Inspiration

We aim to tackle the issues that students face when returning back to in-person classes. One of the biggest issues we've noticed is how students often struggle to manage their study hours when it comes to their college courses.

What it does

The tool we’ve developed allows students to determine if a course is manageable. The program takes into account how previous students of the course have performed using public course data and calculates the course’s average grade. We take into account the letter grade the student is aiming towards and their expected dedication in terms of the number of hours they can afford to spend studying per week. We then provide the appropriate feedback based on those 3 factors and provide the number of hours they can expect to study per week in order to meet their grade requirement.

How we built it

The program was built in python, utilizing the PyWebIO web framework along with imported libraries including flask, pandas, matplotlib, and seaborn.

Challenges we ran into

One of the biggest challenges we faced included developing a proper algorithm to handle the various different cases between class averages and the goals the student was aiming for. We had to develop an algorithm that could adequately incorporate subsequent increases in grade level and map them to the predicted number of study hours.

Another challenge we faced was deciding on a tech stack that was best for us as a team. Our team was composed of individuals with different programming backgrounds, hence we chose to stick with a web-framework that could be coded in just python.

Accomplishments that we're proud of

We’re proud to have a functioning tool that can adequately predict how you’d fare in a course depending on the amount of time you’re willing to put in. We hope it can provide students with a better way to choose the classes that are right for them at the right time and not just because it’s required.

What we learned

We learned how to collaborate with team members despite having different backgrounds. We learned how to distribute our work into different categories that include more than just the coding aspect. We also learned new technologies that one of our team-members may have known, while others may have not.

What's next for Study_Time

The next step of the project would be to implement a system that notifies students when they fall behind on recommended study hours. This system could also be used to notify students of upcoming exams based on the students inputs and recommend the hours needed to prepare for the exam.

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