Student Academic AI based Prediction System

Education is a critical factor in any nation's development. As a result, proper consideration should be given to its implementation. Every institution gathered a large amount of data from students in the form of session tests, assignment grades, and internal and external laboratory evaluations. However, all this information is used to determine whether a student passes or fails a specific examination. If student data is analyzed on time, it will undoubtedly help students improve their academic performance. So, for any educational system to be successful, a proper evaluation check should be maintained. These methodologies generate a lot of data about students' academic progress and marks, and if that data is not properly analyzed, all the collected data is wasted, and no further use of that data occurs. As a result, every educational institution now employs assessment or evaluation criteria to monitor student performance. There are numerous evaluations or assessment tools available in this modern era of education that can be used to monitor students' academic performance. By evaluating student progress on a regular basis, timely help and support are provided to students who are at risk of failing or dropping out, allowing them to improve their performance in the future. It also assists the organization's management and administrative staff in taking appropriate action to improve the system. A detailed literature survey is carried out while keeping all these factors in mind. The primary goal of this survey report is to identify the factors that influence student performance.