The focus of the project is on the design of efficient pedagogical pathways to utilizing big data to educate the next generation of mathematics and statistics undergraduates to confront new challenges in computational and data-enabled science and engineering (CDS&E). The main goals are to 1) build a culture of training the next generation of mathematics and statistics undergraduate majors to become interdisciplinary collaborators and promote the value of mathematical and statistical thinking in advancing CDS&E and 2) develop a new pedagogical approach to teaching mathematics and statistics courses that complements lecturing with experimentation where students engage in hands-on activities with cyberinfrastructure (CI) enabling technologies. The project is interdisciplinary and integrates research, education, training, and faculty professional development/outreach components that subtly lead to the establishment and sustainability of a CI resource center. The center coordinates the CI resource needs and access to supercomputing centers and CDS&E collaborators for the research community at Jackson State University (JSU). The research component focuses on the quantitative exploration of large data sets from climate, weather and genomic acquired remotely through CI enabling technologies to explain the known mathematical and statistical theories and to develop new algebraic and statistical structures and theories. The main objectives are to: 1) Engage 28 undergraduate students majoring in mathematics or statistics, biology, and meteorology in a year-long collaborative CDS&E research for a minimum of two years under the supervision of an interdisciplinary team of faculty mentors; and 2) Guide participating students to place in summer undergraduate research in CDS&E. The educational and training component focuses on developing a BS in statistics and new pedagogical approaches to teaching mathematics and statistics. The teaching combines lecturing with lab activities where concepts learned in class are reinforced with CI lab activities connecting specific mathematical and statistical concepts to genomic and meteorological applications. The specific objectives are to 1) revise the course contents for abstract and linear algebra, set theory and logic, modern geometry, ordinary differential equations and mathematical modeling to integrate CDS&E in specific course topics for CI data and visualization activities; 2) develop a curriculum for the Bachelor of Science degree in statistics; and 3) create a LISA-QED lab equipped with the OptiPortal and associated technologies for local and distant collaboration, access to NOAA resources and Extreme Science and Engineering Discovery Environment (XSEDE) systems to enhance CDS&E activities. The faculty professional development and outreach components focus on developing mathematics faculty expertise in CDS&E and creating awareness. The specific objectives are to 1) Organize a series of Summer, Fall, and Spring CDS&E training workshops on bioinformatics, system biology, meteorology, cyberlearning-XSEDE systems, and OptiPortal with follow ups sessions for mathematics and other faculty members at JSU; 2) Organize CI Days events each year to provide opportunities for faculty and students to share information about CI resources and their use in research, present research posters, and OptiPortal demonstrations; 3) Invite at least 30 mathematics faculty from six HBCUs, K-12 and junior colleges to CI Days events; and 4) sponsor at least two mathematics faculty and students on field trips to High-End Computing (HEC) sites.

The activities are structured to serve as a forum for learning, discussion and exchange of information on the CDS&E driven undergraduate mathematics/statistics education guided by a combination of lecturing and hands-on activities in a CI lab. The CDS&E-based project modules approach to teaching mathematics and statistics emphasize creative and original applications in the use of CI technologies for visual analytic and collaboration. The success of it requires a sound educational background of both the faculty and the mathematics or statistics majors in the relevant biology, computer programming, and meteorology disciplines. The engagement of 28 students, mostly minorities, through research, faculty as mentors, and open CI Days events broadens both the CDS&E education and expanded awareness. The collaboration with Supercomputing Centers and HEC sites to gain access to collaborators of CDS&E will expose more students and faculty to CDS&E and contribute to increase in research productivity. Both faculty and students will present their research at professional meetings. The structure of LISA-QED and the BS in statistics will lead to significant curricula changes in both qualitative and quantitative academic disciplines.

National Science Foundation (NSF)
Division of Mathematical Sciences (DMS)
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Jennifer Slimowitz Pearl
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Jackson State University
United States
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