Franklin Sayre

I’m the Makerspace Librarian at Thompson Rivers University and also Co-Chair the Librarians’ Department. These days I am particularly interested in creating active learning spaces that foster belonging and encouraging sustainability and critical thinking about technology and information.

Workshop Outline (2 hours)

Workshop Overview

This hands-on workshop invites participants to explore generative AI through the lens of their disciplinary expertise. I believe that GenAI is most (maybe only) interesting and useful for experts working within their areas of expertise. To get valuable responses, you need to understand the specific issues and language of your field. More importantly, your expertise allows you to use your judgment to evaluate when AI is giving you something useful or not.

As faculty and staff at a university, I think it is especially important that disciplinary expertise is central to our approach to generative AI.

We’re also going to focus on how AI might be used to enhance what we create, not on what AI can create independently. The distinction is subtle but important - we’re not interested in having AI generate content from minimal prompts, but rather in using AI to improve and extend the work we’re already doing as experts.

Setting Expectations

The workshop also follows a makerspace pedagogy since that is where I work and what I do, so the focus will be on learning through doing and reflecting.

This isn’t a computer science class. Whether you’ve used AI tools extensively or are trying them for the first time today, what matters is your disciplinary knowledge. We’re here to explore how AI intersects with your expertise, not to judge technical proficiency.

Finally, there are no manuals for AI, so instead of worrying about the “correct” way to use AI, we’ll emphasize playful experimentation, critical evaluation, and collaborative learning.

Instead of thinking of working with AI as something like computer programming, think about it as having a dialogue with another person. There are problems with this framing, but it also helps level the playing field.

One of the reasons I continue to do these workshops is that I want to find ways to engage with this technology that are critical, exploratory, and interesting. I am still discovering what that means and whether it is even possible.

Not everything we do today is going to work particularly well. It’s impossible to completely plan how generative AI models will respond to a given prompt, and even if you did, that wouldn’t reflect the reality you all experience once you leave the workshop.

Learning Objectives

By the end of this workshop, participants will be able to:

  • Demonstrate different techniques for prompting GenAI models
  • Apply personas and use context to AI prompts
  • Critically evaluate AI strengths and limitations based on their disciplinary expertise

Materials Required

  • Laptop/device with internet access for each participant
  • Access to an AI tool (ChatGPT, Claude, etc.)
  • Workshop resource page with shared document link

Workshop Flow

Part 1: Introduction and Collective Prompting (30 minutes)

  • Welcome and brief introductions (10 minutes)
    • Workshop purpose and objectives
    • Timer-guided round-robin: “Your name, role, and one thing you’d like to learn today” (1 minute per person)
  • Workshop meta-example: Exploring the workshop prompt (15 minutes)
    • Demonstrate the prompt used to create this workshop
    • Collaboratively discuss strategies visible in this prompt
    • Highlight key prompting principles and techniques
    • Demonstrate rapid iteration with 2-3 quick examples showing how to quickly try different approaches rather than spending time perfecting a single prompt
  • Brief overview of prompting strategies (5 minutes)
    • Introduce the strategy handout and shared document link
    • Emphasize the importance of quick, iterative prompting over perfectionism
    • Quick examples of each approach

Part 2: Individual Adaptation to Discipline (15 minutes)

  • Individual work: Adapt to your discipline (15 minutes)
    • Take the workshop prompt (see online resource) and adapt it to something you teach or do for work
    • Apply prompting strategies from the handout
    • Try at least 3 different prompt iterations within the 15 minutes
    • Note what was interesting, weird, and what the AI did right and wrong from your expert perspective
    • Copy your most effective prompt and interesting outcome to the shared document

Part 3: UDL Enhancement (15 minutes)

  • Individual work: Enhancing content with UDL principles (15 minutes)
    • Use AI to enhance your existing content by identifying opportunities to make it more inclusive and accessible
    • Prompt AI to evaluate your content based on UDL principles , including by pasting the content into the prompt
    • Ask AI for specific enhancements that align with UDL principles
    • Try at least 3 different prompt iterations within the 15 minutes
    • Copy your most interesting UDL prompts/responses to the shared document

Collaborative Review (10 minutes)

  • Group review of shared examples (10 minutes)
    • Facilitator highlights interesting examples from the shared document
    • Brief discussion of effective approaches and interesting outcomes
    • Identification of patterns and strategies

Break (5 minutes)

Part 4: Cross-Disciplinary Exploration (10 minutes)

  • Partner work: Swap and iterate from another disciplinary perspective (15 minutes)
    • Exchange the discipline-specific prompts you developed before the break with another participant (copy and paste from shared document is easiest, or swap computers)
    • Start a new conversation using their initial prompt
    • Start trying to develop a discipline-specific workshop for their discipline using UDL principles.
    • Apply at least 3 iterative prompts
    • Key reflection questions to consider as you work:

Part 5: Partner Feedback (10 minutes)

  • Prompt exchange review (10 minutes)
    • Return to original partners and together review what you created with each other’s prompts
    • Discuss how the AI responded differently to your discipline when prompted by someone else
      • How does working in an unfamiliar discipline change how you interact with AI?
      • What disciplinary assumptions become visible when working outside your field?
      • How does your own expertise influence how you approach another discipline?
      • How would a student in your class do at this?

Part 6: Collective Insights and Reflection (15 minutes)

  • Group works together to gather:
    • Observations about AI’s strengths and limitations
    • Role of expertise in using GenAI

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