抄録
As data science becomes vital for solving complex societal challenges, inclusive data literacy is needed across all disciplines. However, in Japan, rigid divisions between STEM and non-STEM fields limit access for students in humanities, social sciences, and sports. This paper explores the systemic, cultural, and educational barriers facing non-STEM students in acquiring data skills. Drawing on policy trends and institutional practices, we identify key challenges such as narrow curricula, negative attitudes toward quantitative subjects, and unclear career relevance. We advocate for interdisciplinary, context-based learning that empowers diverse learners to apply data science for social good. This first paper in a two-part series highlights the need for inclusive education reforms to build a more equitable digital society.
