Tuesday, November 10, 2015

Computational thinking and how to get it in the classroom

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.  


  1. I like the tie-in to real-world science and problem solving. I remember the first few times I tried to do programming for a course I felt like I didn't know where to begin. My teacher wasn't very good, so I didn't advance as far as I probably should have, but I at least knew where to start. Another thing that programming teaches students is to be creative in their problem solving. I can't tell you how many times I hit a snag on a programming project for one of my classes and ended up having to find some weird solution to get around it. As for your concerns about sitting in front of a computer, one of my friends from undergrad, who majored in electrical engineering and took several programming courses, told me that his best programming teachers never started at the computer. Instead, they started at the board and mapped out how they would attempt to solve the problem. Only when that was done did they move to the computer and start translating their solution into a programming language. If you decide to incorporate it into your classroom you could attempt to do it that way. Another possibility is to bring out the programs when you're looking at something that is very difficult/impossible to study in the lab, such as evolution or ecology.

  2. In this information/technology age, the concern that our computers and fancy gadgets could start to blot out the hands-on or relational aspect of pretty much anything is a very legitimate concern. What I think this means for us is we, as teachers, have to point our students in the correct direction AS we teach CT--keeping student's perspectives ordered, knowing that CT is only to stand in for what truly constitutes the 'stuff' of science. There is no replacement for the 'stuff' of science. And this is why the CT incorporation, I think, ALWAYS needs to come alongside the hands-on interaction with science as well, whether it is using data the students themselves gather, translating the qualitative observations to quantitative, etc

  3. I also agree with you that science is very hands-on and I don't think every topic applies equally well to the use of computer programming. Maybe focus its use in techlabs and other more engineering-driven settings?