Integrating IQ and Emotional Intelligence for Students Career Decision Making Using Machine Learning: A Review

The goal of developing a system that can accurately predict a student’s IQ and EI using a variety of data points, such as academic success, scores on aptitude tests, certifications, and feedback from professors and family members, is to design a student assessment model based on intelligence quotient using machine learning. This approach could be used to enhance student placement and guarantee career success for graduates. In addition to the foregoing, my work is important because it represents one of the initial initiatives to apply machine learning to create a comprehensive indicator of student intelligence. Although this is a difficult task, it has the ability to completely change how we evaluate kids and assist them in realizing their potential. Overall, a student assessment model based on intelligence quotient might be created utilizing a variety of different machine learning techniques. The ideal strategy will change based on the application’s particular requirements and the data’s accessibility. My task is to use machine learning to create an intelligence-based student assessment model. The placement of students can therefore be improved, and this information can be used to guarantee that students succeed in their jobs. The conclusion drawn from the foregoing is that applying machine learning to enhance student evaluation is of growing interest.