Revealing Students’ Career Interests From Textual Responses: An Application of Structural Topic Model

This study utilizes the Structural Topic Model (STM; Roberts et al., 2014) to uncover key career interests among secondary school students from their open-ended survey responses. Textual data from students were analyzed to identify five core career interest themes, and covariate analysis revealed gender differences and associations between giftedness scores and career interests. These findings demonstrate the potential of STM as a robust tool for analyzing large-scale textual data, enabling educators to tailor career guidance programs.