Decision Support System Based Markov Model for Performance Evaluation of Students Flow In Computers Faculties (Case Study: King Abdulaziz University)

This paper proposes an effective decision support system based on an absorbing Markov model, which is used for helping decision makers in Faculty of Computing and Information Technology (FCIT) at King Abdul Aziz University (KAU) in controlling student’s flow transition enrollment. Several important controlling criteria that govern student’s flow performance during semesters are evaluated. These include estimating students flow between different study levels, the average life time a student spends at each level, the semesters required for graduation, and students graduating probability. A complete performance evaluation comparison between boys and girls at IT College is investigated. Results show that girls achieved better performance than boys. The system has several advantages, such as, helping to find any bottle necks to be solved during student’s transition study from one semester to another, and helping to know students needed facilities to planning for future required resources, hence achieving good quality and efficient university education. The proposed model is validated using cross-validation methodology, and the achieved results were acceptable