting unnecessary personal data and includes teacher monitoring features.

10. Human-in-the-Loop (HITL)

Definition: A design approach in AI systems that ensures a human remains involved in critical decisions, especially those that impact learning, assessment, or student wellbeing.

Classroom Example: An AI grades essays for grammar but flags any ambiguous results for teacher review.

11. Adaptive Learning

Definition: Educational technology that uses AI to personalize the learning experience by adjusting content, pace, and instructional methods based on a student’s individual performance and needs.

Classroom Example: An adaptive math platform provides a struggling student with more practice problems on a specific concept, while an advanced student receives challenging enrichment activities.

Citation: Pane, J. F., Steiner, E. D., Baird, M. D., Hamilton, L. S., & Doss, C. J. (2015). *The promise of personalized learning*. RAND Corporation.

12. AI-Powered Tutoring Systems

Definition: AI applications designed to provide individualized academic support, often offering explanations, feedback, and practice exercises tailored to a student’s learning gaps.

Classroom Example: A student uses an AI tutor to get step-by-step guidance on a complex physics problem outside of class hours.

Citation: Woolf, B. P. (2009). *Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning*. Morgan Kaufmann.

13. Natural Language Processing (NLP)

Definition: A branch of AI that enables computers to understand, interpret, and generate human language, crucial for applications like AI writing assistants and chatbots.

Classroom Example: An NLP-driven tool analyzes student essays to provide feedback on coherence and argumentation, not just grammar.

Citation: Jurafsky, D., & Martin, J. H. (2009). *Speech and language processing: An introduction to natural language processing, computational linguistics, and speech recognition*. Prentice Hall.

14. Explainable AI (XAI)

Definition: An emerging field of AI that aims to make AI systems more transparent and understandable to humans, particularly regarding how they arrive at their decisions or recommendations.

Classroom Example: A teacher uses an XAI-enabled assessment tool that not only gives a score but also explains *why* certain answers were marked incorrect, helping students understand their misconceptions.

Citation: Gunning, D., & Aha, D. (2019). DARPA’s explainable artificial intelligence (XAI) program. *AI Magazine*, *40*(2), 44-58.

15. AI Ethics Guidelines

Definition: Principles and recommendations developed by organizations or governments to ensure that AI is developed and used responsibly, fairly, and with respect for human rights and societal well-being.

Classroom Example: A school district adopts AI ethics guidelines that require transparency in how student data is used by AI educational tools and mandate human oversight for high-stakes decisions.

Citation: European Commission. (2019). *Ethics guidelines for trustworthy AI*.