Application of Decision Tree Algorithm in Educational Data Mining

Decision tree algorithms in Educational Data Mining (EDM) emerges as a powerful method for student classification according to their learning station. This article emphasizes the necessity classify students due changing scenario of China's higher education system, which has shifted from elitist popularization, and lead university students' differences abilities. For specialty characteristics educational data, this study adopts decision algorithm based on ID3 students. presents an analysis application course "Hydraulic Pneumatic Technology Course Design," is mandatory Mechanical Design Manufacture Automation Major. identifies five splitting features that affect ability achieve success practical course, build model. The samples mode are collected Bachelor University Shanghai Science (USST). According categorization results teachers make informed decisions insights provided by improve experience academic performance Similarly also provide personalized guidance students, beneficial ensuring ultimately improving overall outcomes.