إستخدام التحليل العنقودي والتحليل التمييزي في تصنيف العوامل المؤثرة على التحصيل الأكاديمي لدى طلبة كلية التربية بجامعة سيئون
This study aimed to utilize cluster analysis and discriminant analysis to identify the factors influencing academic achievement among students of the College of Education at Seiyun University. The researcher employed a descriptive analytical approach, collecting data from a sample of 214 students. Student data were used as predictors, including gender, major, and course groups: educational, psychological, and specialized. The study's results indicated the following: 1) There were two clusters of sample individuals: the first cluster (low academic achievers) consisted of 76 students, while the second cluster (high academic achievers) included 138 students. 2) There was a statistically significant relationship between gender and the student's belonging to one of the clusters. Most females were concentrated in the second cluster (high achievers), while most males were concentrated in the first cluster (low achievers). 3) A statistically significant relationship existed between the specialization and the student's belonging to one of the clusters. Students specializing in mathematics, science, and social studies were clustered found in the first cluster, while students in chemistry and geography were in the second cluster. 4) A set of factors distinguished between high and low academic achievers, including: (gender, specialization, and the academic courses. The educational curriculum had the greatest weight and ranked first in its ability to differentiate between high and low achievers. Then in the second rank: Real Analysis (Mathematics), Organic Chemistry (Sciences), Modern Arab History (Social Studies), Automated Analysis Chemistry (Chemistry) and Industrial Geography (Geography). Practical Education ranked third. The discriminant function significantly contributed to distinguishing between high and low academic achievers. The Classification was Correct (96.7%). (Published abstract)