Crafting Clarity: Mastering AI Prompt Engineering in Education

Presented by Kris Hagel, James CantonwineConference WorkshopFor WERA Conference

Crafting Clarity: Mastering AI Prompt Engineering in Education

Presented on December 4, 2024, by Kris Hagel and James Cantonwine, this presentation focused on empowering educators with the skills to master AI prompt engineering. It covered foundational concepts, advanced prompting techniques, and strategies for creating reusable AI tools, all within the context of education.

Key Takeaways:

  • Embrace the AI Mindset: Similar to previous presentations, this one emphasized the importance of a proactive, exploratory approach to using AI in education.
  • Understand Your AI Comfort Level: The presentation encouraged participants to assess their comfort level with AI, ranging from "Cautious Observer" to "Innovation Leader," promoting self-awareness and growth.
  • Master Advanced Prompting Techniques: Four key techniques were explored to refine AI interactions:
    • Persona Pattern: Assign specific roles to AI (e.g., 3rd-grade teacher, superintendent, data scientist) to ensure contextually relevant and appropriate responses.
    • Few-Shot Prompting: Train AI by providing examples of desired outputs, similar to showing exemplar lesson plans or essays.
    • Chain of Thought Prompting: Elicit step-by-step reasoning from AI, mirroring the "show your work" approach in math education.
    • Template Pattern: Utilize structured templates for consistent AI outputs, analogous to using standardized rubrics or lesson plan formats.
  • Prioritize Data Security: The presentation introduced a tiered data security model for AI tools: Sandbox AI (general use), Lifeguard AI (vetted educational tools), Vault AI (secure, private environments), and Pocket AI (on-device processing).
  • Create Reusable AI Assistants: Develop customized AI tools to streamline tasks and improve efficiency.
  • System Prompts are Crucial: Understanding the components of system prompts – persona, audience, scope, tone, and instructions – is essential for effective AI interaction.

Actionable Insights:

  • Experiment with the Persona Pattern: Ask AI to explain educational concepts from different perspectives (student, expert, parent advocate) to gain new insights.
  • Practice Few-Shot Prompting: Create exemplar analyses of educational documents (student responses, teacher evaluations) to guide AI in processing similar documents.
  • Utilize Chain of Thought Prompting: Apply this technique to educational decision-making (student behavior analysis, budget allocation, curriculum planning) for more thorough analysis.
  • Develop Templates for Recurring Tasks: Create and test template prompts for tasks like weekly parent updates, professional development feedback, and program evaluation reports.
  • Use the Data Security Model: Categorize AI tools based on data sensitivity using the Sandbox, Lifeguard, Vault, and Pocket AI framework.
  • Explore Tools for System Prompt Writing: Leverage resources like the OpenAI Playground and materials from the Stanford Accelerator for Learning to improve your system prompt skills.

Looking Ahead:

This presentation equips educators with the knowledge and skills to effectively harness the power of AI through precise prompt engineering. By implementing these strategies, educators can leverage AI to enhance teaching, learning, and administrative tasks, ultimately fostering a more effective and engaging educational experience. The presentation emphasizes that mastering AI prompt engineering is crucial for unlocking the full potential of AI in education and creating a future where technology effectively supports both educators and students.