A new model for using data mining technology in higher educational systems

Quality in higher educational systems has been placed squarely on the contemporary agenda. Nowadays, it can be observed that higher educational systems have encountered many challenges which prevent them to achieve their quality objectives. Some of these problems stem from the knowledge gap in higher educational operational and business processes. Knowledge gap is the lack of enough and deep knowledge at educational processes such as planning, evaluation and counseling. The main idea in This work is that the hidden patterns, associations, and anomalies that are discovered by data mining techniques can help bridging this knowledge gap in higher educational systems. We present and justify the capabilities of data mining technology in the context of higher educational system by proposing a model for improving the efficiency and effectiveness of the higher educational process. Higher educational institutes can use this model to identify which part of their processes can be improved by data mining technology and how they can achieve this goal.