SCRAP – Smart Character Recognition and Prediction AI

This paper provides a comparative analysis of existing research on using machine learning techniques to predict students’ career paths based on personality traits and interests. Four prominent studies on this topic are critically examined, including their approaches, results, and limitations. Collectively, the papers underscore the potential of machine learning in career counseling but also reveal challenges like privacy, interpretability, and ethical concerns. The analysis suggests that incorporating diverse factors like interests, academic performance, and evolving career trends can enhance prediction accuracy. Expertise in both machine learning and psychology is identified as crucial for mapping behaviors to careers. While existing studies demonstrate promise, this analysis highlights areas needing improvement. It concludes that the field is continuously advancing and holds promise for transforming career decision-making if challenges are addressed through a multi-disciplinary approach.