Currently the schedule creating tools given to students do not include a schedule suggestion engine. Without any explicit, personalized guidelines, students are forced to spend hours reading descriptions, looking up offer dates, and checking prerequisites before their advising meetings. This lack of guidance leads to students being ill prepared for their advising meetings, which forces a fifteen-minute meeting to become an hour-long slog through possible classes. An engine that automatically suggests schedules based on past student performance will greatly ease this process for both students and their advisors. Students that are proactive will, with greater ease, be able to whittle down all the available classes to a few that the student could visualize registering for and eventually attending. Advisors would also be able to shorten meeting with unprepared students. While it may be easy to suggest courses from the professor’s home department, it is more of a challenge to suggest classes that fulfill LAC requirements. This project creates a tool for selecting appropriate courses and a schedule for a specific student based on their academic history. It is coded in Java for ease of understanding, future enhancement, and portability.
