The Impact of Data Processing by Neural Networks on Academic Failure

Abstract

Academic failure has become a shocking phenomenon, affecting large numbers of students at all stages of education, particularly in the early years, and students and their families experience academic failure in a dramatic way. For a long time, academic failure among university students has been the subject of heated debate. Many educational psychologists have tried to understand and explain it. Statisticians have tried to predict it. This research (chapter) aims to classify students into several categories, as well as using artificial neural networks to classify first-year students and identify variables likely to explain the problem (students failing at the end of their first year).