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Computational Thinking

As I mentioned last week, although I love using tech in the classroom and am really excited about the opportunities to use it in the library space, I am not great at understanding how it actually works. Spending some time learning about coding and how to approach these hurdles was miles outside of my comfort zone, but in the long run, really useful!

Computational thinking, which breaks down complex ideas using a computer science approach, was an unfamiliar term to me. However, I think that a lot of teachers and librarians would recognize the underlying principals: breaking down a problem into parts, recognizing patterns, understanding principles, and creating steps to complete the task. These skills transcend the fields of technology, but knowing and thinking more about them really helped me overcome my mental barrier around technology and computer science.

I found algorithmic thinking, or breaking a problem into parts, the most helpful step to starting to learn to code. The Hour of Code project, which provides opportunities for students to learn basic coding languages, starting for just one hour. I tried out a project called “Code the News” that had me add graphics, text, color, and audio to a video clip; while I never would have thought that I would understand any of the language behind these additions, because each individual step was identified and explained, I picked it up fairly easily within the hour!

The second part, decomposition, or recognizing patterns, clicked for me once I saw the individual steps for adding and positioning a graphic or text on my video. This is one of the most important steps for teaching with technology, and for using it in the library, because it shows the learner how to start recreating the patterns or algorithms that they have learned to recognize.

Understanding the basic principles, or abstraction, gives the learner the templates that they need to be able to adapt their own ideas into a project. For example, in teaching students to use a 3D printer, many printers now come with basic projects loaded onto an SD card. Teaching students to recognize the patterns in code and how to break down the algorithms allows them to start to make small changes and see the effects. One drawback to this level of experimentation with 3D printing is that the users have to wait for a project to finish printing in order to find out if there are flaws that render it ineffective. Most printers include software modeling to help prevent this issue, but the supplies for the printers are not inexpensive, especially if they are being used for trial and error. Coding is a much less expensive way for students to practice abstraction- if something is incorrect in their code, the only real consequence is that the program does not function correctly.

The final piece of this type of thinking, pattern recognition, teaches students to understand real world thinking and learning applications of the skills that they have acquired. The can apply the skills not just in the one specific situation in which they have practiced, but across disciplines, both in and out of school. This level of abstract thinking is challenging for many younger students, but having low stakes opportunities to practice new skills and ideas is important in creating resilient learners.

Creating real items such as paper circuits may also be a strategy to reinforce concrete learning skills in students. Mirroring many elementary and middle school science and math curricula, STEM based learning can incorporate art with simple circuitry, allowing students to create light up art projects. This would require collaboration across the school- the classroom teacher, librarians who are responsible for the makerspace, and the art teacher all working together to promote this growth mindset.

This is a significant part of why makerspaces in school libraries are so important. Schools that allow students to make attempts, fail, and try again will produce students who understand problem solving, a critical skill for 21st century learners. As Samuel Beckett wrote in Westward Ho, “Ever tried. Ever failed. No matter. Try again. Fail again. Fail better” (Beckett, 1984).

References

Beckett, S. (1984). Westward Ho. New York: Grove Press.

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One thought on “Computational Thinking

  1. I loved your Samuel Beckett quote. Can you imagine changing the mindset that failing is a positive outcome and will not only drive instruction but create problem solvers, and students that think outside of the box.

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