The problem, however, is that many science concepts are related to things that are too small, too big, too complex, too expensive, or too dangerous to be built in the classroom realistically. (If you are a LEGO fan, you may argue that LEGO can be used to build anything, but most LEGO models simulate the appearance but not the function — a LEGO bike probably cannot roll and LEGO molecules probably do not assemble themselves. To scientists and engineers, functions are all that matters.)
Three approaches of using science models. |
A good solution is to have students design computer models that work in cyberspace. This virtualization allows students to take on any design challenge without regard to the expense, hazard, and scale of the challenge. If the computer modeling environment is supported by computational science derived from fundamental laws, it will have the predictive power that permits anyone to design and test any model that falls within the range governed by the laws. Software systems that provide user interfaces for designing, constructing, testing, and evaluating solutions iteratively can potentially become powerful learning systems as they create an abundance of opportunities to motivate students to learn and apply the pertinent science concepts actively. This is the vision of “Constructive Science” that I had dreamed about almost four years ago. This constructive approach opens up a much larger learning space that can result in deeper and broader learning–beyond simply observing and interacting with existing science simulations that were created to assist teaching and learning.
This dream got a shot in the arm today by a small grant awarded by the National Science Foundation. This TUES Type-1 grant will support a collaboration with Bowling Green State University and Dakota County Technical College to pilot test the idea of “Constructive Chemistry” at the college level. Choosing chemistry as a test bed to explore this Constructive Science approach is most appropriate, as chemistry is all about atoms and molecules that are just too small to make any design-based learning option other than computational modeling viable. Decades of research in computational chemistry has developed the computational power needed to make the science right. We believe that using these computational methods should yield chemistry simulations that are sufficiently authentic for teaching and learning.