 Hi everyone, I'm Erin and I'm a customer success specialist with Hypothesis and today we're going to talk about how to assign a hypothesis enabled reading to small groups within your class. It's possible that you have one reading and you would like to have small groups of say four to five students or even less. Read the article together and then annotate such that only the annotations are seen by other members of that small group. We're going to walk through how to do that today. The first thing you'll need to do is make sure that your reading is available in a PDF form and that that PDF is on your device. So let's say in this case, I am going to use a reading about faculty stress during the pandemic. I want to make sure I've already saved that article to my device in this case my computer as a PDF, and I want to make sure that PDF already has an OCR or optical character recognition layer added to it. Now that I've done those things, I want to navigate over to this website here docdrop.org backslash fingerprinter. Once I'm there, I'm going to decide how many groups I will assign this reading to. I have a class of 20. I'd like to assign it to four small groups within my class. I'm also going to assign a suffix to this PDF such that I remember which group is supposed to get which reading I'm going to say group. Actually, I'm just going to say class group. Okay. Then here comes the point where I'm going to choose the PDF, going to make digital fingerprints up so that I can assign each digital fingerprint to a different group within my class. I'm now going to find the PDF on my device. I'm going to select open. And then I want to make sure to choose this button that says re fingerprint. I now have four different digital fingerprints of the same PDF. I can now assign each fingerprint to a different group within my LMS. If I have these four fingerprints, I can either download them individually to my device, or I can download them as a zip file to my device. I'm going to go back over to my LMS. In this case I am using Canvas. This also works if you're using say Blackboard, Moodle, D2L, Sakai, any of the other LMSs out there. Now I'm going to add an assignment. Now in Canvas we select assignment in Blackboard you may select content in Sakai, it's within lessons, really just depends on your LMS. I'm going to call this faculty pandemic stress group one. Now you're going to have to create one assignment separately for each group. It may be beneficial to name the assignment for the group you're assigning it to. So I'm going to call this group one. Scroll down make sure I choose external tool as my submission type. Choose hypothesis. And I'm going to look for my PDF on Google Drive. Now, it's of course we know the PDFs or the fingerprints that we downloaded don't live on Google Drive they live on our device, but we're going to use Google Drive to get to those documents. I'm going to choose upload. Now I can choose the file I would like to use. So I'm going to go into my device here, search the document. And because I know I'm assigning this one to group one, I want to make sure I choose the title that has that group one in it. I'm going to select open. Go ahead and load this tool in a new tab. This is the crucial part I want to assign it to the group that I'm interested, or that the group one that corresponds to this reading, and hit save or save and publish. I want to repeat that same process for each group in my course. If previously you maybe give one assignment assigned it to multiple groups all at once. That does not work with hypothesis, you'll have to create an individual assignment with the correct fingerprint for each group. If I go back to my assignments. I can see. The next assignment I have created for group one. The next assignment I create, I will title faculty pandemic stress group two, and I will use the digital fingerprint for group two that I downloaded to my device. If you have more questions, or you want one of us to walk you through the process we are always happy to do that. Send us an email to success at hypothesis.is.