Measuring and Enhancing the Performance of Undergraduate Student Using Machine Learning Tools

Large number of students are graduated from colleges every year. A student with several specialties and several skills are supposed to be ready for the market. unfortunately, a small percentage of the graduate students are having the required market skills. Therefore, they can directly start their career life. A few numbers of researches address the systematic approaches of measuring the student performance while they haven't graduated yet. In addition, a few numbers of researchers address the techniques and approaches that can be adopted not only for measuring the student performance, but also improving their performance. In this research, the student's related data is analyzed based on several features. The data in this context is considered as big data in which there is a need for a specialized tool to perform an accurate and efficient analysis. Student gender, type of enrollment, marital status, city of birth and the type of learning in the k-12 stage are the features that have been chosen in this study. Moreover, the Al-Al Bayt University student was the population in this study.