 Students will come to this hackathon and come up with ideas, form teams and hopefully build some product that they can take away that will help themselves or other students. I came to the hackathon because I wanted to explore the tools that are being used in the data industry. I think the very radical ideas are really what attract, you know, those are what attract me to like group dynamics. Yeah, you get to bounce off ideas and that's really awesome. So students are learning a ton of things at this hackathon. Pandas. Git, GitHub. Jupyter. JavaScript, JSON. Python. Matplotlib and the Canvas API. So they're getting exposure to a variety of tools that people and industry are already using. And this is very hands-on so they're taking real data that they've generated in Canvas. They're actually really coming up with really interesting stuff. My project is about recommending courses. We are building a function to predict who is your future friend for the first year student. My project is about sentiment analysis and the relevancy to certain discussion topics. So learning analytics is, you know, is an emerging field. It's an interdisciplinary field where it brings people from computer science, from education, from psychology, statistics. It's an effort to understand and enhance students' learning by collecting and analyzing data. One thing I think that is really important about learning analytics hackathons is the transparency. So we really want the learning analytics to be a community process. We want people to understand what the data is inside of systems. So after the hackathon, I want students to be able to think about their own data that's sitting in Canvas and do something with it.