A Framework for Predicting Student Academic Path Using Machine Learning

The academic world is constantly evolving, and with it, comes an ever-increasing importance on predicting students’ academic path. Choosing the right orientation is crucial as it can have a significant impact on future career and personal growth. Thus, an effective prediction approach can help ensure that all students have the opportunity to reach their full potential and achieve success in their academic pursuits. In this article, we introduce a framework for predicting high school students’ academic path based on machine learning algorithm. The purpose of this framework is to provide educators and researchers with a systematic approach for analyzing student data from different sources. Our focus is also to identify significant factors that influence student academic orientation. Hence, we collected comprehensive information about students as such as their academic performance, demographics, learning style, and socio-economic status, among other characteristics. Ultimately, our goal is to promote innovation in the field of education by providing valuable insights into this critical exploration.