Targeted Infusion Project: Infusing Data-Centered Pedagogy and Data-Analytical Skills into Introductory Statistics

历史黑人学院和大学本科项目(HBCU-UP)通过有针对性的灌输项目，支持基于证据的创新模式和方法的开发、实施和研究，以改善HBCU本科生的准备和成功，使他们能够攻读STEM研究生课程和/或职业。因此，根据国家科学院的建议，北卡罗来纳农业与技术州立大学(NCA&amp；T)寻求通过重新设计其统计学入门课程来实现现代化，其中包括数据科学和大数据分析组件的注入。该项目旨在实现三个主要目标：增强学生从统计学入门课程中获得的统计知识和数据分析技能；通过准备和吸引学习统计学入门课程的STEM和非STEM学生进行数据科学教育，为新的数据科学证书和学位课程创建一个渠道；以及建立一支能够并致力于使用以数据为中心的教学方法教授入门统计学的教员干部队伍。每年，这门有针对性的统计学入门课程将招收约600名学生。课程的重新设计将包括在课程中增加一个虚拟统计计算实验室，并在实验室和课堂教学中采用以证据为基础的数据为中心的教学方法，以加强学生对基本统计概念的理解，训练学生用数据进行结构化思考，做出数据知情的决策，并使学生及早和频繁地接触数据科学工作流程的要素。该项目将使统计学入门教师参与一系列专业发展活动，以便在其教学中采用以数据为中心的教学法。拟议的入门统计学重新设计预计将提高学生从课程中获得的知识，降低课程重复率，帮助学生发展数据科学和STEM所需的计算能力，增加该机构数据科学项目的入学人数，并发展教师教学专业知识。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The Historically Black Colleges and Universities Undergraduate Program (HBCU-UP), through Targeted Infusion Projects, supports the development, implementation, and study of evidence-based innovative models and approaches for improving the preparation and success of HBCU undergraduate students so that they may pursue STEM graduate programs and/or careers. Accordingly, in line with recommendations of the National Academies, North Carolina Agricultural & Technical State University (NCA&T) seeks to modernize its introductory statistics course through a redesign that involves the infusion of data science and big data analytics components. This project seeks to achieve three main goals: enhance students’ statistical knowledge and data-analytical skills gained from the Introductory Statistics course; create a pipeline for the new certificate and degree programs in Data Science by preparing and enticing STEM and non-STEM students taking introductory statistics to pursue data science education; and build a faculty cadre capable of, and committed to, teaching introductory statistics using data-centered pedagogy. Each year, the targeted Introductory Statistics course will enroll about 600 students. The redesign of the course will consist of adding a virtual statistical computing lab to the course and adopting evidence-based data-centered pedagogy in teaching the lab and class sessions to enhance students’ understanding of fundamental statistical concepts and to train students to think structurally with data, make data-informed decisions, and expose students, early and frequently, to the elements of the data science workflow. The project will engage the introductory statistics faculty in a suite of professional development activities on adopting the data-centered pedagogy in their teaching. The proposed redesign of introductory statistics is expected to improve students’ knowledge gained from the course, reduce the course repeat rates, help students develop the computational competencies needed for data science and STEM, increase the enrollment in the Data Science programs at the institution, and develop faculty teaching expertise.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.