A Predicting Of Student Grades Using Decision Tree Algorithm

  • Ahmed I. Taloba, Alanazi Rayan, Osama R. Shahin, Rasha M. Abd El-Aziz, Zayed Al-Ruwaili, Rakan Al-Juhani, Mohamed Al-Ruwaili


Data mining has already been effectively employed in the commercial world in recent decades. Today, leading institutions frequently use data mining technologies to analyze available collect and analyze information and expertise to aid decision-making. Education is a large and vital topic which can be properly handled in this area. The quantity of data saved in educational databases has been constantly increasing in recent years. In educational settings, the capacity to anticipate student success is extremely significant. Evaluate data mining tools and strategies to build a prediction model for student grade prediction. Data mining can also be used to sort out educational problems by employing analysis approaches to assess student achievement. In this study, a categorization approach called a decision tree to assess student grades. Estimating a student's grade is a major challenge for university education administrators. Every academic institution in the world keeps a student result database, which contains data on students' grades in various courses. In this paper, data collected used in the research based on male and female students of the Department of Computer Science in Al-Qurayyat - Jouf University, by making a questionnaire on the Google Form website, to collect the male and female students’ scores in the 6 major courses of the Computer Science Department, in addition to the cumulative average of the male and female students. As a result, the WEKA tool to apply the decision tree method to obtain a model through which can predict the student's cumulative average depending on the student's grades in the specialization courses, and obtained an accuracy of 45% due to the lack of examples used in the training phase. conclusion based on the information utilized in the training phase, computer programming course 2 is perhaps the most significant course in determining students' GPA.