This paper aims to support academic advising, which plays a crucial role in student success and retention. The paper focuses on one of the most challenging tasks involved in academic advising: individual course scheduling. This task includes not only careful planning for different courses over several semesters according to students’ preferences and goals but also must conform to many student constraints and administrative regulations, some of which may rely on student-specific cases..
This paper introduces a novel approach that tries to provide meaningful support to decision makers involved in the course scheduling problem. The approach uses optimization algorithms to perform a pro-active analysis of the impact of different problem aspects and eventually suggests a balanced study plan that tries to satisfy both student preferences and advisor recommendations without violating any constraints.
An initial application of the proposed system is used to discuss its benefits.
The paper introduces a novel approach that uses optimization techniques to support making efficient decisions during the academic advising process.
