Exploring Competency Gaps, Motivations and Learning Expectations of Women in Postgraduate Applied Data Science Training in Ghana

Abstract

ABSTRACT Women continue to be underrepresented in STEM fields, including data science. Although much research has focused on gender gaps at the undergraduate level, there has been less focus on women's experiences in postgraduate programs that combine statistics and applied data science. This study investigated the experiences of women enrolled in a postgraduate applied data science program in Ghana. Using a qualitative descriptive approach, data were gathered through semi‐structured interviews with eight female postgraduate students. Thematic analysis showed that, despite a limited background in advanced research and statistical techniques, the women exhibited strong motivation to learn these skills through postgraduate studies. They also expressed clear expectations for hands‐on use of statistical software, supportive interactions with lecturers, and experiential learning opportunities. The results emphasize the need for supportive teaching environments, early skills development, and practical learning in postgraduate education in statistics and data science.