Analysis on Student Behavior

As a science mentor for UTSA, part of the job is to create events for students that benefit them in different areas. This analysis is meant to help us understand the how to achieve a high turnout.

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Inspiration

My biggest inspiration in pursuing this project was my job as a Science Mentor at UTSA. One of our main focuses is making sure that students within the College of Science succeed, so we do this through mentorship and events. One of our biggest challenges is getting students to come to these events and benefit from the many resources offered to them. So, the biggest focus of this project is finding a way to understand our student behavior to increase the amount of people that go to these events.

What it does

Essentially what my project was initially going to be was an app for the science mentors to use to determine what day of the week and time they should throw their event at, based on event type. It is meant to be really simple to the user with only one functionality. As for the future predictions, that is meant to be determined by past event data that is fed through a time series forecasting algorithm (supervised machine learning).

How we built it

Although there is no app built yet, Google Colab (in python) was used to analyze the data. I used machine learning libraries such as sklearn and Prophet for the prediction model.

Challenges we ran into

The biggest challenge was obtaining a clean dataset. Initially, I wanted to use Tableau to visualize the data for me to fully understand my dataset, but unfortunately it was not working on my computer. After switching my idea to use Google Colab, my next biggest challenge was figuring out how to connect the different data points in a way that is meaningful/useful.

Accomplishments that we're proud of

I am very proud about taking on this challenge by myself. This is my first time actually competing in a hackathon and even though I started late on my project, I'm proud that I really utilized my time to continue to learn.

What we learned

I learned that planning is really important. When taking on a project, many many unexpected things can happen but having a plan to fall back on is key to success. I also learned that it's okay to "fail". Most of my peers ended with a project completely different from their initial plan, but we all learned a lot in the process; and I believe that's what is most important.

What's next for Analysis on Student Behavior

Next I am going to actually start building the app. I plan on consulting with professors to help me with my dataset and I'll move on from there

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