An Intelligent Tool to Predict and Analyze Students' Stress for Their Academic Growth

Due to inadequate preparation and direction, students are currently unable to pursue careers as scientists, doctors, engineers, or pilots. The administration of the school, can use different steps in order to improve performance among pupils by motivating them to achieve their objectives and providing them with the necessary training and direction so that they can pass the entrance test for their further education by being aware of their areas of strength. We have developed a web application as a solution to the aforementioned issue, allowing the administration to gather pupil information and save it in a database for use in tracking attendance, marks, and performance. Next data gathering, the factors that determine the pupil's result are separated and entered into a web application that can forecast whether the pupil will pass the entrance exam. For the purpose of determining if the student is prepared to take their tests with confidence, a quiz that assesses the students' mental health is provided before the inclusion of this prediction. If the management or mentors of the institute determine that a student cannot pass the test or that their mental health requires extra coaching, they can offer them adequate counsel. Our project involves developing an effective web application that uses the random forest machine learning algorithm to examine the mental health of the student. We installed it in our web application since we obtain an accuracy of 94%. This online application will serve as a conduit between high school students and the administration of the school. Utilising this tool, administrators may assess students' abilities and provide them with the appropriate guidance.