Journal Summary

Elements of Computational Science and Engineering Education

By : Osman Yasar & Rubin H. Landau

Abstract

The past decade has witnessed extraordinary advances in science and engineering that were fueled, in part, by dramatic increases in the power and pervasiveness of computers and communications. We have capitalized on those advances by developing techniques for modern computers that let us better understand systems with ever-increasing complexity and realism.

Definition of Computational Science and Engineering (CSE)

Computational science and engineering (CSE), or computational science for short, in several ways. Sometimes it denotes the multidisciplinary combination of computational techniques, tools, and knowledge needed

Value of CSE in Research

Generally, most scientific disciplines appear to be benefiting CSE from computer modeling, analysis, and visualization. In fact, the newfound and widespread importance of computation has shifted the paradigm of scientific research to include simulation, along with experiment and theory, as a fundamental technique of science. Simulation and visualization allow us to acquire insights into real-life problems that are too complex or difficult to study analytically, or too expensive, big, small, or dangerous to access experimentally. For example, simulations permit us to study the fuel density, ignition energy, and heat waves in a combustion chamber at temperatures above 3000 Kelvin, the configuration of gluon flux tubes between quarks within the proton, and the possible orbits for earth–asteroid collisions. 

Nature of CSE Education

Due in part to reports and grants from the federal government, education in science and engineering has responded to the advances in computational science. In 1989, the Office of Science and Technology Policy challenged the educational system to (1) increase the supply of students prepared for careers in science, technology, engineering, and mathematics; and (2) improve the scientific, mathematical, technological, and computational literacy of all students.

The traditional teaching of science tends to focus on theory. In contrast, CSE education offers an understanding of science through the computer applications of mathematical models. It teaches science via the method of inquiry in which the computer serves as a virtual laboratory that simulates nature. To aid in the inquiry, facts are presented as needed rather than as individual objects to memorize. As a consequence of its problem-solving nature, the CSE view complements the traditional teaching of science and mathematics. It also makes many

science and mathematics concepts more easily accessible to students who may otherwise

not be reached; for example, those students not interested in computer hardware, software, and algorithms for their own sake [29]. In addition, CSE enriches the science

curriculum by extending the examples used in education to include problems that may

not have analytic solutions, thereby extending the range of problems open to study

 Stages of CSE Education

First stage appear 1989-1990, was recognition-conception, in which practitioners recognized that they were doing something new—but not necessarily well. The second stage of CSE education, ca. 1990–2000, was infancy in which the ideas of CSE started to be taught in a few existing or new courses, often by those who were familiar with the ideas through their research. The third stage, ca. 2000–2010, is early growth. It is the stage we are in now and is characterized by a number of courses and curricula being designed and implemented at both the graduate and undergraduate levels. While we expect the future adult stage of CSE education to resemble what we have now, it is hard to make reliable predictions in the midst of rapid change.

Summary and Conclusions

So, the conclusion is, while there appears to be general agreement that it is appropriate to teach CSE at the graduate level, an undergraduate education in CSE is still a new thing. A decade ago, a widely held view was that undergraduates should view computational methods as just “black boxes” that should remain closed [65]. However, we believe that the pervasiveness and importance of computation throughout all of science and engineering means that even undergraduates should be able to enroll in programs that teach them what’s going on inside the black box. Time will judge the viability

of these programs.