Elective course recommendation model for higher education program

Educational data mining (EDM) applies data mining techniques to resolve educational managing problems. This paper proposes a general process of EDM for elective course recommendations based on student grades. Furthermore, proper and inadequate reasons for applying conventional measurements in the course recommendation domain are studied and complemented with new proposed quality measurements. Several techniques were studied to establish a model for estimating the grades in elective courses. The experiments suggested that SVD classifier using course information gave the best results. The overall results indicate that the proposed model is able to provide personalized recommendations for individual students based on the student’s abilities.