Mining Association Rules for Academic Performance Factors and Teaching Optimization

With the Ministry of Education's advancement of "AI + Education" strategy and the backdrop of student-centered educational philosophy, this study focuses on mining the truth contained in the massive student data, exploring key factors influencing academic outcomes. This study using data from the UI Frontend Design course produced by 189 students. This study was applied the Apriori algorithm with a minimum support threshold of 0.12 and a minimum confidence threshold of 0.45. Effective association rules with a lift greater than 1 were screened to conduct an in-depth analysis of underlying data relationships.