This week we will be talking about computational thinking. As Jeanette Wing describes it, computational thinking is the “thought process involved in formulating problems and their solutions so that the solutions are represented in a form that can be effectively carried out by an information-processing agent.” I thought this description perfectly defines the scientific practices that we’ve been learning all semester. It applies to the practices because first the students have to identify a problem, identifying necessary parts through the process of “abstraction” where they learn to think like experts in peeling away superficial features to put only relevant and important elements into programming. From that students can try to make a model through programming to make sense of data and then make their own representation from their outputs. I think computational thinking could be a really good complement to science learning, especially in situations such as learning about kinetics or ecological systems as described in the article. Personally the only sort of computer programming I’ve done was AP computer science in high school where we worked with C++, a programming language. It was text-based and very abstract and while it helped us think more logically, it felt like an end to itself instead of a means to help us understand more about other subjects, such as science. In essence it was not very cross-disciplinary. However, I question how to integrate computational thinking into a science classroom. I have not used any of the programs described in the articles, so I don’t know how much of it consists of “true” programming versus plugging in variables and adjusting sliders. I wish the articles had given us an example of computational thinking forming a part of a science classroom in a more practical, day-to-day sense. However, the idea of it is very attractive to me indeed.