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.
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ReplyDelete^Had a typo...
ReplyDeleteI agree with your last statement! I have always said I wish I knew more about computer programming and these readings really drove that home. So as I like the idea of adding this to science education, I am hesitant that it will overshadow more hands-on, lab based, learning.