The Data Analytics Throughout Undergraduate Mathematics Program (DATUM) develops an integrated education/research program aimed at training students to become versatile in the philosophy and tools of data analysis and modeling for Computer and Data-Enabled Science and Engineering (CDS&E). We define data analytics to include modeling, simulation, and analysis of mathematical models based on data and observations. The anchor of the educational program is a new sophomore level course, "Introduction to Data Mathematics" (IDM), which introduces high-dimensional data modeling and its interdisciplinary application to CDS&E. To provide exposure to data for Freshman, the program will include capsules for the Calculus and Linear Algebra course sequence that introduce CDS&E applications as well as labs in the Introductory Biology course devoted to Data Analytics. Upper class students that have completed IDM, can choose from 5 existing mathematics courses enhanced to include data modeling with CDS&E applications and projects as well as a co-developed Information Technology "Data Analytics" course. Further, learning communities will be established in the residence halls led by advanced undergraduate "Math Mentors" with experience in data analytics research. After completing IDM, math majors/minors, possibly teamed with other majors, can submit research proposals on data analytics to participate in a summer undergraduate research program. A capstone senior research project and participation in research symposia will culminate the research experience.
There is an urgent need for people who are fluent in data modeling, analysis, and simulation in science and engineering disciplines. This project rapidly transforms the mathematics curriculum and culture to provide an undergraduate experience where students develop an exploratory mindset that enables them to independently translate real-world problems and real-world data sets into mathematical models that they can analyze to produce answers and insights. Enabling students to do analysis of real-world problems as part of the undergraduate curriculum provides an intriguing vehicle for attracting more students to majors in science, technology, engineering and mathematics. An increased pool of deep analytic talent can accelerate discovery in science, engineering, and medicine and increase the global business competitiveness of the United States.
