通过新算法识别影响理工科毕业率的关键因素，助力高校精准提升学生成功率。

Improving undergraduate success in STEM requires identifying actionable factors that impact student outcomes, allowing institutions to prioritize key leverage points for change. We examined academic, demographic, and institutional factors that might be associated with graduation rates at two four-year colleges in the northeastern United States using a novel association algorithm called D-basis to rank attributes associated with graduation. Importantly, the data analyzed included tracking data from the National Student Clearinghouse on students who left their original institutions to determine outcomes following transfer. Key predictors of successful graduation include performance in introductory STEM courses, the choice of first mathematics class, and flexibility in major selection. High grades in introductory biology, general chemistry, and mathematics courses were strongly correlated with graduation. At the same time, students who switched majors - especially from STEM to non-STEM - had higher overall graduation rates. Additionally, Pell eligibility and demographic factors, though less predictive overall, revealed disparities in time to graduation and retention rates. The findings highlight the importance of early academic support in STEM gateway courses and the implementation of institutional policies that provide flexibility in major selection. Enhancing student success in introductory mathematics, biology, and chemistry courses could greatly influence graduation rates. Furthermore, customized mathematics pathways and focused support for STEM courses may assist institutions in optimizing student outcomes. This study offers data-driven insights to guide strategies to increase STEM degree completion.