Being a team with the power to navigate technology, and the vision of a budding economist, the team has a harmonious blend of humanities and STEM perspectives. Our inspiration was to create social stability in our community of college students through economics logic and the power of the machine. We decided to take a unique perspective on the presented stimulus and correlated it to not just the suggested area of aided learning, but also student loans. Being college students ourselves, we best understand the overbearing threat of these loans. With the help of an economic lens, we put things through the eyes of the banks too, realizing the tool we imagined has the power to mitigate loan related risks and increase ROI’s for banks
What it does
The code runs the various parameters identified by our group as contributors to success and calculates an output based on the data from the spreadsheet. The output is representative of the rate of success of students post-graduation.
How we built it
The team categorized the array of variables into five bins, each one summarizing one factor contributing to future success. Then, using the quantitative data we were given, we created formulas to calculate an output value, that would describe the success rate of students post-graduation.
Challenges we ran into
The major challenge was identifying and sorting the variables into the five bins we identified as contributing factors to success. There were more columns of data than we could handle/comprehend. The other limiting factor was negative values. Upon exploration of the data source website, we concluded that the negatives represent some form of abstinence from partaking in the survey. Those negative numbers, since arbitrary, were skewing our mathematical summaries (mean, averages). Omitting them was the only (not necessarily wisest) option. Given more training on understanding and working with the data, the team will surely produce more accurate results.
Accomplishments that we're proud of
Given the diversity of the group, a freshman, an economics major, and two CS majors, our group’s communication, teamwork, and interpersonal relations were impressively smooth and efficient. The interdisciplinary dynamic enabled great ideas to nurture and blossom into working solutions.
What we learned
Our major take away as a group was learning how to work on 100% capacity during a span of two days continuously. There will be many instances in the real world where such dedication and commitment is required for short periods of time.
We learned to think on our feet. With limited time to design a solution, rapid decision making as a group is a skill the team acquired with relative ease. Listening to other’s opinions and evaluating perspectives in order to be respectful while deliberating is another skill we practiced through the course of this challenge.
What's next for Calculating Success Scores
Account for all errors created during the data synthesis process, and factor in the discrepancy in the final formulas. Broaden the scope of evaluation of the formulas to be inclusive of more variables and rightfully categorize those variables into larger groups. Create a user interface for customers that are easy to operate.