An Optimal Slack-Based Course Scheduling Algorithm for Personalised Study Plans

TL;DR: In this paper, a slack-based algorithm is proposed to provide a personalized study plan to help university students determine which courses to take each semester in order to achieve optimal graduation time.

Abstract: Receiving a degree or learning certificate in a chosen field is often seen as the gateway to a bright future, and an essential building block when paving a way toward a successful career in one's chosen field. However, it is often the case that many undergraduate university students take longer than the expected number of years to attain their degree. This is often a result of poor planning, such as not taking enough courses per semester, or course scheduling conflicts. In this paper, we propose a solution to help mitigate causes associated with poor course planning as reasons why students do not graduate on time. We propose a slack-based algorithm, which uses the prerequisite relationship between courses, to provide a personalized study plan to help university students determine which courses to take each semester in order to achieve optimal graduation time. Each student's recommended study plan is based on the student's personal interests and preferences. This will ensure that the student not only fulfils the university's requirements for graduation in a timely manner, but they also take courses that are appropriately suited to their interests.