SECANT: Science Education in Computational Thinking

SECANT is a community building project funded through the NSF CPATH (Pathways to Revitalized Undergraduate Computing Education) program1). The goal of SECANT is to bring together scientists who recognize that computer science has become indispensable to scientific inquiry and is set to permeate science in a manner that is transformative, changing computing from a service discipline for the sciences into a fundamental paradigm for science in general. The effort complements Purdue's recently adopted College of Science curriculum, which includes a requirement that all science students take at least one course in computing and at least one course giving a multi-disciplinary experience.

The project consists of two main components: new course development and annual workshops. Led by Susanne Hambrusch from Computer Science, the multidisciplinary team consisting of Chris Hoffmann (CS), Tony Hosking (CS), Tim Korb (CS), Mark Haugan (Physics), Olga Vitek (Statistics and CS), and Sabre Kais (Chemistry), will design a two-course sequence introducing science majors to computational thinking, to the parallels between computational concepts and scientific models, and to the role of computation in exploring and understanding of physical phenomena. The first course “Introduction to Computational Thinking” is currently being developed and will be offered in Spring 2008. It will introduce science majors to computational thinking via basic programming concepts, data and data management concepts, simulation, and visual interaction. The course will use Python and VPython and will be coordinated with material on computational physics currently covered in PHYS 172. A second course “Computation and Scientific Discovery” to be developed within the projects will allow science students to satisfy the multi-disciplinary course requirement.

The first SECANT workshop was held on November 15 and 16, 2007. The second SECANT workshop was held October 30 and 31, 2008. A third workshop is planned for 2010.

1) This material is based upon work supported by the National Science Foundation under Grant No. CCF-0722210. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.