Microsoft Copilot in education

Microsoft Copilot is transforming the way educators and students engage with technology in the classroom. This article introduces Copilot’s capabilities, explains the fundamentals of generative AI, and provides guidance on using AI responsibly in educational settings. Explore how Copilot and other AI tools can support teaching, learning, and productivity in your school community.

What is generative AI and Microsoft Copilot?

• Microsoft Copilot is a tool that uses generative AI (GenAI) to serve as a helpful assistant to you in the classroom. Copilot can help you save time, differentiate instruction, and enhance student learning. With Copilot, you can easily create lesson plans, quizzes, rubrics, and other class resources for any level of learner. Microsoft Copilot comes in three main versions:

  • Copilot for Microsoft 365 - Microsoft 365 apps like Word, Excel, PowerPoint, Outlook, and Teams. It requires a subscription and is designed to enhance productivity by leveraging enterprise-specific data.
  • Copilot Pro - This is a subscription-based version that offers priority access to GPT-4 and GPT-4 Turbo during high traffic times. It includes additional features and capabilities for business users.
  • Free Microsoft Copilot - This version is available to everyone using Windows, Microsoft Edge, or the Bing website. It provides general AI assistance without the specialized features of the other versions.

• Generative AI - GenAI - Generative AI, often abbreviated as GenAI, is a subset of artificial intelligence that focuses on creating new content. This can include text, images, videos, audio, and even software code. GenAI models are trained on vast amounts of data to learn patterns and structures, enabling them to generate original content based on user prompts. For example, tools like ChatGPT for text, DALL-E for images, and various other models for different media types are all applications of generative AI.

• Build the future of your organization with AI - Microsoft helps you scale AI confidently across your organization, wherever you are in your AI journey. Achieve new productivity levels and learn how to securely integrate AI for all your business needs.

• Large learning models (LLM) - A large language model (LLM) is a type of artificial intelligence model designed to understand and generate human-like text. These models are trained on vast amounts of text data, learning the statistical relationships between words and phrases to perform various natural language processing tasks.LLMs can generate coherent and contextually relevant text, translate languages, summarize documents, and even engage in conversations. Examples of LLMs include OpenAI’s GPT-4, Google’s PaLM, and Meta’s LLaMA.

• ChatGTP - ChatGPT (Chat Generative Pre-trained Transformer) is a conversational AI model developed by OpenAI. It uses an LLM to understand and generate human-like text based on the input it receives. ChatGPT can perform a variety of tasks, such as answering questions, writing essays, generating creative content, and even coding. The model is trained on a diverse range of internet text, allowing it to provide detailed and contextually relevant responses. It’s widely used for customer service, educational purposes, and personal assistance.

AI techniques

• Grounding- Grounding in AI refers to ensuring that the AI’s responses are based on accurate and relevant data. Grounding in Generative AI (GenAI) refers to anchoring AI-generated content to real-world data, factual knowledge, or specific sources, ensuring that the responses are accurate, reliable, and contextually appropriate. This process is crucial for making GenAI outputs relevant and actionable in various applications, from customer service to content creation. Grounding methods include using retrieval-augmented generation (RAG) to pull in specific data in real-time, linking to APIs or databases, or fine-tuning models on specialized corpora. Grounding helps reduce inaccuracies and improves the trustworthiness of the AI’s responses. Grounding typically involves feeding the model:

  • Domain-Specific Data: This could be industry information, customer databases, product catalogs, or any proprietary data that makes the AI knowledgeable in a specific area.
  • Factual Sources: Using verified databases, documents, or real-time information to prevent the model from generating incorrect responses, facts, or details.
  • User Intent and Context: Understanding the specific requirements of the user in the given moment so that the responses are relevant.

• Generative Pre-trained Transformers (GPTs) - GPTs are a type of language model developed by OpenAI designed to generate human-like text based on a given prompt.

  • Conversational AI: Develop chatbots that can engage in natural, human-like conversations.
  • Language Translation: Translate text between different languages with high accuracy.
  • Text Summarization: Condense long documents into concise summaries.
  • Creative Writing: Assist in writing stories, poems, and other creative content.

Education AI guardrails

• Microsoft's framework for building AI systems responsibly

AI for education

• Resources and learning opportunities
  • Embark on your AI journey with free AI tool from Microsoft Education
  • Empower educators to explore the potential of artificial intelligence
  • Enhance teaching and learning with Microsoft Copilot
  • Support reading fluency practice with Reading Progress
  • Equip and support AI tools from Microsoft
  • AI in education

Getting started

• Getting started with free AI tools from Microsoft Education
• Microsoft Copilot
• GitHub Copilot
• Learning Accelerators
• Microsoft Teams for Education
• Minecraft Education AI foundations
• Khanmigo for Teachers
• Unlocking productivity and personalization learning with AI