This week’s “Codecademy” assignment, along with the readings, served as yet another helpful stop along the way to better understanding semiotics and cognitive technologies. It seems like everything we have read before this point has led us here, and while I had absolutely no experience in coding before this week, it suddenly seemed less intimidating than it has always appeared to be in the past.

Out of all of the reading that we’ve done this semester, all of the pieces that have covered cognitive technologies seemed to jump out at me this week as I got started on the Python coding process. It is evident, as I practice this very basic introduction to coding, that computers – and so much of our life – run on a set of codes and symbols.

For example, I enjoyed learning how to do simple math equations on Python. Although the language is slightly different from what I know, the outcome is the same. Regardless of the symbol used to show that something is “equal” or “true” or “false,” the actual outcome of the process remains the same. This process takes me back to learning any other foreign language. When I took Spanish classes in high school and college, “I want two pieces of pizza” looked a lot different in English than it did in Spanish. The sentences were structured differently, and entirely different words were used to express the desire. However, the outcome remained the same, so long as someone knows how to translate between the two languages.

Thus, when I was following along to the Python lesson, I was reminded that although the way of computing on the screen looked & seemed very different than the way that I compute things in my head, there was a visible correlation. In “Computational Thinking,” Jeanette Wing mentioned that computational thinking is parallel processing – code is interpreted as data, and data is interpreted as code (33). This statement was made very clear as I, followed by the readings, worked on Python. As Subrata Dasgupta mentioned in “It Began with Babbage, computation is associated with the process and activity of human thought (11). While many of our readings have stressed this idea in weeks past, it wasn’t until I logged on to Codecademy that it all began to really make sense.

It may sound naive, but as I worked on the Python training, I couldn’t help but think that the coding process could be simplified; like it has somehow become harder than it needs to be. Obviously, I have very little experience with coding. However, I did become easily confused with all of the symbols that meant something very different than what I know them as in everyday life (for example, the = sign). While human language has been around for centuries, coding language still seems relatively new. Who exactly placed new meanings on these various coding symbols, and why were they chosen in particular? Obviously, there are various coding languages, and coding in general has evolved over time. However, I’m still interested in further discussing why computation and coding happens the way that it does.

References:

Wing, Jeannette. “Computational Thinking.” Communications of the ACM 49, no. 3 (March 2006): 33–35

Dasgupta, Subrata. “It Began With Babbage: The Genesis of Computer Science.” 2014. Oxford University Press.