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In Event: Transformative Practices in Higher Education: Promoting Data Literacy, Collaboration, and Criticality Online
Not long ago the advent of social media was greeted with uncritical enthusiasm, but today the tide has turned, as societies, organizations, industries and individuals come to grips with unexpected threats to privacy, identity, and truth. In the context of higher education, universities’ fascination with data mining and predictive analytics has likewise given way to concerns about ethical challenges surrounding big data (Johnson, 2014). We explore in our research, which included both building an app and assessing students’ uses of it, how the potential of data analytics might be harnessed by students themselves.
Studying the use of digital tools in a university setting and its networked environments requires the analysis not only of individual students’ learning, but the sociomaterial systems that mediate those activities. Building from Vygotsky (1978) and Latour (2005), we define sociomaterial systems as the human and nonhuman actors, including digital tools and data, that comprise an activity in a particular institutional space and the relations and effects that flow from their intersection (Author, 2018).
Methods and data sources
Over the last four years we designed, implemented, and researched a set of digital tools for university classrooms meant to afford creativity, curation, and collaboration, as well as to recenter student knowledge production and agency. Through mixed-method analysis, we analyzed the following data sources from two course semesters to study usage of a student-facing analytics tool, the Impact Studio: 1) mass click data, 2) survey responses, 3) student work, and 4) interviews.
Our findings suggest that tools which give access to data visualizations of online work are still unfamiliar to students, whose digital literacy practices both in and out-of-school rarely require them to analyze such data or envision their use.
Students used our student-facing analytics tool in multiple and often unanticipated ways—for example, as a way to create a sense of belonging with others or to shape their own design processes via peer feedback—while others ignored the tool entirely.
There was variation in students’ responses to the visibility the tool gave to their own and their peers’ participation. While some students appreciated an increased sense of involvement and presence in the course that they attributed to the tool, others worried about their participation data being collected and visualized, even for their own use.
Our work highlights the potential and challenge of leveraging big data in ways that are ethical, transparent, and aligned with educational objectives. Our analysis of students’ use of the tools provide one instance of how student-facing analytics might be implemented in higher education, with an emphasis on giving students access to information about their own online participation and contributions. But for students to experience “the power to know” (Student interview, 5.8.2019), educators will need to be attentive to how new tools can become legitimate actants in the complex sociomaterial system of the university classroom.