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      • Using Data Mining Techniques in Building a Model to Determine the Factors Affecting Academic Data for Undergraduate Students

        Nafie, Faisal Mohammed,Hamed, Abdelmoneim Ali Mohamed International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.4

        The main goal of higher education institutions is to present a high level of quality education to its students. This study uses data mining techniques to extract educational data from cumulative databases and used them to make the right decisions. This paper also aims to find the factors affecting students' academic performance in Majmaah University, KSA, during 2010 - 2017 period. The study utilized a sample of 6,158 students enrolled from two colleges, males and females. The results showed a high percentage of stumbling and dismissed between graduate and regular students where more than 62.5% failed to follow the plan. Only 2% of students scored distinction during their study of all graduated since their grade point average, secondary level, was statistically significant, where p<0.05. Dismissed percentage was higher among males. These results promoted some recommendations in which decision-makers could take them in considerations for better improvement of academic achievements: including of specialized programs to follow-up in regards to stumbling and failure. Utilization of different communication tools are needed to activate academic advisory for dismiss and dropout evaluation.

      • Tracing Students Performance by Intervention of the Academic Advisor

        Mohamed, Abdelmoneim Ali,Nafie, Faisal Mohammed International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.spc12

        Data mining technique was used to track student's performance during years studding in college and determine the impact of GPA_SEC on the GPA student rates according to the current academic advising method used on student's status. The study utilized a sample of 5436 individuals were drawn from two colleges in Majmaah University, KSA during 2013-2018 period. The results showed that the student's completion status in terms of graduation, dropout, Stumbling or dismissed was classified according to the average grades of admission from secondary school GPA_SEC. The results show the effect of the current academic advising that most of students gain less grades comparing with GPA_SEC in addition that the higher GPA_SEC was the higher graduation, dropout and dismissed decreased when GPA_SEC was high.. Therefore, the study recommends tracking students academically to evaluate their results of each semester to find out the causes of the deficiencies and addressing them within the departments.

      • Tracing Students Performance by Intervention of the Academic Advisor

        Mohamed, Abdelmoneim Ali,Nafie, Faisal Mohammed International Journal of Computer ScienceNetwork S 2021 International journal of computer science and netw Vol.21 No.12

        Data mining technique was used to track student's performance during years studding in college and determine the impact of GPA_SEC on the GPA student rates according to the current academic advising method used on student's status. The study utilized a sample of 5436 individuals were drawn from two colleges in Majmaah University, KSA during 2013-2018 period. The results showed that the student's completion status in terms of graduation, dropout, Stumbling or dismissed was classified according to the average grades of admission from secondary school GPA_SEC. The results show the effect of the current academic advising that most of students gain less grades comparing with GPA_SEC in addition that the higher GPA_SEC was the higher graduation, dropout and dismissed decreased when GPA_SEC was high.. Therefore, the study recommends tracking students academically to evaluate their results of each semester to find out the causes of the deficiencies and addressing them within the departments.

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