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It’s Time to Graduate Beyond STE(A)M and Coding

By Matt Harris
It’s Time to Graduate Beyond STE(A)M and Coding

We have been talking about STEM (Science Technology Engineering Mathematics) and coding as critical literacies for the modern student. Schools around the world have invested heavily in STEM programs and centers—now STE(A)M, with the inclusion of the Arts—creating new teaching jobs to focus the curriculum on these vital areas of learning. Coding has become the buzzword of 21st-century learning, where every student is seen to need coding knowledge to thrive in the modern workplace. We have coding clubs, Hour of Code, Coding 4 All, and of course integration of coding into courses across the curriculum, not just in the STE(A)M subject areas. One wonders: are these programs having the desired effect of building intrinsic technical skills among students that will be used in university and beyond? My travels and experiences have shown the answer to be… maybe. But we can do better. The challenge of focusing on STE(A)M and coding in the current iteration I see applied in schools is too discrete. When taken at face value, STE(A)M is simply a collection of subjects we have been teaching for decades. Coding is merely the exercise of learning a language, albeit one that follows a more rigid syntax than natural languages. On the surface, these areas are neither special nor transformative. They teach discrete knowledge, which has been effective in developing technical skills in students at many schools. Yet, the approaches I see at most schools, especially well-resourced ones, are immature in their understanding of the learning value of STE(A)M and coding. As a result, I recommend that schools graduate their programs to focus on the skills and knowledge inherent in STE(A)M and coding that are most valuable for students as they transition out of K–12 education: innovation and computational thinking. At its heart, STE(A)M speaks to the value of technical subjects in addressing problems and improving material conditions. The value is not in learning the technical skills themselves, as that could be seen vocational learning; rather it is in the application, combination, and transference of those skills to other situations. In short, innovation. Students need to learn how to take attained skills and knowledge and apply them to unrelated tasks. Therein lies the true value of learning about the Sciences or Mathematics. The simple exercise of learning how to map an ecology in Biology is not useful outside of Biology, but to use that skill in the mapping of an ecosystem of interrelated political systems to bring about governmental changes is invaluable. Coding, similarly, has little value as an area of study in isolation. By itself it only teaches the rules, operators, and syntax of a language no differently than learning a spoken language, such as Mandarin. The way I most often see it taught, students learn coding so discretely that they don’t benefit from intended impacts on higher-order thinking and problem solving. Computational thinking, or the focus on systemic problem solving, has far-reaching implications for contemporary students, from greater understanding of our information-based society to the logical and algorithmic skills often needed to address large-scale tasks. As part of a larger effort to teach computational thinking, coding is a critical partner. You might think of coding as being akin to teaching students Mandarin, whereas computational thinking would be the study of China and Chinese culture. Beyond missing the core value of these subjects, when schools focus heavily on the technical aspects of STE(A)M and coding without contextualizing, learning potential is limited to a subset of academic subjects. Shifting the focus to innovation and computational thinking allows learning to influence all areas of a student life. For example, innovation can come in the form of social endeavors or physical environments, where the knowledge gained from STE(A)M learning can be transferred away from Engineering and Technology. Similarly, computational thinking can address environmental issues or provide greater insight into communication norms through the rules and interactions found in coding. However, to draw upon these valuable skills, schools need to be intentional in designing or reconfiguring these programs. School leaders should identify learning outcomes already achieved and use those as a basis for creating new approaches. In the place of STE(A)M centers, we should create Innovation Hubs. Rather than impose coding courses, we should implement computational thinking components in all areas of the curriculum, connecting all learning through this universal skill. Finally, we need to consider the inherent failure of STE(A)M and coding programs to address all students. While I find it admirable that so much work is being done to bring girls into these fields, it is troubling that we need to do so in the first place. Perhaps with innovation and computational thinking—both of which are skills and not discrete knowledge—schools will be better equipped to offer future-ready educational programs that are engaging to every student, regardless of their interests or background. [email protected]

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