Computational thinking, computational participation

Computational thinking represents an excellent starting point, the broader conception of "computational participation" better captures the twenty first century reality. Computational participation moves beyond the individual to focus on wider social networks and a DIY culture of digital "making".

In 2006, computer science professor Jeannette Wing coined the term computational thinking in a short essay that was published in communications of the association for computing machinery, the monthly journal of the world's largest professional organisation for computer scientists. She defined computational thinking broadly as all "aspects for designing systems, solving problems, and understanding human behaviours" that highlight the contributions of computer science. She argued that understanding the world computationally gives a particular lens to understanding problems and contributing to their solutions. Computational thinking is often associated solely with computer science, but it applies computer science principles to other disciplines to help break down the constituent elements of any problem, determine their relationship to each other and the greater whole, and then devise algorithms to arrived at an automated solution. Computational thinking is not limited to mathematics and the sciences, and it does not necessarily involve the use of a computer.
Jeanette Wing's essay on computational thinking provoked a wide range of responses within the computer science community and beyond. Members of a discipline often begin to define its essence by discussing its core ideas and contributions. But the effects of computational thinking have reached far beyond the boundaries of academic computer science, and it has become a catch-all term for what understanding computer science, and it has become a catch-all term for understanding what computer science can contribute to the increasing digital world in which we live. These discussions on computational thinking also noted that technology courses that teach only word processing and presentation software do not engage students in the deeper analysis needed to think creatively and critically with digital media. They also made clear that most young people know little about computer science as a discipline or the ways that they can apply it to their own daily lives. In short, computational thinking has become the rallying cry for those who study what youth need to know about computer science and what it means to think systematically about solving all types of problems, big and small.

Computational thinking has progressed since Jeanette Wing's 2006 article. What started as a concept now exists in curricula and pedagogy in K-12 schools and school based clubs across the country. Although computational thinking offers a framework for how to use technology more rigorously and critically in schools, there also remains a question of outcome. Teaching children to think more rigorously and critically is an admirable goal, but it is hardly a new one. Many curricula (in Ancient Greece, philosophy and rhetoric; in the nineteenth century, Latin; and in the twentieth  century, computer programming) were intended to develop more rigorous critical thinking. And despite the fact that many K-12 schools have had the machines for over 30 years, little progress has been made in programming education.

Those who would like to return programming to schools need to articulate an argument that extends beyond the common desire to make children more rigorous thinkers. Learning how to think is an admirable goal, but it is a limited conception of what programming affords young learners. If programming is promoted solely as a more effective way to think (and not as an effective way to communicate logically and creatively), then we will again fail to understand what teaching and learning code can afford us in a networked age. learning to code ultimately manifests it's worth when it increases an individuals capacity to participate in today's digital publics. Programming is a form of expressing oneself and of participating in social networks and communities. Through the book, they argue that computational thinking needs to be thought of as computational participation because the computer programs that are being created, used, repurposed, and shared have become our social connections. This view of code as connected has implications for how programming is learned, what is being designed, and where it is being shared.

The development of creative and critical networks to share information and ideas stand as the model for students who wish to create a more collaborative and open society. It is not enough to be "hanging out" on the computer and "messing around" on occasion, as media researcher Mizuko Ito and colleagues discuss in their 2009 book on youth engagement with digital media.  Referring to a third category as "geeking out", Ito and her colleagues note that few youth engage in such activity and that such engagement with technology is rarely found in schools. Computational thinking represents schools' attempt to remedy this lack of engagement and provide students with the concepts and skills that will allow them to solve problems algorithmically. Computational participation focuses on the practices and perspectives that are needed to contribute within wider social networks, including but not limited to schools. within the wider network of creative and critical thinkers, educators have the chance to take the "geek" out of "geeking out" and set new academic and social norms for what it means to use technology meaningful.

The near lack of computational participation in any introductory technology based coursework means that few students consider computer science principles or even encounter computer science at any point in their K-12 education.

Connected Code, why children need to learn programming, Yasmin b. Kafai and Quinn Burke. 2014