抄録
This study examined the impact of a data science lecture for social inclusion on 168 STEM and non-STEM undergraduates (89 in the Sports and 79 in the Regular program) at Rissho University. Using a mixed-methods approach (survey analysis and NLP-driven qualitative text analysis), it explored evolving student perceptions. Quantitative results showed increased understanding and interest. Qualitative analysis revealed that despite initially lower theoretical confidence, non-STEM students creatively proposed practical, socially oriented applications. Key themes included "Data Utilization," "Social Issues," and "Disability and Welfare," with a notable shift from abstract concepts to concrete problem-solving. Findings suggest that interdisciplinary, context-based pedagogy emphasizing real-world problems and social impact enhances data literacy and fosters inclusive innovation.
