Our Presentation Slides, with speaker notes

  • Speaker Notes: Project name, who worked on it, we are creating a resource guide on AI in LD in partnership with TLL, informed by survey of LDs and our own research​

  • Speaker Notes: None, slide is self-explanatory

  • Speaker Notes: What we did:​ 1 – discussions with Gabe, Allison Pingree, AI and LD class session, Nicole Nash (all using AI)​ Project flow – initial focus was tools used by TLL but decided to expand our focus to LDs in general; made that decisions because TLL is restricted to certain tools; other LDs have varying regulations regarding tools ​ ​ 2 – using Qualtrics, key categories (familiarity, present + potential applications, best form for resource guide), surveyed 22 responses and hoping to get more (push survey)​.

  • Speaker Notes: -Q13 – talking more about the results​  since we know our target audience has familiarity with AI and feels comfortable: we could instead focus on upskilling with AI; less energy devoted to what is AI/explaining tech (not "how do I use AI" but "how do I use AI well"​

  • Speaker Notes: 1. The most popular choices for what people thought AI could help with were: drafting learning objectives, content research, course structure/outlines, prototypes, generating feedback​ Discuss, if time, the "I don’t do this" section​: learning designers are varied and don't all do the same tasks

  • Speaker Notes: -share top 3, those with the stars​ -intend to focus on creation on these things in the times we have​ -thinking about time and resources (constraints)​ -things that surprised us about results (low response on access to research; people want to make these decisions themselves on where to use AI; LDs using AI in their workflow vs LDs implementing AI in the learning experiences they create)​

  • Speaker notes: none, self-explanatory

Reflection

Post a reflection to your portfolio about your experience during the Deliver module. You may consider the design of the Gallery Walk in the context of course learning outcomes. Perhaps you want to reflect on what you learned from audience members and how that will inform your Capstone. Or you may consider the team based approach (if applicable) to presenting a collaborative project.  

My experience of the gallery walk was a good one! Katie and I have been working on the AI in Learning Design project this semester, and we’ve done pretty much everything in tandem. We met at the same time each week, have made decisions together, have designed and collected data together. So it was natural that we prepared for the presentation together. We wrote the content and created the slides. She pulled in the data and I designed the look of the presentation.

Our experience was that we learned quickly HOW to talk about our work. We started with the WHY of this project -everyone liked the ‘you won’t lose your job to ai but you will to someone who knows how to use ai’ quote. From there we explained our process and then explored some of the answers with the audience. We learned a lot from the interactions with the audience. Some people said that the responses were interesting because they weren’t future-facing, but grounded in the current experience. Some were surprised by the level of comfort people reported with AI, because they themselves were very unsure about it. We also had the opposite reaction: one audience member spoke about themself as “very pro-AI,” and fascinated by people who don’t want to see it become part of LD work. Some wanted to know more about the least useful potential applications of AI in LD work, as given by our survey (turns out that’s mostly Content Research, people do not think it will be useful in that regard). We also had several practicing learning designers as audience members who took our survey there and then, and we appreciate their responses.

All the responses and input we got was relevant. We used this experience to inform our next steps of research and creating the guide. Based on the responses we got, we’re going to seek out case studies, address an audience that is already comfortable with AI, focus on successful applications of AI and let the readers decide what their course of action will be, and not recommend anything to do with content research or the Ethics of AI use.

Our final project will be posted on a site designed on Microsoft Sway.

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