Enhancing undergraduate engagement and motivation towards internship using machine learning and gamification techniques

Abstract

Internship selection process is a critical milestone for undergraduates in their academic journey. Traditional selection processes for internships often face challenges in selecting the full potential of candidates. Those methods are manual, time-consuming, and lack the ability to engage and motivate students effectively. They are focused on a limited range of methods, such as interviews, resumes, biodata, and assessment centers. This not only creates barriers for deserving students but also leaves organizations struggling to identify suitable candidates. To address this, we propose a gamification based solution which integrates machine learning, designed to engage and evaluate undergraduates in more accurate manner. Gamification elements such as points, badges, leaderboards and feedback has proven effective in improving motivation and engagement in various domains [2]. By implementing these gamification mechanisms, we aim to transform the internship selection process into an interactive and rewarding experience. The proposed solution evaluates undergraduates based on their academic performance, extracurricular activities, and sports participation. This approach aims to save time for recruiters by automating evaluations from academic performance to extracurricular engagement. Ultimately undergraduates feel valued, employers find better matches, and internships that nurture potential rather than suppress it.