REU Site: Increasing Statistical Preparation in Research Education for Underrepresented Undergraduates

点击翻译按钮获取中文摘要

This project is funded from the Research Experiences for Undergraduates (REU) Sites program in the Directorate for Social, Behavioral and Economic Sciences (SBE). It has both scientific and societal benefits, and it integrates research and education. The REU Site "Increasing Statistical Preparation in Research Education for Underrepresented Undergraduates" (INSPIRE U2 Program) will recruit and train 24 underrepresented female students in statistical analyses of big data. It is expected that this initiative will: 1) increase student interest in advanced degree programs; 2) provide support and mentorship to students; and 3) serve as a pipeline for entry into advanced degree programs. Each student will have the opportunity to conduct an independent research project, and in doing so, students will develop the skills, confidence, and inspiration to pursue advanced statistics opportunities within the sciences. Key innovations include: 1) the merging of two evidence-based training approaches; 2) training in the flexible application of knowledge; 3) analysis of data in real world contexts; and 4) intensive one-on-one mentoring and support. The project will have significant impact on science, policy, and society by increasing representation of women and ethnic minorities in statistical and data analysis fields and enhancing the rigor with which scientific research is conducted.Women of color and minorities are less likely to pursue careers in statistical fields because of lack of uniquely stimulating opportunities and appropriate support within the college environment. Thus, there is a critical need for diverse perspectives in statistical inquiry because there are educational and societal benefits to such diversity. The primary aim of the REU site is to address this need. Each year, for 3 years, approximately 8 underrepresented undergraduate female students who are rising sophomores will receive training in statistical programs and analytical techniques, including modern techniques not commonly included in the undergraduate curriculum. Students will engage in research in a lab with a faculty mentor and develop their own research question, conduct data analyses to answer their research question, and prepare a poster and oral presentation. Finally, students will participate in activities to promote collaborative behavior such as student mentorship, faculty mentorship, panel discussions, professional development activities, and field trips. The overarching goal is diversification among trained individuals with statistical knowledge and skills, leading to the enhancement of the scientific workforce.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.