Into the Black Box of Computational Thinking

Jalyn Marks

Yet again in this course, I’ve come across another black box that even I, the English major, from the land of “Are You Going to be a Teacher?” and the land of soft skills galore has been open to explore. The accepting tone of Wing’s “Computational Thinking” article (2006) greets the reader with a warm welcome: “Computational thinking is a fundamental skill for everyone, not just computer scientists.” Wing describes the relationship between computers and humans similarly to W. Brian Arthur in The Nature of Technology: “…technologies are shaped by social needs; they come often from experience gained outside the standard domain they apply to” (2009). Like Arthur, Wing states that the ways humans think about and solve problems (read: soft skills!) is mirrored in computational thinking. “[Computational thinking] is not trying to get humans to think like computers” (Wing 2006). Instead, it uses things like planning, learning, and scheduling to meet various social needs.

Evans describes computational thinking not only as something everyone should have access to, but as something that can serve as a “the ultimate mental amplifier” when problem solving (2013). According to him, computer science is interdisciplinary, attributing to its multi-use, multi-user flexibility. When using the Linked-In Learning course on programming, I found–much to my surprise–that coding was fairly intuitive to me, in more ways than one. Most closely, coding is like like poetry; the semantics of a sestina about nostalgia compared to a villanelle about nostalgia might be similar, but the the syntax will always be different. Different poem structures elicit different poetical affects.

As fun as it would be to go into affect theory now, I’m going to shift this essay to my current academic pursuit: Disability Studies. How is computational thinking relevant to the disability world?

There are several starting points I could use (all ideas derived from Evans 2013):

  • Coding executes problems in a faster, shorter way than typing everything out.
  • Universality is the pinnacle value included in universal design (UD).
  • Abstract ideas are concretized in coding.
  • Coding is a textual language and not a natural language. For those who do not use, unreliably use, or minimally use natural language, is textual language more or less accessible? Without much research, my intuition is telling me that yes, textual language is probably more accessible (given my limited interactions with the “Spelliverse” and I-ASC community).
  • Clear rules are helpful to people who like them and challenging for people who don’t. (E.g. Stereotypic that autistics like rules, stereotype that people with developmental disabilities and some behavioral disabilities have trouble following rules)
  • “Anyone who is able to master the intellectual challenge of learning a language… can become a good programmer” (Evans 2013).

Lastly, an original poem/some code:

title = “Python”

num = 26
age = num
age = years_it_took_me_to_learn_Python

if num % 6 == 0:
print(num, “is divisible by the number of lines per stanza in a sestina”)
print(num, “could be lines of a free verse”)

6 != 26

>>> I = 26
>>> Y = 6

NameError: name ‘Y’ is not defined

>>> I == 26

>>> 6 * (26==6)

print(“Next time, I’ll rhyme.”)



Arthur, W. B. (2011). The nature of technology: what it holds and how it evolves. Free Press.

Evans, D. (2013). Introduction to computing: explorations in language, logic, and machines. Creative Commons.

Wing, J.M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-45.