EXPLORATION OF FACTORS IMPACTING EDUCATIONAL STEADINESS USING MACHINE LEARNING TECHNIQUES: STUDY BASED ON EDUCATIONAL SECTOR OF PAKISTAN

Abstract

This research focuses on pointing out the reasons why students usually drop out of the educational sector and at which level of study. In the present work, a centralized mechanism to collect real-time data has been used that engages selected institutions and stakeholders for the whole process. The new system for this research collects all the academic information of a candidate in one place, regardless of their level of education. It enables students, parents, teachers, and educational authorities, such as school boards, the Ministry of Education, and other government departments, to assess the current state of education and strategize for improvements. The research aims to provide help to students, teachers, educational institutes, and the whole academic system to get all the previous and current records of the students. From the data, it is evident that we can obtain information regarding the number of students who discontinue their education at different educational stages. Subsequently, we can explore the reason behind this situation and make efforts to rectify it, aiming to preserve a high level of literacy in the country.