As college students, we have a pain to decide what classes to take every semester. Existing websites such as Rate My Professors do not provide many details about how much workload each class would have throughout a semester, and they are not personalized. Therefore, we want to provide more accurate statistics on course workload for college students like us. We do this by gathering user input of how many hours they spend on each assignment and use these data to predict the needed time of the assignments for future students.
Use Machine Learning for customized workload prediction
We estimate user’s time needed for next assignment using k nearest neighbors Machine learning algorithm, which is one of our technical challenges. The algorithm gives that the more user input time, the more accurate the estimation can be in the future.
Open source project for data visual representation
We adopt the open source package, Charts, to better present our data in a user-friendly way. Our app shows graphs like workload trends throughout a semester, comparisons between an individual and the entire class, and so on. We decide to use the line charts and bubble charts because they clearly interprets data for users within their intuition.
Our app has 3 tabs. On the first tab, we display popular classes that users can click and view. Users can search for classes and view course information.
Users can click the button here to enroll in a class and use our app to keep track of the courses that they are currently taking. They can enter the time that they spend on every assignment as a reference for future students. To encourage user input, the app will unlock the function of view performance after they submit hours. It compares your time spent on the assignment with the average time in the class and get some idea of how they are doing.
Students obviously don’t want all deadlines all in the same week. After users add classes to the worksheet that they are going to take next semester, they can view their overall workload here in the Planned tab and get a general idea of how the workload of assignments are like. If there are multiple of large bubbles all in a short amount of time, you probably won't want to take these classes in the same semester.