Schedule Helper

Inspiration

When creating a schedule, numeric reviews sometimes aren't enough when effectively gauging what to expect from a certain professor. We wanted to simplify the process of making a perfect schedule by gathering more available data across the web.

What it does

Our course builder accesses UMD students' written reviews for their professors, from various rating websites, and condenses that information into an easy-to-use schedule guide that takes into account what students are saying about each professor.

How we built it

We create the algorithm to understand how "positive" a student's review is in python. From there, we were able to scrape data from the web and create a python-based web app using the Django framework to bring everything together.

Challenges we ran into

We had many issues to tackle when it came to scraping reviews off the web correctly, developing a working algorithm for gauging student responses, and finally visualizing that data on the web application. Eventually, we were able to pull through and overcome each challenge with some last-minute changes.

Accomplishments that we're proud of

We are extremely proud that our project was able to finally work in the end, and that the data it was reading was accurately being used to do what we initially intended it to.

What we learned

We learned a lot about the web development practice, including what resources are needed and how to put it all together. We especially learned all the many factors that come into constructing an ideal algorithm that takes into account efficiency, scalability, and also accuracy.

What's next for Schedule Helper

We definitely want to improve performance time, update the web application appearances, and add more functionality, especially adding more visual data, the ability to add/remove courses dynamically, and improving user navigation through the website.