With support from the Accelerating Discovery program, this project will develop methods and materials for infusing data science instruction within the undergraduate STEM curriculum. Infusion of data science will begin with the earliest STEM calculus prerequisite courses and continue through capstone experiences. Targeted courses include existing STEM classes in science, mathematics, and engineering. Progressions through STEM curricula will be developed to provide students with data science competencies including acquiring, managing, analyzing, visualizing, and drawing conclusions from data. The project materials that will be developed include sequenced modules, curricular and co-curricular projects and internships, and capstone projects for interdisciplinary teams. The project will also create a "data science hub" to facilitate the forming and mentoring of student teams to actively engage in applying data science methods within the physical and natural sciences, mathematics, and engineering.

As expertise in data science is becoming a required component for work in any STEM field, this project aims to integrate data science into the STEM disciplines to enhance undergraduate student learning and preparation for the STEM workforce. The project will use an integrative approach in which data science serves as the interdisciplinary connector of mathematics, science, and engineering. The project aims to conduct a comprehensive research study of the outcomes of the resulting integrative instruction at the collegiate level. Specifically, the project seeks to generate evidence about whether and how the curricular interventions effectively expose students to data science and to determine if this exposure motivates students to attain further training in data science and to pursue data science careers. Student learning outcomes data will inform best practices for infusing data science in undergraduate STEM education. The project will host a workshop for faculty in STEM fields to expand the impact of sharing the curricular materials developed in the project. Additionally, modules and curricular materials for infusing data science will be available freely as web resources. By infusing data science in the STEM disciplines, the project seeks to enhance undergraduate students' exposure to and expertise in data science as well as enhance their preparation to enter the STEM 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.

Agency
National Science Foundation (NSF)
Institute
Division of Undergraduate Education (DUE)
Type
Standard Grant (Standard)
Application #
1917002
Program Officer
Ellen Carpenter
Project Start
Project End
Budget Start
2019-10-01
Budget End
2023-09-30
Support Year
Fiscal Year
2019
Total Cost
$2,791,391
Indirect Cost
Name
Dartmouth College
Department
Type
DUNS #
City
Hanover
State
NH
Country
United States
Zip Code
03755