The Factors Driving Career Planning and Mentoring in Four Year UG Engineering Education using ML Techniques

Abstract

Career Planning is a continuous process of evaluating individual career goals through self-assessment, market research and objectively meeting the goals through continuous learning. In the context of Industry 4.0, career planning is not just limited to working professionals, but also plays a major role for the professional engineering students. Mentoring becomes a solid supporting prop to reach these goals systematically. It requires a philosophy, proper design of methodology, and organization structure. This study explores various factors driving career planning and mentoring in Four year UG Engineering Education. In this context, authors conducted literature survey and student's survey on 171 students to understand various factors, skill levels needed in designing career planning model and proposed mentoring model using Machine Learning Techniques (k-Means Clustering Algorithm). Further, authors surveyed 1525 students to understand career aspirations, designed Center for Career Planning organization and experimenting this model in a leading private group engineering college.