Scholarly

Inspiration

We initially began with the idea of an app that catches cheating by analyzing multiple choice questions and patterns in student answers. However, we discovered that the patterns we identified for cheating did not necessarily indicate that cheating occurred, and we didn't want to accuse a student of cheating when they did not. Therefore, we shifted our idea to preventing cheating altogether with our well rounded study site, Scholarly.

What it does

Scholarly allows student students to monitor and prioritize all of their courses (up to 8); the user inputs course average goals and their current course average, and the difference is used to determine which courses need the most work. Then study resources for that course are suggested.

How we built it

We create our site in Visual Studio Code (Live Share), and coded and tested small parts of functions in Replit to keep the final product organized. We coded entirely in Java to create our GUI. First, we retrieved the students' marks from the text fields and calculated the differences between their marks and their goals (for each course). We prevented the program from crashing by implementing try catch to find inappropriate inputs (like Strings instead of numbers). We added the differences to an array and determined the lowest (most negative) difference, which would be the student's worst course. Then a for loop was used to extract the corresponding resources from other arrays. Finally, the resources were displayed back in the GUI.

Challenges we ran into

We found that the VSCode Live Shares session would end when the host exited the program, preventing others from working on the code while the host was away; however, we utilized that time to focus on other aspects of our presentation and to research solutions to various technical problems. One of these technical issues occurred when we tried to link/access data from a Google Sheets in our site; because the Google Sheets API was not working and most Internet resources were out of data, we could not use the Sheet as a database. We overcame this by converting the Sheet into a csv file and uploading it to VSCode, and we created arrays with the information from each column, allowing us to avoid hard-coding all of the data into the program.

Accomplishments that we're proud of

We are extremely proud of our progress as a team with 3 out of 4 members being new and inexperienced. Our problem solving (especially in the case of our Google Sheets) has allowed us to make progress that we never expected, and all members have gained excellent experience.

What we learned

We learned how to build a Java GUI, and our inexperienced members were able to obtain more knowledge on Java. We also discovered several extensions and applications that we could use to work collaboratively, like VSCode Live Share.

What's next for Scholarly

Our site still has great room for improvement; given more time, we would like to change the application from a GUI to a website that allows users to create accounts and save their progress. We would also figure out how to use a larger database for our resources so that more courses can be available to users.