Creating Science Simulations Through Computational Thinking Patterns

Computational thinking aims to outline fundamental skills from computer science that everyone should learn. As currently defined, with help from the National Science Foundation (NSF), these skills include problem formulation, logically organizing data, automating solutions through algorithmic thinking, and representing data through abstraction. One aim of the NSF is to integrate these and other computational thinking concepts into the classroom. End-user programming tools offer a unique opportunity to accomplish this goal. An end-user programming tool that allows students with little or no prior experience the ability to create simulations based on phenomena they see in-class could be a first step towards meeting most, if not all, of the above computational thinking goals. This thesis describes the creation, implementation and initial testing of a programming tool, called the Simulation Creation Toolkit, with which users apply high-level agent interactions called Computational Thinking Patterns (CTPs) to create simulations. Employing Computational Thinking Patterns obviates lower behavior-level programming and allows users to directly create agent interactions in a simulation by making an analogy with real world phenomena they are trying to represent. Data collected from 21 sixth grade students with no prior programming experience and 45 seventh grade students with minimal programming experience indicates that this is an effective first step towards enabling students to create simulations in the classroom environment. Furthermore, an analogical reasoning study that looked at how users might apply patterns to create simulations from high- level descriptions with little guidance shows promising results. These initial results indicate that the high level strategy employed by the Simulation Creation Toolkit is a promising strategy towards incorporating Computational Thinking concepts in the classroom environment