Academic Evasion
Employment of Data Mining in the discovery of Driving Factors
- 56 pages
- 2 hours of reading
Focusing on the critical issue of student dropout in education, this work explores its multifaceted impacts, including social and economic losses. It emphasizes the necessity of developing effective predictive methods to identify students at risk of leaving higher education. By utilizing a knowledge discovery approach and analyzing a database, the study aims to uncover patterns and group students, enabling institutions to implement proactive measures to reduce dropout rates.
