Abstract
Educational Data mining has been proved as a practical solution in handling educational obstacles. Selecting undesirable learning pathway is a real precarious problem. The complication of such problem backs to its nature, as it is discovered after graduation or in the middle way of the learning pathway which makes the correction is almost impossible and it is too late to take corrective actions. Selecting undesirable learning pathway influences even the whole community by either low quality of graduates or graduates working in unsuitable career. This paper is introduced a rule-based recommendation system for students' learning pathway at University of Tabuk, at Kingdom of Saudi Arabia. As a research methodology: first, decision tree has been selected as a data mining algorithm. Second, required data has been collected from University of Tabuk, Faculty of Computers and Information Technology. Third, decision tree has been developed based on the questionnaire's data. Last, induction rules have deduced from the tree paths to provide a recommendation advices. The proposed recommendation has been validated using test samples which are part of collected questionnaires. From the rules there are seven interesting findings have been presented. Expected result is enhancing the overall learning process at University of Tabuk by providing suitable learning pathways.