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In an academic environment, student advising is considered a paramountactivity for both advisors and student to improve the academic performance ofstudents. In universities of large numbers of students, advising is atime-consuming activity that may take a considerable effort of advisors anduniversity administration in guiding students to complete their registrationsuccessfully and efficiently. Current systems are traditional and dependgreatly on the effort of the advisor to find the best selection of courses toimprove students performance. There is a need for a smart system that canadvise a large number of students every semester. In this paper, we propose asmart system that uses association rule mining to help both students andadvisors in selecting and prioritizing courses. The system helps students toimprove their performance by suggesting courses that meet their current needsand at the same time improve their academic performance. The system usesassociation rule mining to find associations between courses that have beenregistered by students in many previous semesters. The system successfullygenerates a list of association rules that guide a particular student to selectcourses registered by similar students.

Building A Smart Academic Advising System Using Association Rule Mining