ABSTRACT
Education is one of the many industries that artificial intelligence (AI) and machine learning (ML) are revolutionizing. Using machine learning approaches, this research paper investigates how study habits, attendance in class, and other characteristics affect student performance. A thousand student's worth of data were evaluated in order to find correlations and forecast final test scores depending on different inputs. According to the study, using educational technology, attending classes on time, and developing consistent study habits all have a big impact on students' academic achievement. This paper offers practical insights and suggestions to help students improve their study techniques, teachers improve their approaches, and legislators successfully incorporate AI and ML into educational systems. The purpose of these results is to maximize learning outcomes and get pupils ready for a future dominated by technology.
Keywords: Artificial Intelligence, Machine Learning, Student Performance, Study Habits, Class Attendance, Educational Technology, Predictive Analytics, Personalized Learning, Educational Policy, Data Analysis.
