Computational Thinking (hereafter, CT) can be easily understood as “A way that humans, not computers, think…[it] is a way humans solve problems; it is not trying to get humans to think like computers.” (Wing, 2006, p. 35). Whilst this may seem like a contradictory definition, it broadly implies that CT within a school setting, entails students to develop their mental capacity to abstract problems and formulate solutions that can be automated (Yadav, Mayfield, Zhou, Hambrusch & Korb, 2014).

Within the classroom, students don’t even need to be introduced to what CT is prior to successfully engaging in tasks requiring it’s use. ‘Blockly’ for instance, is a self-explanatory way to introduce students to the key Computational concepts of decomposition (students break down the maze into smaller steps), pattern recognition (using tools such as ‘repeat until…’) and algorithmic design (creating a chain of instructions) (Google for Education: Computational Thinking, 2019).

Whilst the actual program is only directly related to Mathematical and Geographical concepts of direction and space, the Computational concepts grasped can be transferred to numerous subjects. For example, in English (EN2-4A)(NESA, 2012) – writing a whole narrative can initially seem overwhelming, but by decomposing it down into smaller parts (introduction, complication, resolution), tasks can suddenly feel more achievable.

I was excited to hear that my current supervising teacher recently taught a lesson using the following resource (‘Dog Coding’).

As technology has been a challenge to cooperate with in the class lately, this worksheet was an engaging introduction to CT, without even needing a screen! Whilst this resource alone was at an easy entry level for all abilities, adding a component where students create their own maze and trial each other’s, would have allowed an opportunity to extend more capable students, and would have encouraged various project ideas (Resnick, 2009).

With a strong visual emphasis and very little reading required – these two activities could be introduced as early as Year 1. Yet schools are introducing CT activities far later, naïve of it’s great potential to assist student’s confidence and persistence in dealing with complexity, tolerance for ambiguity, goal setting and communication skills in non-computer science disciplines (Yadav et al., 2014; Barr & Stephenson, 2011).

Understandably, many teachers (inservice and preservice) simply do not know how to strategically incorporate CT into their teaching content. In response, Hill et al., 2004; Yadav et al., 2014 and Barr Stephenson, 2011, urge to:

– provide preservice teachers with concrete examples of how to integrate CT into curriculum content (such as teaching units like EDUC362 – which in my opinion, should be compulsory)

– deliver professional development opportunities in developing CT in non-computer science disciplines

– have preservice and inservice teachers engage with computer scientists, experienced in CT.

References:

Feature image/gif – https://www.pinterest.com.au/pin/305541155967608836/?lp=true

Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: what is Involved and what is the role of the computer science education community? ACM Inroads, 2(1), 48-54.

Google for Education: Computational Thinking. (2019). Retrieved from https://edu.google.com/resources/programs/exploring-computational-thinking/

Hill, H. C., Schilling, S. G., & Ball, D. L. (2004). Developing measures of teachers’ mathematics knowledge for teaching. The elementary school journal, 105(1), 11-30.

NSW Education Standards Authority [NESA]. (2012). English K-6 Syllabus. Sydney, Australia: Author.

Resnick, M., Maloney, J., Monroy-Hernández, A., Rusk, N., Eastmond, E., Brennan, K., et al. (2009). Scratch: programming for all. Communications of the ACM, 52(11), 60-67.

Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. Available from: http://dl.acm.org.simsrad.net.ocs.mq.edu.au/citation.cfm?doid=1118178.1118215

Yadav, A., Mayfield, C., Zhou, N., Hambrusch, S., & Korb, J. T. (2014). Computational thinking in elementary and secondary teacher education. ACM Transactions on Computing Education (TOCE), 14(1), 5.