Significant resources have been directed towards K-12 computing and data education over the past ten years, as part of what has come to be known as the CSforAll initiative. This initiative has focused on raising awareness of computing education among parents and students, developing situated learning progressions that resonate with many different interests and pursuits, training teachers, and addressing issues of underrepresentation in computing among females and racial minorities. In this dissertation, I argue that as the CSforAll initiative continues to expand, it is important for the education community to also reflect on the forms of knowledge that are believed to be essential, and the presumed benefits of computing and data education. Specifically, how might the goal of producing citizens with robust computing and data literacies change what is considered to be fundamental to a computing education; as well as the kinds of contexts in which computing and data science are situated?
I use the term sociotechnical literacy to name this vision for computing education, which I define as a broad set of social and technical practices, strategies, ideas, and dispositions that can help people to reason about the computer-mediated systems that shape their everyday lives. As the term suggests, I argue that it is important for learners to engage with technical ideas as well as their social applications and implications. To examine what this might mean for teaching and learning, I describe two design experiments that I conducted with young people (ages 14 – 22). Each approach aimed to make the applications of computing primary (rather than treating applications as the backdrop from which the abstractions of computation are motivated), so that learners could examine some of the specific ways in which data and computing might be directed to particular goals, subject to real possibilities and constraints, and in relation to alternative forms of participation.
I examine the possibilities and limitations of each approach. I also analyze some of the assumptions that framed the design experiments – which were naïve, but also reflective of a broader ethos that pervades CSforAll. I reflect on what these studies collectively reveal about the possibilities, limitations, and risks of data and computing, as situated in the lives of young people; as well as what this might mean for helping young people develop a robust sociotechnical literacy. There are very real limits to what can be accomplished with computing and data alone. There are also significant benefits and risks associated with the many sociotechnical systems that shape our lives. As such, I argue that rather than positioning computing education as a remedy to various social ills, we instead offer young people a fair explanation of what computing is and is not capable of, grounded within specific contexts involving real people. I conclude with what this fair explanation might include, and how it might be fostered.
|Commitee:||Duguid, Paul, Gutiérrez, Kris D|
|School:||University of California, Berkeley|
|Department:||Information Management & Systems|
|School Location:||United States -- California|
|Source:||DAI-A 81/9(E), Dissertation Abstracts International|
|Subjects:||Information science, Educational technology|
|Keywords:||Computer science education, Data literacy, Data science education, Design experiment, HCI, Learning sciences|
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