Executive Summary (full paper, posted on etc journal can be found here)
The 2010 National Educational Technology Plan says “…technology is at the core of virtually every aspect of our daily lives and work…. Whether the domain is English language arts, mathematics, sciences, social studies, history, art, or music, 21st-century competencies and such expertise as critical thinking, complex problem solving, collaboration, and multimedia communication should be woven into all content areas.”
The US has, since the late 1990s, been trying to describe what a 21st Century education should look like. Futurists are trying to divine the skills that will be needed for jobs that do not yet exist, employing technologies that have not yet been invented. However, a careful look around can allow us to see many areas that have been virtually unnoticed by those who are focused on 21st Century Skills.
Supercomputing – sometimes called high performance computing – is not a new technology concept, but the supercomputers of 25 years ago were about as powerful as a cell phone is today, and likewise the supercomputers of today will be no better than a laptop of 10 to 15 years from now. As the world of the biggest and fastest computers has evolved and these computers have become increasingly available to industry, government, and academia, they are being used in ways that influence everyday life, from the cars we drive, to the food in our cupboards, to the movies we enjoy.
Supercomputing is not an end in itself, but rather the technological foundation for large scale computational and data-enabled science and engineering, or computational science, for short. It is a collection of techniques for using computing to examine phenomena that are too big, too small, too fast, too slow, too expensive, or too dangerous to experiment on in the real world. While problems with small computing footprints can be examined on a laptop, the grand challenge problems most crucial for us to address have enormous computing footprints and, thus, are best solved via supercomputing.
As a result, in order to be competitive as a nation, we need to produce knowledge workers in far greater numbers who understand both what supercomputers can do and how to use them effectively to improve our understanding of the world around us and our day to day lives.
The thinking about large scale and advanced computing has evolved, too. Today, we realize that, while not everyone will be using big computing in their jobs, they will need to understand the underlying concepts.
These concepts collectively are referred to as “computational thinking,” a means of describing problems and how to solve them so that their solutions can be found via computing (paraphrased from Jeanette Wing, Jan Cuny, and Larry Snyder). Computational thinking includes abstraction, recursion, algorithms, induction, and scale.
Our 21st century citizens, entrepreneurs, leadership, and workforce will be best positioned to solve emerging challenges and to exploit new opportunities if they have a strong understanding of computational thinking, how it applies to computational science, and how it can be implemented via high performance computing. These are true 21st century competencies that will serve our nation well.