Career Confusion Prediction System for Students

Career decision-making is a critical phase in a student's academic journey, often accompanied by uncertainty and confusion due to multiple available options and unclear self-assessment. Traditional career guidance systems primarily focus on aptitude testing or preference-based recommendations, without evaluating the stability of a student's decision-making process. This paper proposes a Career Confusion Prediction and Roadmap Recommendation System that first identifies the level of career confusion and then provides a structured career pathway. The system analyzes behavioral indicators such as response hesitation, answer variability, interest switching, and expectation mismatch to compute a confusion score. Based on this score, students are classified into Low, Medium, or High confusion levels using a rule-based decision framework. For students with stable decision patterns, the system suggests a final career path and generates a detailed study roadmap outlining educational steps, skill development stages, and progression milestones. The proposed approach serves as an integrated decision-support framework that not only predicts confusion but also guides students toward a clear and actionable career direction, promoting informed and confident career choices.