  In an academic environment, student advising is considered a paramount
activity for both advisors and student to improve the academic performance of
students. In universities of large numbers of students, advising is a
time-consuming activity that may take a considerable effort of advisors and
university administration in guiding students to complete their registration
successfully and efficiently. Current systems are traditional and depend
greatly on the effort of the advisor to find the best selection of courses to
improve students performance. There is a need for a smart system that can
advise a large number of students every semester. In this paper, we propose a
smart system that uses association rule mining to help both students and
advisors in selecting and prioritizing courses. The system helps students to
improve their performance by suggesting courses that meet their current needs
and at the same time improve their academic performance. The system uses
association rule mining to find associations between courses that have been
registered by students in many previous semesters. The system successfully
generates a list of association rules that guide a particular student to select
courses registered by similar students.
