(April 2024) AI Copilot for Education: Session 5 of AI in Education Series

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[Detra Price] This is really such an incredible opportunity we have as as a

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community at EHE to be able to host these monthly conversations around AI.

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And today we are so excited to have two incredible subject matter experts who I

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think have been on tour like Tina Turner or The Rolling Stones talking to

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everybody around the university, Bruce Springsteen,

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talking to everyone around the university about generative AI.

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But today we wanted to invite them in to specifically talk with us about Copilot.

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We have Doctor Larry Hurtubise and Dr.

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Dave Sovic from the Drake Institute for Teaching and Learning,

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and I know we’re in for a treat.

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And again, for those of you just joining us,

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please use the chat throughout to introduce yourself, to share resources,

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to raise questions.

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We would like to engage with you throughout this conversation.

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And I believe I will now turn it over to Larry and Dave.

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[Larry Hurtubise] Awesome.

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Thank you, Detra.

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It’s really exciting to be here today.

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And so again, my name is Larry Hurtubise.

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And one of the things roles that I’m doing at the university is and with the

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Drake Institute is leading our planning for programming around AI, generative AI.

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And so just get an opportunity to work with a lot of people from around the

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campus and it’s really exciting.

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So you’ll notice on this slide, there’s a QR code as well as a URL and I

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put the URL in the in the chat as well.

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So that’s where all of our resources are.

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So there’s a link to this presentation as well as a link to a sample of some

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prompts that I did with Copilot for creating a course in sports management.

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So, so that’s there for you and we will

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discuss. And I got this, this paragraph off the ISTE site and it

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felt like it really sort of encompassed what I think is sort of our goals as we

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go forward.

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And it’s sort of to think, be comfortable teaching with and about

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artificial intelligence, rethinking and redesigning learning,

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strengthening learning experiences and having addressing its ethical

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considerations.

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But in the end, it feels like it’s all of our role and

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duty to thoughtfully, safely and responsibly introduce AI that

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enhance learning and empowers students and teachers.

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So hopefully we’ll just touch on a lot of those subjects,

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but that’s I think our goal.

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And so just to start off with some key terms, by the way,

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this key I made using Copilot and the prompt that I use is at the bottom.

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You are a medical educator giving a presentation.

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Create a simple black and white wood block print of an old fashioned key you

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can use on a slide introducing key terms.

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And so this is the the key that I got.

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And So what is generative AI?

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Well, artificial intelligence really mimics

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intelligence and it’s really what it’s doing

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it’s predicting what you think, what it thinks you want to see next in in

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your paragraph or in your images that you’re creating.

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And it feels like based on your introduction, Detra,

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that you guys have already looked at AI a lot and this is sort of in the middle.

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So I, I will sort of move on from defining,

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but I did wanna share with you one of the things that’s happening at Ohio State is

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that they’re looking at RAG or Retrieval Augmented Generation.

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And so the idea there is instead of going sort of straight to the Internet,

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RAG would go to Ohio State data first.

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And so as as you look at sort of this example,

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how many credit hours does the post candidacy student have to maintain at OSU.

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The feedback went in ChatGPT just went it was prompted was vague and incorrect.

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But when they, and that this was again, our OTDI folks are piloting this now when

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they put used Ohio State data, it was still correct or it was correct,

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but still general.

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And so this is something they’re working on.

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I wanted to sort of let you all know about this so that perhaps if you are

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asked to provide use cases for how they program the RAG,

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then you’ll be kind of aware of what it is.

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And I wanted to share, you know, sort of what’s in the black box then.

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And in addition to sort of the normal large language model and predictive

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algorithms.

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What they’ve demonstrated so far though, as you folks is that it can,

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you can have questions answered like what to do when it doesn’t know.

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So instead of hallucinating or guessing, you can say, if you don’t know,

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say I don’t know, if you don’t have the data,

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say I don’t know.

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And then you can also tell it what not to do.

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And so, for example, I’ve tried to get Copilot to create an

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image of Abraham Lincoln.

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It won’t do it.

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It won’t create images of real people.

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I can get it to create images of sort of general people, but not specific,

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not a specific person.

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Just to give you an example of how one school is using this just as sort of and

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imagine the possibilities at NYU College of Medicine,

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what they’re doing is they have the data from their electronic medical record of

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what their third year medical students are inputting.

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And what they’re doing is then directing that toward the NYU materials that have

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been created there, as well as articles and research in Pub

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Med.

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And then they’re summarizing that for the students.

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And so you can see that it it what they’re calling that is precision medical

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education.

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And I can imagine a time when you might say, here’s my course number,

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here’s the materials, here’s the literature that I want you to

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search.

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Connect with top hat, make some questions for me and top hat

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make some practice questions for students.

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Perhaps student records are connected so that if they are need help in a certain

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area, AI always make sure that they get that.

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And maybe it doesn’t tell you the instructor what the student is weak in.

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And maybe the student doesn’t want you to know that they were deficient in the past

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in a certain area.

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Maybe they want a fresh start.

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So just giving you some ideas of what what might be around the bend.

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In terms of getting started prompting,

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We have developed this model or this diagram to help prompting and so we call

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it SPARC.

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And so that’s sort of the first letters of the different portions of this model.

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And so the first part is a self reflection.

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So what’s important to you?

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What’s your teaching philosophy?

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Who are your learners?

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You wanna reflect on those things, your context.

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And then the P stands for prompting and we’ll take you through a TRACI model of

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prompting here in a second.

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And then academic requirements.

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So what are the accreditation standards or disciplinary specifics that you wanna

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make sure that AI is aware of as you’re prompting it?

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And then research on pedagogy.

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So that could be backward design, universal design for learning,

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Bloom’s Taxonomy, Fink’s taxonomy.

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So you would pick whichever research you again, want AI to focus on,

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and then you’re gonna critique that basically aligned with your goals.

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And does it really match your self

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reflections, your academic requirements, your research, is it matching that?

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Is it aligned well?

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And so here is the TRACI framework.

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Are you all familiar with prompting frameworks?

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So looks like Casey, you’re reading it or are you saying, no,

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I’m not familiar.

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So essentially what you can do is you can give it a task.

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So what it is you want it to do, you can give it a role.

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Who is it that the AI is playing?

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What role are they playing?

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Who are they responding to?

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So who is it for?

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What do you want them to create?

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And then what’s the intent?

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And so to get started sort of thinking about the model,

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that SPARC model and the self reflection.

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so that activity that we had you do at the very beginning.

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Some common metaphors for educators are gardeners, coaches,

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tour guides and sculptors.

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And folks who think of themselves as gardeners then tend to think of students

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as plants and tend to think of themselves as being responsible for creating an

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environment for growth and that the student isn’t responsible for that.

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Folks who tend to think of themselves as coaches think of students as athletes and

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think of themselves as liking to work on teams and being goal directed.

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And the coach kind of stands back and directs,

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but it’s not sort of in there with them.

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Tour guides are more in there with them, but the the students are tourists.

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And so they’re only there temporarily.

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And then sculptors think of their students as clay.

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So they’re molding the students.

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And again, the students have less sort of

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responsibility or agency in that process.

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And so I just wanted to share these are the images that I had copilot create

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related to those metaphors.

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And just to give you a a little bit of a critique,

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when I first started trying to get images of coaches, they all seem to be white men.

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And so it’s like, OK, we need to tell it that I want something

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different.

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And then the clay powder that that had some issues with it as well.

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I find that if I put a sunset in the back, I like the picture better.

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And we’ll share you that share with you.

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We do this activity in our CDI and, and one of the people said that they were

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like a surfer and I was like surfer.

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And when they explained it, it’s like if you’re a surf instructor,

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you have to keep your students safe.

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You have to be out there with them, but in the end you have to surf.

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So it’s like, oh, there’s some flexibility.

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And so I kind of like that metaphor.

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And what I’m using these metaphors for is really a placeholder for anything that

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you might think about in that self reflection that’s not related to your

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discipline or your academic requirements or a model.

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So that might be your teaching philosophy, your epistemology,

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your teaching perspective.

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I don’t know if you all can think of things that you might put in that

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reflection.

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You know, as you’re thinking about what’s most

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important to you, what are your big rocks?

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That’s what you would put in the S.

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And then we’ve talked about the TRACI model and then for the AI have some links

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to some of your standards for accreditation, but you might say, hey,

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I want to use these.

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And for the R, just put some ideas in there of,

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of research on pedagogy or people who have models or theories that you might

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again link to.

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And then here’s some questions you might use when you’re critiquing.

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So what did you anticipate AI would give you?

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How did that align with your self reflections,

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academic requirements and pedagogy?

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What part of the prompt will you change?

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So that might be things that you change.

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And so here is an example of a prompt that I put in and said you are a

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professor in a teacher preparation program.

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Develop a short 5 sentence e-mail welcoming students to your Introduction

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to Teacher Preparation course.

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The e-mail should have three learning goals that are aligned with Fink’s

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Significant Learning taxons of application, human dimension,

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and learning to learn.

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The tone of the e-mail should promote a growth mindset.

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So can you see in this diagram that sort of the TRACI elements of the prompt?

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Can you see that the task and the role, are there any that you don’t see or that

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you have a question about?

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Awesome.

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And so this is what I got.

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Welcome to the Introduction to teacher Preparation course.

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As we embark on this educational journey together,

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our collective goal is not to only acquire knowledge,

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but to transform how we see ourselves and the world of teaching.

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Through this course, we will focus on three learning goals,

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applying educational theories into practice,

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understanding the human dimension of teaching and its impact on both students

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and educators, and mastering the art of learning to

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learn, which will empower you to continue

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growing beyond the classroom,

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embrace

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embrace challenges as opportunities for growth,

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and remember that that every effort you make is a step toward becoming an

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educator you aspire to be.

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Looking forward to a semester of significant learning and growth.

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So what do you think of this as a e-mail?

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By the way, this is exactly what I got.

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Even with the bolding was what I got.

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So what do you think?

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Is this?

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Is this an e-mail that you could use?

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Would you change it?

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[Dave Sovic] One comment I have there is just in thinking about the context here,

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it might something that I see is potentially missing is thinking about who

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are the students?

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At what level are these students?

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What what type of course, because that could change some of the

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language, you know, the complexity of language,

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the the expectations for the amount of growth, that type of thing.

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If these are new students in a brand new, you know,

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just getting started Ed prep program, maybe I want to let it know and say,

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you know, this is a good start.

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Now rewrite this for students just starting in a brand new program as, yeah,

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new students at the university or something like that.

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So they’re just thinking about that additional context.

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And I think that’s where that S step in the SPARC model where you’re reflecting,

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thinking about what’s important thing about the context can really help in

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generating these prompts.

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[Larry Hurtubise] Yeah.

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And that, that actually brings up a great point,

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Dave, ’cause I’m not sure that AI knows the

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difference between a freshman, sophomore, junior, senior, grad student,

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6th grade grader, right?

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So I didn’t say, I said that this was a teacher

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preparation course and professor, but I didn’t necessarily say higher

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education and I did say students.

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So I decided to, there’s a educator in health and

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rehabilitation sciences who has started staying,

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summarizing his lessons or his modules and wanting them to be,

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I think hip and funny is the term, the phrase he used to sort of describe

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what he was looking for and that, hey, it’s making his summaries better and

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people are reading them.

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And so I thought, hey, well, let’s try that.

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So I put this is a great start.

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Can you write it with a funny informal tone?

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So this is what I got and when I did this like if I think about this,

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this maybe looks like 6th graders would might appreciate this, right?

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And I checked with one of our grad students.

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How many of you know what the flip side is?

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It’s the B side of a 45.

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So, so it, it’s like, I’m not sure they’re getting what catch

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you on the flip side.

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I’m not sure that’s gonna endear you anyway.

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So it it doesn’t work for me, but I don’t know if it works for you.

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But so that’s an idea of how I might have changed it with the intent,

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changing the intent of the of the prompt.

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And so now I thought we’d try a group activity.

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And I’m going to go back to this is the web page that we’ve set up for this

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session that has the presentation materials and sample course design

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prompts.

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And you can see in the upper, I mean it also has the TRACI and some OSU

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resources as well as references and additional resources from outside of OSU.

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But you can see in the upper right hand corner you have Copilot.

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And so then you can, if you click on that, you’ll get this model.

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If you don’t see this green protected link there,

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that means you haven’t logged in and you’ll probably in the middle of your

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screen have a place where you can.

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It’ll say the login, so you have a link to login and you just

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use your OSU name, dot number and password.

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If you work in the Medical Center or have an OSUMC,

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you just use that e-mail and it’ll work.

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And then I would suggest using more creative,

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but you can try the same prompts and more balanced and more precise and see what

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you get.

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See if one of those works better for you.

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But basically, while you’re here, you just type in the prompt that you want

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to put in.

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And so we have a, a few minutes to would folks like me to

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prompt something or do you just want to try it on your own and see how it works?

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Maybe prompt something that is from your context, so giving, you know,

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maybe a beginning e-mail or right learning goals or something like that.

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Or is there something you’d like me to try?

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So I know that there’s an APA way to cite and then for me there’s kind of an

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ethical.

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How do you cite?

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So for instance, on that image, I put the prompt I use and let me show

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you this example.

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So I did.

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Are you seeing the introduction to sports management course design?

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So basically I put in the TRACI prompt and asked it to give me goals and then

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expected learning outcomes and then that were aligned with the goals and then a

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constructive alignment table.

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And I will say, getting back to your amount of time,

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that it took me longer to format it so that there would be a table of contents

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and that the.

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I’m trying to think of it and see if I have one.

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Yeah.

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So see how this table heading ’cause it goes over a page, repeat.

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So I had to do that.

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I had to make sure that, you know, change all the tops to red.

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So, so it took me longer to do that than to

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actually do the, the prompting.

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I don’t know because I’m not in sports management whether or not this is

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something that’s usable, but I wanted to give it to you all as an

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example.

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But for me doing this, this is what I prompted.

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Let’s see, here’s the prompt and then here’s what

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Copilot said when you did it.

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So I have the at the top prompts response by Copilot for Bing On this date.

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So to me, it’s, I think that’s sort of an ethical example

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that we wanna set, right?

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Like if you’re using it, then you need to share that you used it.

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And this is an example of a audit trail.

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So you can see what I prompted, what I got, what I prompted next,

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what I got, what’s not in here that I would add to an

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audit trail is what I thought.

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So why did I prompt what, what, what was my critique of what I got?

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And so that’s a way that you can come alongside students and say,

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what are you prompting?

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What are you, what are you getting?

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What do you think about that?

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What’s your critique of that?

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Sort of a, a think out loud, if you will.

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but and then I would say as educators telling students,

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this is how I want you to cite it.

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This is how I want you to track what you’re doing and why you’re doing that,

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right.

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So we’re learning to use this new tool together and it’s a new world.

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And so we need to share with with each other what we’re thinking,

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how we’re doing that.

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So Dave, it sounded like you, I I sent you one that I did for biology.

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Did you have thoughts on the critique of that one?

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[Dave Sovic] Yeah.

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And and just to follow up on the last comment there,

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I would say also important right now, because there isn’t very specific or

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defined policy around how we should go about citing AI at OSU,

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talking to the students about, you know, this is how we’re using it in this course

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and we’re trying to be ethical in it, in it’s in our use of these tools.

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You may hear other things in other courses.

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And that’s why I want to be very clear in this course.

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This is how we’re looking to cite.

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This is how we’re, we’re using these tools in this course.

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And just to clarify that for students, because it’s very likely they’re going to

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experience vastly different uses in different courses at this point in time.

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And as it continues to evolve and develop and and grow,

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that will likely change as well.

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So just being as transparent as we can with expectations and use in our,

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in our courses, I think is really important.

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[Larry Hurtubise] Can I, can I interject just for a second?

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So on the page that we created for the session,

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there’s a link to a teaching and learning Resource Center on transparent strategies.

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And so, so it has some information, but also information about being

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transparent and using AI. I

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just wanted to show that.

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Go ahead, Dave.

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[Dave Sovic] Absolutely.

25:11
Thanks for sharing that, Larry.

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I would say for the biology example, it was prompted for an introductory

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course to generate some learning goals and and outcomes for that course to

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structure it.

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And I think what I would find really useful is the starting point aspect of

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this, that I’m not starting entirely from a

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blank slate, very similar to if I had another course

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that was already produced right now, this is one that maybe there isn’t,

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maybe I’m an, I’m an instructor and I’ve got a course

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idea and I don’t have anything from a colleague.

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And so I can prompt for this initial idea, right initial framework,

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initial structure.

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But I can see based on my own disciplinary expertise, pieces missing.

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For a specific example, in the one that was produced,

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you talked about the first learning goal was around key characteristics of cells

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and living systems.

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And one of the first outcomes was about eukaryotic cells.

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And the first thing that jumped to mind for me was, wait a minute,

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what about prokaryotic cells?

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What about prokaryotic systems?

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What about these?

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And it it hadn’t addressed that.

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So it was taking introductory materials for students,

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but it was also missing a lot that someone with disciplinary expertise might

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automatically recognize.

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And so I think again, nice starting point.

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And then I could continue to prompt and re prompt to say this is a good start.

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You know, can we can you introduce some learning

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outcomes around prokaryotic systems within learning goal one?

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So I think it’s a great way, a great place to start,

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but requires that disciplinary expertise can’t just simply rely on those outputs.

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And if you’re prompting something like you said, Larry, sports management,

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I don’t have expertise here to rely on that output.

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It may look great, but for someone in the discipline,

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they may see some glaring omissions or gaps that might need to be addressed.

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[Larry Hurtubise] And so, so when I think of that SPARC model,

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sort of what you’re bringing up, Dave, is you have to know the literature,

27:28
you have to know the standards, you have to know the pedagogy.

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You have to have done that work of reflection on, you know what,

27:38
what’s most important to you to be able to.

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[Dave Sovic] And that really, I mean, I hadn’t thought about this,

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but as you’re mentioning that, then putting yourself in,

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in the place of your students, because they haven’t done it,

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they don’t know it, they’re just learning it.

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And if they’re relying on AI to generate ideas for themselves,

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we need them to give that, them that awareness that, you know,

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it’s not perfect. It’s, it’s not going to provide everything that

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they need, but it is a great starting point.

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And then they can start to access literature and look for those, those gaps.

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And we can even use that as an exercise for the students in our course design,

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right?

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So I think there are a lot of opportunities there,

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but all interesting and, and all lead to more questions and ways

28:25
to think about it.

28:29
And Detra, I know you’ve done some work on some

28:33
assignments.

28:34
Do you want to share a little bit about your experiences?

28:39
[Detra Price] Yeah, I’ll just take a minute to say it was

28:41
really fun to work with the students and to think about some of the the prompting

28:45
that they could do.

28:47
I used the basic prompt model like the TRACI but then I also introduced a flip

28:53
model where they have to ask questions or they have to position ChatGPT or sorry

28:59
Copilot to ask questions for them to end up producing something.

29:05
So it might be I’m an eighth grade teacher in a middle school who is

29:09
struggling with students using social media during class time.

29:14
Asked me a set of questions to create a policy for my class and so Copilot,

29:19
any GPT, we could ask a series of questions and as

29:22
the students answer the question at the end,

29:25
it generates a policy and so then after that the students were then to go and and

29:30
critique and, you know, reflect on what the policy is and then

29:35
what would they re-prompt?

29:36
How would they do that?

29:37
So we created an audit trail based on the policies that were generated and then

29:42
just one for fun.

29:43
I don’t know how many of you are on TikTok,

29:45
but a while ago there was this whole sort of set of videos coming out around

29:50
Disney-fi my life, Disney-fi something.

29:53
And so I asked them to Disney-fi an article and to use those images to create

29:59
a really brief digital story about the important takeaways from the article.

30:05
And so those are really fun for the students to generate Disney like images

30:09
based on key ideas from the article that they read.

30:12
And there were lots of hallucinations in the articles.

30:15
Like I forget there was one with Pluto or Mickey that had a human foot.

30:18
So there was there are interesting things that the students start to see with the

30:22
images and with the written text that do what Dave just said.

30:26
It makes it so obvious that it you can’t rely on it to give you accurate

30:29
information all the time and you have to have a critical eye.

30:33
So we had really great conversations around that.

30:38
[Larry Hurtubise] You’re reminding me of a couple things.

30:40
One is that there is a instructor again in the health professions who wanted AI

30:48
to adopt, be adopt the role of the patient.

30:54
And it was a patient who wanted like an antibiotic for the flu.

30:59
And so then the student adopted the role as the physician and talked with Copilot

31:08
and was able to hold that conversation.

31:13
I don’t know how great it did, but it it could also be

31:21
it could also be a, I’m thinking like a parent teacher

31:27
conference.

31:28
Like you might have some sample questions that a parent might ask,

31:32
or you could practice those.

31:35
And theoretically you could have that whole exchange be posted to Carmen or to

31:42
a discussion board and have other learners critique it.

31:48
So other examples folks wanted to share maybe assignments they’ve tried or

31:55
questions they have about assignments.

32:15
So I will say if you get a chance, go ahead and look at the resources page.

32:23
There’s a couple, I won’t go back to that real quick.

32:29
There’s a couple of just highlights.

32:32
So these are the Ohio State resources.

32:35
So these are the Teaching Learning Resource Center articles.

32:41
And so I think these folks have found these to be valuable.

32:45
And then here’s some other links around AI you probably are aware of.

32:51
And then this Ithaka S + R is a AI product tracker.

32:59
So it basically will tell you how the the purchasing model, the description,

33:05
the key features, pros and cons.

33:08
So this is a nice way to kind of keep up to date.

33:11
Again, we are using Copilot here at Ohio State,

33:15
but this can give you information about what’s going on with Copilot as well as

33:22
Copilot 365, which is the different Microsoft ones to

33:27
call everything Copilot.

33:29
So, so 365 is embedded in like PowerPoint, Word, Excel and so,

33:37
so this is a nice way to sort of keep up to date.

33:45
And then this, let’s see, where is it learning with where is it

33:53
from Maine?

34:01
Well, I intended to put it on there.

34:05
I will add it.

34:07
But there’s a, a site with the University of Maine

34:11
that’s

34:11
Oh, here it is.

34:16
And so this site just gives a lot of really nice examples of different things

34:21
that you might do with AI and things that you might try.

34:25
So if you’re interested in setting AI guidelines.

34:28
You can go to this page and it will give you examples of what to say in each of

34:34
those things.

34:37
So that’s an example of what you might expect from the the Learn with AI page.

34:43
With that, I’m saying we have a a few minutes left,

34:47
but I will just open it up to questions or comments.

34:53
[Larry Hurtubise] I see Casey is posted a like a final e-mail chat list.

35:05
[Casey Rinehart] Yeah.

35:06
I just wanted to get that in there in case anyone had to head out at noon.

35:08
But thank you again, Larry and and David for fantastic

35:13
presentation.

35:14
I would just really helpful, incredibly helpful and the resources that

35:18
you provided, we’ll make sure to include those in our

35:21
follow up e-mail to everyone who registered today.

35:24
And again, if you haven’t already, please join us for join us in the AI

35:28
community.

35:29
So we have sessions like this ongoing and we have in our teams, we share resources,

35:34
information, updates, and just kind of general conversation and

35:39
community around AI for in EHE.

35:42
This is the last session for our AI workshops for the semester,

35:46
but we will continue our workshops and resources.

35:50
We’ll probably have some communication come to you over the summer and we’ll

35:53
continue those workshops starting in the fall.

35:56
If you have ideas or or suggestions or things you’d like to see us do,

36:00
please feel free to reach out.

36:02
But thank you again for attending and thank you, Larry and David.

36:06
It was absolutely fantastic for us.

36:09
Appreciate it.

36:09
[Larry Hurtubise] Thanks for inviting us.

36:11
I will say one little piece of learning that I got recently was doing sessions

36:16
like this.

36:17
Use the PDF version of your presentation so you can seamlessly go between Copilot

36:23
the web page the you’re not getting in and out of PowerPoint.

36:27
So that dip helps anyone and there you go free of charge.

36:31
[Casey Rinehart] That’s great advice.

36:32
Thank you.

36:35
Thanks everyone.

36:36
Enjoy this lovely day.

36:38
[Detra Price] Thanks everybody.

36:39
Thanks Larry and Dave. [Larry Hurtubise] You’re welcome.