C2Exchange
Led by Ohio Supercomputer Center (OSC) and SURA, the NSF-funded Computational and Data Science Curriculum Exchange (C2Exchange) is a pilot to explore collaboration models to deliver undergraduate computational and data science curriculum, minors, and certificates with low investment. The exchange approach is intended to minimize the faculty preparation time required to deliver new and updated courses; and increase the number of computational and data science courses offered at the participating institutions. Although some strides have been made in integrating computational and data science competencies into the university curriculum, the pace of change has been slow, resulting in a critical shortage of sufficiently qualified students at both the baccalaureate and graduate levels. The C2Exchange takes advantage of national efforts to integrate computational and data science into the curriculum and applies distance learning technologies to enable stable computational and data science offerings at the academic institution partners. [NSF Grant 1829717]
Founding Partners:
- Bethune Cookman University, Raphael Isokpehi, Professor of Biology and Junell Mcall, Associate Director of Career Services
- Clark Atlanta University, Dina Tandabany, Associate Professor of Chemistry
- Southern University and A&M College, Rachel Vincent-Finley, Associate Dean for Academic Affairs in the College of Sciences and Engineering
- Morgan State University, Asamoah Nkwanta, Chair and Professor of Mathematics, and Ahlam Tannouri, Professor of Mathematics
- University of Puerto Rico at Mayagüez, Karen Ríos-Soto, Professor of Applied Mathematics
Administrative Partners:
- Ohio Supercomputer Center, Kate Cahill (PI), Education and Training Specialist,
- SURA
Advisors:
- Steve Gordon, Senior Advisor, The Ohio State University, Professor Emeritus in City and Regional Planning
- Lorna Rivera, External Evaluator
C2Exchange Courses: Contact Kate Cahill for access to the course materials.(kcahill) osc.edu
- Computational Chemistry and Molecular Modeling [syllabus]
- This 4-credit hour course is the lecture and lab to introduce the concepts of computational chemistry and molecular modeling and their applications in chemistry and biology. This course is mainly for upper level undergraduate students of chemistry and biology majors.
- Matrix Methods for Data Science and Machine Learning
- In this course, students will learn advanced linear algebra topics necessary for organizing information, analyzing large data, exploring machine learning techniques to build models and solve problems.
- Introduction to Modeling and Simulation
- This course infuses fundamental concepts of computational science into the undergraduate general education curriculum. It introduces the principles of modeling and simulation; progressive introduction of programming principles and skills using Python; application of programming skills to the solution of different classes of models. This is a 3-credit course with College Algebra as a prerequisite.
Outcomes: The external evaluation conducted with the participating academic institutions and faculty developing and offering C2Exchange Courses identified positive outcomes as well as lessons learned. The findings of Year 1, Year 2 and Year 3 have helped us to collectively envision an outcome of a pedagogical expertise exchange that is scalable using an inclusive excellence approach to develop a diverse, continuously needed scientific research workforce for creating, utilizing, and supporting advanced cyberinfrastructure in the United States. [2019 Evaluation Report] [2020 Evaluation Report]
Papers and Conference Presentations:
Building a Computational and Data Science Workforce, Katharine Cahill, Linda Akli, Tandabany Dinadayalane, Ana Gonzalez, Raphael D. Isokpehi, Asamoah Nkwanta, Rachel Vincent-Finley, Lorna Rivera, and Ahlam Tannouri, Journal of Computational Science Education Volume 13, Issue 1, April 2022
Infusing Fundamental Competencies of Computational Science to the General Undergraduate Curriculum, Ana Gonzalez, Journal of Computational Science Education Volume 12, Issue 3, Dec 2021
November 4 – 6, AAC&U’s 2021 Virtual Conference on Transforming STEM Higher Education, “Consortium Model to Broaden Access to Computational and Data Science Competencies” Workshop
March 2021, ACM SIGHPC Education Chapter Webinar, C2Exchange: A Collaborative Model for Expanding Access to Computational and Data Science Education, Presentation Slides, Recording
July 2020, ACM Practice & Experience in Advanced Research Computing 2020 (PEARC20), “Identifying Opportunities and Needs for Science Gateways in Education at Minority Serving Institutions” Birds of a Feather , Presentation Slides