Distribution of students in university academic fields: underlying myths, locality and influences

This study used a combination of text mining, network text analysis and graph theory to analyse enrolment patterns and identify factors that influence students' academic choices at a Tanzanian university. Data were collected from 1244 students, comprising 910 arts and 334 science students. The computational approach enabled the exploration of the structural relationships between myths, locality and socio-cultural influences that shape academic decisions. One prominent misconception is that STEM disciplines require exceptional academic ability, which discourages many students from pursuing science-related careers. Urban students were more likely to choose STEM programmes due to their greater access to educational resources. In contrast, rural students tended to favour the more traditionally perceived 'safer' fields, such as business, education and the social sciences. Family expectations and perceptions of career stability further reinforce these choices. By integrating computational methods, this study reveals complex enrolment dynamics that are often overlooked by conventional descriptive approaches.