🥼 RESEARCH
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On this page

  • Discussion Outline
    • Case Study: Not All Chatbots Teach
    • Implications for Teaching
    • Reflect & Discuss
  • Prompt Engineering for Learning
    • Using Prompts as Guardrails
    • Prompt Examples
    • Reflect & Discuss
  • Exploring Generative AI Providers
    • Major Providers
    • Building Custom Chatbots for Canvas
    • Reflect & Discuss
  • Wrap-up
  • Next Steps

Meeting 2: Prompt Engineering and Integration Brainstorming

Discussion Outline

  1. Pedagogical Use Cases of AI
  2. Prompt Engineering Strategies for Learning
  3. Exploring Generative AI Providers for Canvas Integration
  4. Group Reflection & Discussion

Case Study: Not All Chatbots Teach

  • Recent study: Not All Chatbots Teach
  • Compared a structured, outcome-aligned chatbot vs. a generic LLM wrapper
  • Key finding: Structured AI tools significantly improved student performance and clarity in software testing tasks

Implications for Teaching

  • Structure and scaffolding matter
  • Alignment with learning outcomes is crucial
  • Promotes metacognition and reduces surface-level AI use

Reflect & Discuss

Questions:

  • Where have you seen AI help or hinder student learning?
  • What risks or opportunities do you see in using AI inside your own course context?

Prompt Engineering for Learning

  • Prompts = Pedagogical design space
  • AI output quality hinges on the prompts we design

Using Prompts as Guardrails

  • Instructor-written prompts can:
    • Set boundaries (academic integrity, tone, focus)
    • Scaffold learning (step-by-step guidance, Socratic questioning)
    • Encourage metacognition (reflect on process)

Prompt Examples

  • “Ask the student questions to deepen their understanding of X.”
  • “You are a peer reviewer. Give friendly but rigorous feedback on their code.”
  • “Use the Feynman Technique to help the student clarify their concept.”

Reflect & Discuss

Questions:

  • What kind of prompts might support your students’ learning?
  • How can prompt templates become reusable teaching assets?

Exploring Generative AI Providers

  • Let’s compare the top options for integration and customization:

Major Providers

Provider Notes
OpenAI GPT-4o, API access, supports embeddings, used widely
Gemini Google’s LLM, integrated into Google Workspace, strong data privacy controls
Anthropic Claude Emphasizes safety and guardrails
Cohere, Mistral, HuggingFace Research/community focused, fine-tuning support

Building Custom Chatbots for Canvas

🛠️ Options include:

  • OpenAI Functions + Flask/FastAPI backend
  • Google Cloud Vertex AI with Gemini + Dialogflow
  • Custom wrappers using LangChain or Semantic Kernel
  • Embed into Canvas via LTI tools, iframes, or static tools

Reflect & Discuss

Questions:

  • What role could a chatbot play in your course?
  • Would it be formative, summative, exploratory?
  • What barriers do you foresee?

Wrap-up

Today’s Themes:

  • Pedagogical framing is essential for AI tools
  • Prompting is teaching
  • Integration is possible — and powerful — in Canvas

Next Steps

  • Share a prompt or idea in our collaborative doc
  • Try one AI tool this week — reflect on use
  • Prepare for Next Week: Deeper Prompt Engineering and use case design