Data models are very common on the Internet. For instance, geographic information system (GIS) software such as Google Earth are driven by a data model that is linked to location (x, y, z). These data are static--they were generated from land surveys and remain unchanged until the next update. Another example is the protein data bank that contains tens of thousands of structure data of macromolecules obtained from crystallography. The structure data are coordinates (x, y, z) that define the positions of atoms in macromolecules. These data are static, characterizing stable conformations of macromolecules.

Nature is not static, however. Our world is fundamentally dynamic. It is full of many different kinds of processes--creep, flow, growth, explosion, flying, and so on. We live in a four-dimensional world (x, y, z, t), not a three-dimensional one (x, y, z). Modeling the four-dimensional world is the domain of process models. Simulations are computational methods to study process models. Simulations can not only be used to reconstruct what has happened, but also be used to predict what will happen.

Simulations lend great power to science education, because they can show important processes to students and be manipulated by them to explore causality. If a picture is worth a thousand words, a simulation is worth many thousand pictures. The salient, dynamic nature of a simulation presents a much better learning experience than didactic instructions with static illustrations. Unlike a movie or an animation, an interactive simulation is not premade or scripted--it is computed in real time and can respond to the user's interactions in many different ways. This is a significant advantage of a simulation over a movie and an animation. If you are watching a movie, you cannot change the plot. If you are interacting with an animation, you probably have a number of limited, exact outcomes depending on the combination of preset rules. But if you are playing with a simulation or creating a new one, no one can predict exactly what results you will have. Simulations can exhibit a similar degree of variety and diversity that we observe in our world.

More importantly, if a simulation is built using first principles, such as Newton's Laws for classic mechanics, the Schrödinger equation for quantum mechanics, the Navier-Stokes equation for fluid dynamics, the Maxwell equations for electromagnetism, and so on, it will not only deliver the most important insights of science, but also open up countless opportunities for students to explore, as many phenomena can essentially be explained using applicable first principles. Now that ordinary computers are powerful enough to perform sophisticated calculations (with multicore computers this is even so), science education has an unprecedented opportunity of revitalization. The next generation of electronic textbooks could well be powered by smart simulations using exactly the same scientific and computational methods used by professional scientists and engineers in their discovery and problem-solving. Wherever you see a static illustration or a movie clip in an electronic textbook today, you will see accurate, interactive simulations tomorrow. Your electronic textbooks will have powerful computational labs integrated within them.

The Molecular Workbench software represents a decade-long effort towards this vision. Help yourself with hundreds of premade simulations delivered through it, and explore how they may help you teach and understand the power of simulations.