Educational Data Mining to Identify Relationship Between Technical Knowledge and Academic Performance
Abstract
Now-a-days educational data is becoming very crucial to analyze students’ performance in their ability to get absorbed in the industry. Educational Data Mining (EDM) is the field of study concerned with mining instructive information to discover fascinating examples and learning in instructive associations. It demonstrates to obtain information from collection of student data from academic Institution databases. This paper highlights the importance of using student data to drive improvement in recruitment or placement of a student. Further, it will enable faculty members to identify, predict and classify students based on academic performance measured using Cumulative Grade point average (CGPA) grades. This investigation investigates different components accepted to influence advanced education and technical skills to finds a subjective model which predicts the capability in view of related individual and specialized elements.