MACHINE LEARNING TO DETECT AND PREVENT STUDENT DROPOUT

Abstract

One issue affecting schools is the high student dropout rate. The dynamic, broad nature of our everyday lives makes it difficult to predict whether or not students will drop out. Even though gathering student data in this region of the world is a challenge, it has hindered a number of studies looking at student dropout and performance prediction.� Early student dropout prediction can assist academic institutions in implementing the proper planning and training, as well as timely interventions, to increase the success rate of their students. With the help of machine learning algorithms, this study shows a system for predicting student academic dropout. Institutions of higher education, secondary schools, and other users in the market will greatly benefit from the suggested predictive system in the area of education.

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urn:uuid:75fbab1e-f1a0-4e7b-8d04-ff9366577e90