Computational science is increasingly used to extend the capabilities and findings of scientific research. Computing has enabled scientific breakthroughs in molecular biology by breaking the genetic code, in atmospherical sciences by improving weather forecasting, in nanotechnology by simulating nano-devices, among others. In this way, computing has become “a third leg” in today’s methodologies of science complementing theory and physical experimentation. Computational simulations developed as research tools for experts could also function as learning environments for novices. Although progress has been made on research that examines students’ learning with computer simulations, less is known about instructors’ goals with regards to incorporating simulations in their teaching and student reaction to instructors’ uses of such tools for teaching and learning. Through a series of qualitative and quantitative research studies we attempt to understand how nanoHUB simulation tools are used as teaching and learning tools in science and engineering education.
Results of our studies reveal the vast potential of integrating computational simulation tools into formal learning experiences. Outcomes of our studies include: a) a set of learning outcomes associated with instructors’ goals for incorporating simulation tools into their teaching and b) a framework that identifies major benefits on students’ learning and that suggest ways to address their difficulties when using or building computational simulation tools. These outcomes provide a general model for using computational simulations as teaching and learning tools from the perspectives of instructors and students. These outcomes also provide guidelines on how to better design curricular materials that accompany simulation tools. Current implementations in the nanoHUB informed by our research findings and the future work will also be discussed.
Researchers should cite this work as follows:
Armstrong B071, Purdue University, West Lafayette, IN