 Welcome everyone to our session with Blackboard and Hypothesis, Leveraging Hypothesis Social Annotation in the Age of AI. So today, we're going to be talking about different ways you can use Hypothesis Social Annotation either in conjunction with AI or maybe to discourage your students from using AI in your courses. So the agenda for today, I want to start out by just first explaining what Hypothesis Social Annotation is. So I recognize that not everybody who's joining us today might be familiar with Hypothesis. So I'll just do a quick five minute intro to show you what Hypothesis allows you to do in your Blackboard course. And then I will hand it over to our guest today, Robin Bell, who will talk about the need for AI literacy and how she is facing AI literacy with Hypothesis in her own courses. And then we'll wrap up with some ideas from my end on how you can start using Hypothesis to approach AI with your students. So today, it's going to be me and Robin speaking with you. My name is Christy Carolus. I'm a customer success manager here at Hypothesis and I'm an instructional designer. I've been supporting faculty with using educational technology for about a decade. And I also use Hypothesis in my own courses that I adjunct. Robin Bell is joining us from South Texas College where she teaches English. So she'll be giving us the rundown on how she's been approaching the use of AI and her courses with Hypothesis. So like I said, I first want to kind of set the foundation, set the stage here for what it looks like to annotate with Hypothesis for those of you who might not be familiar with the tool. So I'm going to hop over into my Blackboard course. So I'm in my Blackboard learn a original course and I have a document loaded into that course. And I'm going to open this document on my screen. And basically what Hypothesis is allowing me to do is open this document from my Blackboard course and it overlays the sidebar on the right hand side of my my document within the course. So you can see throughout the sidebar that there are some conversations happening and I want to highlight a couple of things that are going on. So if I'm looking over into the distance over here, it's because this is where I have my course on my monitor. So here, you might notice that we have different pieces of highlighted text on the screen. So if I hover over text in an annotation on the right hand side, you'll see that text changes color on the left hand side so I can see exactly what portion of text a student has annotated. So Enrique has asked a question about the course learning goals in my syllabus. Later on, I have annotated one of the course learning goals itself. And then again, there's an annotation about the online format and the schedule. So each annotation is anchored to a very specific piece of text, whether that is a word, a phrase, a sentence, you can choose exactly what you're going to comment on with Hypothesis. And we're calling it social annotation because the default setting here is that everyone can see everyone else's annotations. So when you see on some of these annotations, the option to show replies. When I click on that option to show replies, it expands almost like a threaded discussion. So here me and Enrique are having a conversation about a course learning goal. And then further on, Jamie and Enrique are having a separate conversation about a different tool that's being used in the course. So we can have almost these simultaneous conversations over a text using Hypothesis that I directly opened from my Blackboard course. So Hypothesis allows us to have these simultaneous conversations and have students actively read and comment on the text as they're reading the text. So if I wanted to add a comment here, I could simply select the text that I want to annotate, click the annotate button, and then I can add an annotation here. And post that and everyone in the course can see what I have annotated. So that's kind of the basic rundown of what Hypothesis social annotation lets us do in Blackboard. A little bit later on in the session, I will talk about some of the details of how that integration works with Blackboard. But first I want to talk about why you might even want to be considering using Hypothesis social annotation in your course with these new generative AI tools that have been popping up. So why is there even a need for AI literacy and how do we approach it with our students? And this is where I'm going to turn things over to Robin to tell us a little bit about how she's approaching AI literacy and how she's using Hypothesis social annotation in her courses. So Robin, do you want to talk a little bit about your slide here? Yes, I will. And I actually think it's really important to talk about this because this slide here represents the very first step that I take with students before we even really talk about or do anything meaningful with regard to AI. And so I did start last semester kind of in an experimental sort of phase where I think that AI was more like the elephant in the room. It was something that we all knew about. Many of us were maybe starting to experiment with it and consider how we were going to navigate that, whether we were going to allow it, whether we were going to try to use it as a tool. And I think after I used it for a small amount of time, I already saw the vision and the possibility. And I know that just a moment ago Christy brought up the fact that the things that are going to be addressed here are how and why we might even want to be even talking about AI literacy or how we might want to use it in our courses. But I know that some people may have a completely different philosophy than I do and that's certainly valid too. But I think the way that I see it, I feel like it's very important for students to, for me to build buy-in for students and to make an appeal to them that's related to academic integrity, but not, you know, honesty for honesty's sake in the abstract, but more in a practical kind of way where students can see what's in it from their vantage point in terms of learning how to use AI ethically, responsibly, and effectively to improve their workflows and foster real learning and boost their creativity. And I start out by telling them, and last semester when we started this, I didn't have this slide here, but I do have this slide now. And it's one of the first things that I show students to kind of make this appeal. I tell them that if AI can outright do your job, or if it can outright do your homework, what useful you be to your future employer. And my philosophy is that I need to get them to buy into the value and the integrity of their degree. And if they're doing things to circumvent real learning, then they're devaluing the worth of their degree. They may very well have that piece of paper at the end of four years, but it won't mean much if they can't do what the degree claims they can do. And kind of I think the prevailing internet wisdom is that AI won't take your job, someone who knows how to use it will. And this has kind of informed my philosophy and my decision to try to use and incorporate AI as a tool, not as a focus, not as something to ever do our work for us, but something that we can work into our workflows to improve them and evaluate them and learn how to use it better so that we can be more productive. And one of the things that I like to emphasize with students is this notion of us being the pilot and AI being the co-pilot. And that's kind of a riff off the language that Microsoft uses and GitHub and, you know, the links on this slide actually go out to those places and I do talk to students about that. And neither of those platforms are intended to replace the humans that use them, but they were designed, you know, with the mindset of making our workflows more productive. But it's important that we are the human in the loop and that we are and that we remember that it's humans that are behind AI. It's humans that are in front of AI using it. And I think we have a real opportunity as educators to have something to say about, you know, how and what happens not only in our classrooms, but to give students things to think about in terms of how will AI impact their future career, their workflows, their own education, and maybe even more importantly the education of their children. And I will say before I jump in a moment to share with you the some of the assignments that I have created is that when I beta tested this last semester, I did it very slowly and very deliberately and I created transparent workflows and a culture of kind of trust and collaboration. And I must say that it was really inspiring and that the students validated my, for the most part, they validated my positive assumptions about them. And they were absolutely vital in helping me kind of transform what we were able to do with three specific assignments last semester and the vision and the execution of what I have in mind for this one. So I would like to maybe jump from this to Christy, can we, is it okay for me to share my screen. Sure, so I'm going to stop screen sharing so Robin can show you all a little bit more about the assignment she's used with AI and hypothesis. Okay. Okay, there we go. Okay, so this is a little Google site that I created to kind of house some of these things that I think it'll be more convenient for me to show them to you this way. So what I have here is an overview of an AI hypothesis assignment that I hope students find to be wildly fascinating and to serve as something that opens up bigger conversations that have more relevance to their majors their degree plans their future careers and so on. So the name of the assignment is called art in the age of AI annotating the intersection of creativity, technology, and it's broader implications. So in a nutshell and in a moment I'll show you what it actually looks like, but it's a very easy assignment it's high interest, and I chose the subject of art, because I think art is for one thing it's uniquely human I think it's something that we associate, primarily or maybe exclusively with humans, the notion of being create creative. And if you look up the definition of art in the dictionary, it will speak to the fact that it is, you know, it is something created by humans. And I do think with the advent of the AI generated art platforms like mid journey and Dolly, and, and others that, you know, we have a new tool that can be used by artists and people who may don't maybe don't have an art background and I think art is something that resonates with just about everybody. What we have over here is I have, you know, kind of the PDF document here that I could make full screen but I think I'm going to leave it this size for now. But I always start when I have an assignment for students, I give them an assignment overview. And so this gives a summary and an upshot of the assignment which I'm just going to tell you about here. So this involves two steps, two layers, if you will. And the first step is that students are going to annotate an actual chat GPT thread containing a conversation between me and chat GPT for on the subject of art. AI art, all the, and all the things that that might encompass. So it's a pretty broad conversation that goes in a lot of different directions. And this becomes the, the first text in this little mini AI unit that I have that is currently sitting outside of the other units. So this is something that we kind of have on the back burner. And this will serve this is my introduction to the class about AI and why we're using it and establishing a rationale. And I hope that this assignment helps me do that. So that moving forward, I can my lessons regarding AI will be course specific to to my course. So in the first step, they're going to actually annotate that thread. And they're going to annotate it up to a certain point. And let me just scroll down for a moment. I'm going to show you the actual GPT thread. That I have embedded here. So one of the things that I love about Blackboard Ultra is the ability to embed content. And so you can create pages that are very much like the one that you see here. They're almost like a mini webpage, if you will, you can embed content, you can embed all kinds of things. And I love the fact that I figured out last way last semester, a way for us to annotate this thread and now it's even easier, because all of the platforms being AI they all have a way to annotate the text that you can generate there natively from, you know, clicking at share link right inside. So this is the actual chat GPT thread. And part one, they're going to annotate this according to the directions that I have for this and I'll bounce back to that in just a moment. It's a pretty lengthy little conversation. I hope it asks some interesting questions. But the more we iterated the less formula it became, it became, and the more it became a more organic kind of conversation. And the idea is that students are going to annotate this up to a point. And then there's a part, when I get to part two, down here, let me see I'm looking for a part two. And it should be coming here we go part two. So I actually use part part two or I use chat GPT to help me create almost like a custom made hypothesis text. So up to this point, it's the conversation. And then at this point, students are going to take a pause. And I'm going to give them two weeks to play on some AI art generators that I'm going to show them how to use. So by this point, I will have already showed them some images in mid journey, which I use quite a bit. I use it in my courses for almost all of the images that I create and almost all of the images on this Google site are also from mid journey. But I'm going to show them how to use AI art from some free platforms and give them a couple of weeks to play on that before we really dig in and talk about the ethical concerns, the issues, the controversies, the use cases, and kind of get into all of those kinds of things. So they're going to annotate this pause. And then I've created some anchor points and I actually gave chat GPT this instruction, and I said, Hey, I want students to have some anchor points below because this is going to be in a hypothesis assignment. And they're going to anchor some of their AI art here and then they're going to discuss that experience and they're going to look at some of the questions that I have that follow and wrap up this chat GPT thread before we move on to the next. Part. And so then at the end, I have some kind of culminating questions that I want students to look at and explore. They don't have to answer all of them. But they do have to answer some and then obviously they're going to have to go in and reply and engage with their with their classmates. And I do typically the reason why I have eight anchor points up here for the AI art is because for all of the hypothesis assignments that I create. I tend to put students in groups of eight. I have, you know, relatively small classes. 22 to 24. So the groups never exceed eight. And so I wanted eight anchor spots so that students can do this. So my thought here was is that I can give students some hands on experience with a real AI tool and do it in a way that they might find to be fun or interesting in some way. And then we're going to talk about the ethics and the implications of that on a broader scale. So let me go down here to the bottom so I have some more handouts here. One of which is a guide to exploring AI art so I do need to show them how to how to do that so when they do that pause if they're in a face to face class I will have gone over this in class if they're in an online class I have instruction in the course plus I have a handout showing them how to get started with the being AI image creator. For example, this is free and you get 100 free credits a month for fast image generation. And then thereafter if you run out of that you can still generate images but it may just slow down a little bit. So it's totally free and it's pretty good. And I think it's fun for the students to play on. Our school also provides us with an LMS version of Padlet, but this could also be accomplished with a free version of Padlet. They have an I can't draw feature which is powered by AI. And so you can create free art there as much as you want for no outlay at all. And based on the image here I'm pretty sure this runs on an older version of Dolly. So all they have to do here is create a Padlet, click on the I can't draw and they put some descriptors of what it is they want to try to draw or paint or create an image of, and it will even create, you know, kind of photographic images of people as well. And then I have an example here. You can see that here I said, you know, to draw do Hogwarts painted in the style of Henry Rousseau. And that is a painter that I learned about and I would say, you know, that's, you know, a pretty fair representation of, of his style. And so it's just kind of look a little handout showing them how to do it, and telling them that, you know, this is supposed to be fun don't stress about it nobody's going to be, you know, upset if you don't create a masterpiece. And in fact, I actually want them to kind of see that I want them to see that sometimes you can create something that is quite beautiful. Sometimes you can create something that's weird. Things that, you know, are there are anomalies in the images. And I want them to see the good and the bad in terms of the output in the generative AI art images. Now, once they get done with, with that, the second part of this there's another hypothesis assignment that's really the second part of this. So the first part again is the chat GPT thread up to the part where they pause play on the art generators, then they come back and kind of culminate that start thinking about the bigger implications of that. And then what we have here is a two page article on art and the science of generative AI. And what I really like about this are two things. Number one, it's short. And number two, it contains a claim that kind of inspired this whole assignment. It makes the claim that if we, if we can talk about the impact and the implication and the use cases of AI in one domain, such as art, because art is something that most people can identify with and can relate to in some way. If we can do it in that one domain, it can be a good gateway for you to open those conversations in other disciplines or other areas or domains of life. So this is part two, and part two does require some lateral reading. So it requires them to do outside research and they would have to include that in part of their, their annotations. If I bounce back up here to the instructions, you know, in the beginning I pointed out that, you know, there's an overview here, and it also explains the two layers so they can kind of see in an upshot. What it is that we're doing, they see the simple little rubric that I have in terms of, you know, how this is going to be graded parts one and parts two of the chat GPT thread. And then part two, the annotation of the little article and there's a little summary there. I think or at least I hope that that is useful. For each part of the assignment I have very specific instructions and sample posts. So in this one annotating a chat GPT thread on AI art, it's very step by step with screenshots showing them, you know, where to post that they need to post to their group. And then I have, these are my, these are my tag types. I do require students to tag all of their annotations because I have very specific objectives for each thing that I have them read. They may not change from reading to reading but if it's something super specific or I have some kind of alternative objective and that will be reflected in the tag types. And for some things I give them a range, you know, I might say 8 to 10 annotations, sometimes I give them a hard number, and I'll tell them that you need at least so many of each kind and so many replies. And then I do try to provide examples for every single, you know, thing that they could come up with. In terms of the different tag types. And let me see if I can, and here at the bottom so here's what I want them to do on those anchor points. This is where I would have them share their artwork on those anchor posts and then talk about those culminating questions. And I've also included instruction for them on the other handout that you may remember from just a moment ago on how to play with the AI art generators. One of the things that I'm going to encourage them to do but it won't be required is to create an AI art gallery on Padlet. So no matter where they happen to create that AI art, whether it's, you know, in the free AI art generators that I recommend to them, or whether they are choosing to try, you know, other ones, they can house those on that Padlet. And I've encouraged them to, you know, post a picture like the one that you see here to the anchor, but then include a link to your AI art gallery. And so my hope is that that will encourage them to do that to create more kind of have some fun doing that and share the results with with their classmates. And so this is an example of, you know, an image created on, you know, the Padlet AI, you know, art generator and then I have a link to kind of a little mini gallery that, you know, I just put together and all of those images were created on the Padlet, but you could, you know, bring in links from, you know, mid journey or, you know, any other art platform that students are of a mind to try and you can do the same thing with being AI and they can just kind of collect those, you know, all together. So, if I scroll down just a bit more, this will show you what it looks like in hypothesis. So this is actually what it looks like inside one of my Blackboard offer classes, but I did drag these to the top of the screen so that we could just see that this is what the links look like and this is what students would see. I do put a description underneath kind of telling them, hey, this is part one, this is part two, and I will often put, you know, if it's a two part assignment, I will generally put, you know, the due dates there just so they can kind of see them out in the open. And just like Christie showed us a moment ago, this is what it looks like in Blackboard Ultra, you can see the actual chat GPT thread there and this is me just as a model for students annotating, you know, out to the side and also trying to model and show them that they can include multimedia when it's relevant to do so. They can include images when it's relevant to do so. They can include articles. So I even have a link to an article here, which isn't, it's kind of an encouragement on the chat GPT thread, but it is a requirement on the article. And then one of the reasons why I really like this assignment is I do think that it is adaptable to just about any discipline. I do know that English teachers can get away with a lot in terms of borrowing from other disciplines in terms of things to write about or read about or talk about. So I do think that even other disciplines, even if you didn't use this assignment as is, it's a good gateway. It's a good attention getter. It's a good conversation starter. And even if you use the little two page article, it's a good gateway into opening the door to explore and to discuss AI in meaningful ways as it applies to your discipline and as it applies to the disciplines that the students are choosing to study. So I'm really excited about this. I have just opened this in my classes. This is something that I have not, it's brand new. So this is still in, this is my first iteration of it. So I'm really excited to see what students are going to come up with. And this is my kind of more structured introduction to what then what I did last semester and I have deliberate lessons that are also presented in class and in the online environment. And then the last thing that I want to, you know, just kind of briefly share before, you know, turning this back over to Christie is, you know, other use cases. So I do have, you know, kind of just a little blurb here about how valuable now this I did do quite a bit last semester to the extent that I could in the last third of the class, and that's teaching AI literacy as it applies to my course. I created a lot of chat GPT threads that we looked at and analyzed and evaluated in class showing the limitations of AI showing the capabilities of it and showing how it really is a skill in terms of learning how to use it and use it effectively. And I also had and required students to use AI in very specific workflows as part of some of our assignments, and they had to turn in their chat GPT threads to me in the assignment link. They had to post them to a padlet that I created for that purpose. And we did reflective writing on anything that we did with regard to AI. So we weren't just using it to use it. We were also reflecting on it. And in some cases we compared the outputs that we got there to other human inputs. And it was a really a good experience overall. And, you know, that was kind of my my first draft iteration of it. So what I'm doing this second semester is kind of a second draft iteration. It's bigger. It's I think it's better. It's more deliberate from the beginning. And it's probably going to take me another semester or two to get it, you know, to really get it right. But I'm kind of excited about, you know, the possibilities here. So that's kind of in a nutshell of what I have to share, you know, with you today. Christy, I guess I'll go ahead and turn that over. Turn it back to you. So, thanks so much, Robin. And taking that deep dive with us on how you're using hypothesis and AI in your course. I think it's super interesting the journey that you're taking with your students and the level in which you're having them. Not only use AI, but kind of critically look at what AI is generating and what it means for them and the future in general. So I did put for anyone that is interested the link to the Google site that Robin was showing us into the chat. So if you want to access her assignment instructions, you can see them in the Google site. I am going to spend a little bit of time talking about some other ways you might think about using AI with hypothesis in your Blackboard course or approaching AI with hypothesis in your Blackboard course. So maybe you're thinking, wow, Robin has done a whole lot in her class with these assignments. So she's really did like, you know, gone into the deep end and really bought in with making sure she's approaching AI with her students. I have some ideas for if you want to try and like dip your toes into the water a little bit first, how you might do so with hypothesis in Blackboard. First, I want to go through a couple of key details about how hypothesis works in blackboard for schools that are hypothesis subscribers. So if you are a hypothesis subscriber, you do have hypothesis available in your Blackboard course already, and I'll show you where you can find it in Blackboard. It basically allows you to create any document you have loaded into your Blackboard course annotatable. The students and yourself do not have to create logins or leaves a Blackboard course site. You're annotating the documents within Blackboard itself. So your Blackboard course documents are becoming annotatable with hypothesis without leaving the site or having that extra barrier of creating an account. You also can grade annotations in Blackboard. So I know Robin did kind of briefly show the rubric that she's using with her annotations and her assignments. If I hop over back to my annotation assignment I was demonstrating before you may have noticed the top there's this grading bar at the top of my document. If you're an instructor and of course and you've enabled grading on your assignment only you'll see this and I can select a student to grade and it will filter only that students annotations within Blackboard. And I can grade that student and that grade will be sent to the Blackboard grade center. So it's really easy to give students credit for their annotations and look at just one student annotations at a time. Robin also mentioned this feature as she was discussing the way she sets up her assignments. So in the beginning I noted that the default setting with hypothesis in Blackboard is that everyone can see each other's annotations in the class. So everyone's annotating together. But hypothesis does integrate with group sets in Blackboard. So if you do want students to annotate in smaller groups that you have a really large class. And it just doesn't make sense for 100 students to be annotating together, or maybe you're in a situation like Robin then you just want to have eight students annotating together. You can set up your group sets in Blackboard and hypothesis will automatically set up a separate annotation space for each of those groups. So there are lots of flexible ways that you can set up your hypothesis enabled readings in Blackboard. So now that we know a couple of the details of how it's integrated into Blackboard, I want to talk about some of the ways we can approach using hypothesis with AI in mind in our courses. Hypothesis makes our Blackboard readings more active, visible and social. It makes their readings more active because it's asking students to engage in metacognition as they read. So I think it was really powerful that Robin mentioned, you know, like if you're not putting the work into learning, you're not going to get anything out of it, right? You putting hypothesis annotations on an assignment is asking a student to reflect on that reading to think about what do I not understand about this? How is this connected to what I might have learned before? How is this connected to what we've done in this course or in my other courses or my own life experiences? So having students annotate is asking them to actively engage in that reading instead of just being kind of a passive participant in the course. It makes reading visible for us as instructors because we can see where students are having those connections, where they have questions and how exactly they're connecting to the reading. And it makes reading social because, like I said, the default is everyone's annotating together or everyone is annotating in smaller groups. So students can learn from one another. And this is in my own experiences. Whether my students are annotating about AI or not, they tell me that they like using hypothesis because seeing their classmates interpretations of the text help them better understand and comprehend the concepts that are being displayed in the text. So how do I think social annotation can help in the wake of these generative AI tools? And this is for everybody. So whether or not you're using AI or having your students use or examine AI in your course, I think just using hypothesis along with your readings in your blackboard course can help. And it's for the three reasons I have on this slide. Consistently using hypothesis social annotation helps emphasize the process of learning over the final product. So why we have to think about why are students going to be turning to generative AI tools in the first place? They might be turning to a chat GPT or Bard or one of the tools out there because they're feeling pressure. They have a big paper coming up. They have something that is a large portion of their grade, something that they feel like they can't fail at. And they're feeling the pressure of that grade and the need to do well on that assignment. Incorporating hypothesis social annotation throughout the semester as formative assessment emphasizes this process of learning before we get to that final product. Because we have to be honest. Learning is not always about being right. We can't always be right about things we don't know yet, right? We might fail and we can practice that art of failing when using hypothesis. Students can learn to explore and critically think about the text and do it in a way where it's okay if they're not 100% correct. So we bring in that value of the learning process by consistently using a social annotation assignments. And that can help take some of that pressure away from those large summative assessments. It also encourages continued engagement with the course materials throughout the semester. So another reason students might turn to generative AI tools when they're reaching their final assignments is because they didn't do the reading. As the students progress through the semester, life, the demands of life come at them, right? They have jobs. They have four or five other courses that they have to think of. They have family obligations and their exams and their papers and all these things that they have to be held account for are taking precedent. And oftentimes they stop doing the reading, maybe unintentionally just because they run out of time. But asking them to engage with the readings with hypothesis ensures that they're going to keep engaging with the readings through the semester. We actually have a case study on our website with UT Austin showing that using hypothesis does increase student engagement with the course readings throughout the semester. That means that by the time they're getting to those summative assessments, they might not need to turn to generative AI because they've been keeping up with the reading. And that's, again, more anecdotal feedback from my students as they like being held accountable for doing the reading. They like the way that it kind of forces them to check in and keep up with that material. And finally, using hypothesis social annotation cultivates the student voice. So having students annotate in kind of a more informal way throughout the semester on your course readings help you as the instructor better understand what that student's writing style sounds like. So you can kind of get a sense of what that student naturally sounds like when they're writing, when they're turning in summative assessments, you can like think about is this what they kind of sounded like throughout the semester. So I think consistently using social annotation throughout your readings through the semester just is a good foundational practice to encourage students to that not only value learning but keep up with the course materials throughout the term. So I know Robin went into like a deep dive of how she is using AI, lots of AI tools, chat, Upt, mid journey, Dolly, in her course, but whether what are some other ideas for using hypothesis and blackboard with generative AI in mind. So, if you don't want to use AI at all, I know there are some people who might be like AI is not for me. Then in that case, you might want to just use annotation as a formative assessment. So, like I kind of was just explaining, you can use hypothesis through with each of your readings throughout the semester and give students maybe, you know, low stakes formative assessment for that low stakes points for completing those assignments. So maybe they'll get some participation grades for completing their annotations throughout the semester. And that can also provide scaffolding for those larger assignments. You can pinpoint where students are struggling before they get to do those exams into those essays based on how they're annotating. You should also consider incorporating community annotations into your summative assessments. So, can the student annotations actually become course material that could be referenced or cited. Part of my favorite reason for using hypothesis is that it de-centers me as the authority with my students and my students become active scholars and active contributors to the course. So, I actually like to bring those contributions into summative assessments and have students cite each other's work, cite each other's annotations when they're creating projects or writing papers. Because that is something that Generative AI does not have access to, right? ChatGPT doesn't know what students are annotating in your courses. So if you can bring those things in, that can be a way to make sure that students are incorporating your original course materials into their work. And then similarly to what Robin has walked us through, you can have students critique AI generated text using social annotation. So your students themselves don't necessarily need to use ChatGPT or BARD or something to do an activity like this. You could simply put an essay prompt into ChatGPT and see what it comes out with. And have your students critique that essay through a number of different ways. And we have a number of starter assignments available on the slide, and you can take these instructions and use them in your own courses. So you can have students work as editors, for example, and critique ChatGPT's writing style and writing form. Did ChatGPT make a good argument? Did it provide good evidence for its argument? Was it missing things stylistically? What was its voice like? You could even have students compare ChatGPT written text to human written text using social annotation and look at what are the strengths and limitations of each. I think it's also important to have students fact check ChatGPT or other generative AI. So if it has created a text that you can have students annotate, have students really rip that text apart that ChatGPT or BARD or whatever has created and fact check every single fact that is in there. So we know generative AI sometimes tends to hallucinate. I don't know if students always realize the extent to which it can hallucinate. So having students fact check find citations for each of the facts in an article can be revealing for them on how they can or cannot depend on AI. You can also have students act as content experts. So I saw this a little bit with Robin's example with artwork. She had one of the art examples she gave. It was like having AI create art in the style of a specific artist. I forget which artist it was exactly, but you could have students do this with writing. So have a ChatGPT write a poem in a style of a specific poet and then have the students critique. Did a ChatGPT do this well? What is wrong about the style here? What is correct about the style here? So there are a lot of different ways that you can have students use annotation to critique generative AI's work. In addition, we have just general annotation starter assignments here. So these starter assignments are specific to AI. If you're not interested in using AI in your course and you just want to have students annotate documents, we have samples of instructions for students annotating documents here as well. Because I do think it is important to prompt your students, give them guidance for annotation. If they don't have that guidance, sometimes they're not sure how to contribute meaningfully to that conversation. So I want to use the last few minutes to show you how easy it is to get a hypothesis reading set up in Blackboard. At this point in time, hypothesis readings work best with open educational resources. So you can use PDFs with hypothesis, open textbooks and open educational resources like press books, open stacks, library texts are very common. You can use public facing web pages and online articles with hypothesis. We recently introduced the ability to annotate YouTube video transcripts as you watch a YouTube video with hypothesis. And you can also now at certain schools use hypothesis with JSTOR articles and vital source e-texts. Another thing that Robin kind of hinted at is that you're not limited to just annotating with text as well. There are lots of different things within an annotation that can make reading a more multimodal experience. So you can add images to annotations. So that's where students in Robin's assignment are annotating the text and then adding their own mid-journey images to their annotations. You can embed videos into annotations. You can use latex to add equations to annotations as well as adding external links and tags as well. So again, you can really make the reading a more multimodal experience by adding these different things which can enhance understanding of concepts by not just understanding them through text alone. So if I have a hypothesis available at my institution, in Blackboard Learn, I will find it in my content area. And it would be under my build content space. So you will find it and by scrolling down and finding hypothesis toward the end of the list of the build content space. And I'll click on hypothesis here. I can enter the name of my hypothesis assignment. And I always want to apply instructions for my students. So I am going to just kind of copy and paste some of our sample instructions here into my assignment. If I want to use a PDF, I'm actually going to ignore this attachments area here. This is not why I want to attach my document. I first want to set up my instructions and then I will add my document as a second step. If I want to enable grading, I can do so here and add a due date and submit. And I've created kind of a shell for my assignment at this point. Now if I scroll down, I can find the shell that I've created and click into that to see the different options I have for adding a resource to a hypothesis enabled reading. So I have, like I said, the option to add a URL using from a website, a YouTube video or a JSTOR article. I can also grab a PDF from Google Drive, OneDrive or Blackboard. In this example, I'm just going to grab a URL and throw that in here. And my hypothesis assignment is basically ready to go. So in Blackboard Learn Original, that is the setup process. If you have hypothesis available at your institution, if you're using Blackboard Learn Ultra, the process is not any more complex than that. It's just a different click path that you would be using. And we do have some instructions in the slide deck as well. So as we come to the end here, I want to review what comes with being a hypothesis partner. You do get pedagogical support from our customer success team. So the customer success team provides training for your school, one-on-one consultations for your faculty. You also have access to some of our resources, like our Hypothesis Educator Forum and our support team. Partnering with Hypothesis also gives you access to Hypothesis Academy. And Robin did take Hypothesis Academy over the summer and became a Hypothesis Certified Educator. There are two week courses designed to help you create your own annotation assignment. In a way that best supports your students' learning. So we have two topics that run throughout each semester, Social Annotation 101 and Social Annotation in the Age of AI, which works well for our current topic today. And you also will have access to our weekly partner workshops. So those of you who are not currently Hypothesis subscribers, if you are interested in learning more about gaining access to Hypothesis in Blackboard at your institution, we have a spring starter promotion going on right now. And you can reach out to the email on that slide to learn more about how that could work for your school and have someone reach out to you. And customers, if you need any assistance, please reach out to the customer success team so we can help you get started with Hypothesis. But we are rounding out in the last few minutes today and I want to thank everyone again for joining and see if anyone has any final questions for the day. I see Lee has your hand raised. Did you have a question, Lee? You should be able to talk if you have a question now. Anyone else you can also either raise your hand or put a question into the Q&A box. I'll share the link to the slide deck in the chat one more time to make sure everyone has access to that. Great. Well, it looks like everyone might be okay for the day. So thanks again for joining. Thank you to Robin for sharing her assignment and her approach for using AI with Hypothesis in her Blackboard courses. I really appreciate the time that you've all taken to attend at this busy time of year. I hope you all have a great start to the term and please reach out if there's anything we can do to help. Thanks so much, everyone.