Inspiration
My teammates and I, as senior-year students, faced the common challenge of needing to select classes for registration. Every time we had to choose a course, we would check the available professors and their reviews on RateMyProfessor and Reddit. This step became so routine that we realized it was a common issue for many students. So, we identified this gap and worked on a solution to streamline the process.
What it does
CourseSphere is a website that allows students to search for courses and get all the necessary information in one place. It provides details about the available professors, their reviews, difficulty ratings, and overall performance from platforms like RateMyProfessor and Reddit. Additionally, we added a community forum where students can exchange messages and comments about the course. A chatbot is also implemented to provide advice and course information, simplifying the decision-making process for students.
How we built it
We built the website using JavaScript, Express.js, and Node.js for the backend. We also used Python to automate real-time web scraping to gather data, and JsDelivr to host the JavaScript CDN for the chatbot functionality. The web scraping allows us to keep the information about professors and reviews updated dynamically.
Challenges we ran into
One of the biggest challenges we faced was handling highly unstructured data while scraping. Integrating and organizing this data to provide relevant and clean information was a major hurdle, but we overcame it by refining our scraping logic and implementing efficient data-cleaning algorithms.
Accomplishments that we’re proud of
We are proud of successfully integrating multiple data sources like RateMyProfessor and Reddit into one streamlined platform. Building a fully functional chatbot that gives personalized course recommendations and information was another major accomplishment. The ability to simplify a complex process into a user-friendly experience is something we take great pride in.
What we learned
Throughout the project, we learned the importance of handling unstructured data and the complexities involved in real-time web scraping. We also gained experience in building a chatbot and integrating it into a broader system. Most importantly, we learned how to solve a real-world problem by transforming a common student pain point into a practical solution.
What’s next for CourseSphere
The next steps for CourseSphere include expanding the platform beyond Arizona State University to other universities, implementing class tracking for students to monitor their coursework and grades, and improving the chatbot by using machine learning for more accurate recommendations. We also aim to enhance the community forum to make it a more interactive space for student collaboration.
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