Practice and Evaluation of Data Science Education for First-Year Students in Foreign Language Faculties

This study presents the design, implementation, and evaluation of an introductory data science (hereinafter, DS) course tailored specifically for first-year non-STEM students at Kanda University of International Studies (KUIS), focusing on the 2024 academic year cohort. Recognizing common barriers faced by non-STEM students, such as limited mathematical literacy, inadequate ICT skills, and low motivation, the course employed accessible methods to foster engagement and effective DS education. Key features included an emphasis on numerical reasoning over complex mathematics, utilizing student-centered activities using authentic datasets, and extensive practical exercises utilizing Tableau, a no-code business intelligence (BI) tool. Delivered in an on-demand format to approximately 900 students, the course achieved a 90.3% pass rate and led to significant improvement in students' self-assessed DS competencies. It effectively bridged knowledge and skill gaps between students with and without prior DS experience. However, motivational gains were modest, indicating areas for pedagogical improvement. Future research should address potential biases from voluntary survey participation, deepen motivational analyses, and explore strategies that explicitly link DS education with broader career relevance.