Data-Driven Recommendation of Academic Options Based on Personality Traits

Abstract

Master’s thesis exploring how personality-trait inventories can be combined with large-scale academic and career-outcomes data to build a recommendation system for academic majors. The thesis introduces “Pocket Jeanie” — a recommender that helps high-school students identify academic and career paths aligned with their measured traits — and evaluates the system with active users.