Encounters beyond the interface: Data structures, material feminisms, and composition
This dissertation argues that data literacy should be taught in college writing classes along with other new media literacies. Drawing from several areas of study, this dissertation establishes a definition of data literacy, introduces a feminist methodological approach to Big Data and data studies, and makes a case for teaching data literacy in first year composition and professional writing courses as a foundational writing-related literacy. Information written into and read from databases supports research activities in any number of fields from STEM to the humanities; while different disciplines approach databases and data structures from diverse perspectives, all students need foundational data literacies. Nearly all digital environments are facilitated in some way by databases. They drive a range of web applications in ways that most users do not realize. On the surface, only GUIs are visible, and sets of data could be presented in any number of ways through them in the form of visuals, texts, and sound. It is important that students learn how data structures influence what comes across in the interface. By having students rhetorically analyze databases and then create them, composition teachers can help to demystify these ubiquitous yet invisible technocultural objects. Becoming aware of data structures gives students insight into how digital compositions emerge, empowering them to be more than “users” or “subjects” that use technological “objects.” Ideally, they would gain insight into how both “sides” of this encounter arise in dependence on many contributing factors, such as the standards, classifications, and categories perpetuated by techno-cultural infrastructures. Developing a socio-ontological methodology that combines scholarship in both feminist new materialisms and feminist rhetorical methodologies, this dissertation discusses the importance of researcher positionality. The socio-ontological methodology developed here expands on social constructivist theories to view all participants in a situation, including non-human ones, as mutually existing in dependence upon each other. Within this framework, contemplative mapping helps to articulate how the researcher does not exist outside of the research situation and assists in helping to make the situation uncanny, so that we can question assumptions and think through processes. Providing a foundational understanding of why data structures have become important to our professional and personal lives, this dissertation explains the public fascination with Big Data and exposes the ways that individuals can be affected by data collection practices, examining how the data structures that enable what comes across in user interfaces can be understood and taught in the context of writing studies.
Bay, Purdue University.
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