Grover & Pea’s article introduces various definitions of computational thinking and explains how these definitions have developed and evolved over the years. The article then gives reasons for the legitimacy of computation thinking in K-12 curriculum and provides examples of CT implementation in schools.
The Sengupta article was more specific in the definition of computational thinking and gave ideas for integrating CT into a traditional science classroom. The author emphasized the importance of “design-based learning activities” in keeping with the “science as practice” mentality that ties back to our discussions of modeling. Sengupta emphasizes that computation can be used to teach basic science and math concepts such as graphing and rates, thereby integrating CT into lower level classrooms than previously thought practical, without taking additional time to carve out an additional class period. However, Sengupta also notes that CT can be expanded and complicated for those students who require a more advanced knowledge of computation. To whoever is reading this: did you notice how Sengupta gave Amanda a shoutout at the end of the article?!
Computational thinking is a valuable addition to school curriculum that provides students with a useful outlet to build conditional logic, algorithmic thinking, and abstract creativity. Today there are more and more jobs that are either solely computer science, or rely heavily on programming and general computer knowledge. I can speak from personal experience about the dangers of withholding computer education from students at the secondary school level. When I graduated high school, I did not know how to use Microsoft Excel, and entering into the biology major in college, I was expected to use Excel heavily for both data entry and statistical analysis. My grades suffered heavily from the burden of spending hours trying to extract information from a simple computer program that I could not use. As I learn more about computers and programming, I am more and more convinced that had I been introduced to CT at an earlier age, I probably would have pursued a CS major, or at the very least have been more prepared for the digital demands that 21st century science departments place on students. To not prepare students for this would be to ill-prepare them. Even if their future jobs do not involve programming, all students can benefit from the ability to think in a conditional, algorithmic, abstract and creative mindset.
The sad truth is, I don’t know the meaning to those key words I used in that last sentence (conditional, algorithmic, abstract) because I have such a poor CT background. This reading has been especially difficult for me because, unlike other science education concepts, this is one that I just cannot visualize, having no experience with the field.