Week 12: Computational thinking and how to get it in the classroom
This week the readings focused on the idea of computational thinking (CT). CT is a “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”. Which sounds complicated. If you break it down, it is basically what science research does. As a scientist, I formulate hypotheses, and then conduct experiments to study the hypothesis, while representing my findings using data processing and modeling. There is a strong push at the moment to teach this concept to students because the same techniques used in computer programming can be applied to STEM teachings. There are seven key points to computational thinking that focus around computing and programming being a creative process, by removing abstract ideas one can focus on what is relevant, by using data one can create knowledge, and by using algorithms, programming and digital devices one can solve problems. The final point is that computing can be applied to many different fields of thought, including the sciences, humanities, arts, medicine, engineering and business. I can definitely see how this would be beneficial for developing and fostering students as adept problem solvers. Most students don’t know how to address a problem or where to start when asked to solve a problem, by teaching students computational thinking skills they would be better modelers. There is a huge push right now in science research even, for more quantitative over qualitative research and computational thinking addresses this issue. By focusing on the data and removing the abstract, a scientist or student is better able to access a problem and work towards solving or just understanding it. The Sengupta paper focuses on how to get computational thinking, along with modeling, taught as the standard. They propose a framework for changing the K-12 science and math curriculum to focus on CT and modeling based techniques. The only issue I see if having such a heavy focus on computer based teaching/learning. For me, science is very hands on. I experience science in the real world and don’t want to focus on teaching in on a computer. I may use virtual labs in my classroom occasionally when there is no other option, but I don’t want that to be how I am forced to teach. So as much as I think the concepts of computational thinking can relate to science teaching, I don’t want the computational/programming/computer driven focus to take over.