Abstract: Computational science curriculum developments and enhancements in liberal arts colleges can face unique challenges compared with larger institutions. We present a case study of computational science curriculum improvement at a medium sized liberal arts university in the context of cybersecurity. Three approaches, namely a cybersecurity minor, content infusion into existing courses, and a public forum are proposed to enrich the current computational science curriculum with cybersecurity contents.

Abstract: We describe an introductory data science course, entitled Introduction to Data Science, offered at the University of Illinois at Urbana-Champaign. The course introduced general programming concepts by using the Python programming language with an emphasis on data preparation, processing, and presentation. The course had no prerequisites, and students were not expected to have any programming experience. This introductory course was designed to cover a wide range of topics, from the nature of data, to storage, to visualization, to probability and statistical analysis, to cloud and high performance computing, without becoming overly focused on any one subject. We conclude this article with a discussion of lessons learned and our plans to develop new data science courses.

Abstract: Little Fe is a six node Beowulf cluster made from mini-itx motherboards. It is designed to be a low-cost portable parallel computer for educational purposes. Bishop's Theoretical Molecular Biology Lab at Louisiana Tech has reconfigured a Little Fe to model the lab's openSUSE based network. Our Little Susie boots each of its diskless nodes with the same openSUSE operating system installed on the lab's workstations. All nodes utilize a common home directory that is physically attached only to the head node. Thus Little Susie allows students to practice using, maintaining and administering a computer network that has all of the features and tools of the lab's research resources but without compromising lab workstations. In theory, our Preboot Execution Environment (PXE) solution supports installation of any live linux distribution on the Little Fe creating a family of Littles: Little Susie, Little Debbie, Litte Hat, Little Mints. The advantage of this approach over Little Fe's Bootable Cluster CD (BCCD) operating system is that each node of Little Susie has a complete linux distribution installed on each node. Little Susie can thus function as six independent linux workstations or as a Beowulf parallel computer. This approach allows instructors to set up a computational science teaching lab “on the fly” as follows: The instructor setups up a PXE server—head node. Students PXE boot their laptops at the beginning of class to obtain identically configured workstations for the lesson of the day. After saving the day's work to the instructors hard drive students restore their laptop to its native state by simply rebooting. Instructions for setting up a Little Susie and a parallel molecular dynamics simulation with NAMD/VMD will be presented.

Abstract: While already established in other disciplines, integrated degree programs have become more popular in computer science and mathematical education in Germany as well over the last few years. These programs combine a theoretical education and a vocational training. The bachelor degree course "Scientific Programming", offered at FH Aachen University of Applied Sciences, is such an integrated degree program. It consists of 50% mathematics and 50% computer science. It incorporates the MATSE (MAthematical and Technical Software dEveloper) vocational training in cooperation with research facilities and IT companies located in and nearby Aachen, Jülich and Cologne. This paper presents the general concept behind integrated degree programs in Germany and the Scientific Programming educational program in particular. A key distinguishing feature of this concept is the continuous combination of theoretical education at university level with practical work experience at a company. In this fashion, students end up being very well positioned for the labor market, and companies educate knowledgeable staff familiar with their products and processes. Additionally students are able to earn two degrees in three years, which is a rare approach for computer science programs in Germany. Therefore, Scientific Programming offers an important contribution towards reducing the shortage in advanced software development and engineering on the German labor market.

Abstract: Integrating data and models is an important and still challenging goal in science. Computational modeling has been taught for decades and regularly revised, for example in the 2000s where it became more inclusive of data mining. As we are now in the `data science' era, we have the occasion (and often the incentive) to teach in an integrative manner computational modeling and data science. In this paper, we reviewed the content of courses and programs on computational modeling and/or data science. From this review and our teaching experience, we formed a set of design principles for an integrative course. We independently implemented these principles in two public research universities, in Canada and the US, for a course targeting graduate students and upper-division undergraduates. We discuss and contrast these implementations, and suggest ways in which the teaching of computational science can continue to be revised going forward.