Paper Title
Rule Combination in Educational Data Mining- Educational Support for Tutoring and Learning

Student classification is one of the most promising tasks in Educational Data Mining. It provides new patterns to get into the new knowledge of forecasting Students final status. It is an interesting issue since predicting Fragile Learners in early stages enables both Teachers and Learners to evaluate current applied strategies. In this connection, analyzing gathered data ,writing prediction rules, building a model and achieving high predictive performance is vital. As a matter of fact, our method with rule combination gives a perfect result with accuracy rate and high numbers in Recall, Precision and F-Measure. Approach that is applied in this research gives us an idea of a novelty model in Teaching and Learning process. From Students perspective, to identify the Fragile Learners, potential Students who need extra help to perform well during the course. From Tutor perspective, to evaluate their ongoing teaching strategy whether it meets their current students abilities. Keywords - Data Mining , Education ,Technology, Rule Combination