Solving Course Selection Problem by a Combination of Correlation Analysis and Analytic Hierarchy Process

Abstract

In the universities where students have a chance to select and enroll in a particular course, they require special support to avoid the wrong combination of courses that might lead to delay their study. Analysis shows that the students' selection is mainly influenced by list of factors which we categorized them into three groups of concern: course factors, social factors, and individual factors. This paper proposed a two-phased model where the most correlated courses are generated and prioritized based on the student preferences. At this end, we have applied the multi-criteria analytic hierarchy process (MC-AHP) in order to generate the optimum set of courses from the available courses pool. To validate the model, we applied it to the data from students of the Information System Department at Taibah University, Kingdom of Saudi Arabia.