Date:
Location:
“'As Close to Robot as Possible': The Making of Data Subjects in Higher Education"
Attend this event via Zoom (advance registration required)
Speaker:
Madisson Whitman, Postdoctoral Research Scholar; Assistant Director of Co-teaching, Center for Science and Society, Columbia University.
Contact:
Emily Neill
erneill@hks.harvard.edu
Co-sponsored by Harvard STS and the Weatherhead Center for International Affairs.
This event is online only. Please click the "Read More" link for full instructions on how to attend this seminar.
Remote Access Information:
To join by computer:
https://harvard.zoom.us/meeting/register/tJModOmsqjosGdIGnb3dN-gR8SRMXRpau_VT
Please note: This event requires registration in advance in order to receive the meeting link and password.
Abstract:
Predictive modeling projects in higher education in the U.S. have contributed to a proliferation of student data, which universities increasingly use to predict and intervene on graduation and retention outcomes. Some of these interventions are student-facing. Data visualizations and nudging, for example, prompt students to be more productive and manage their time more efficiently. In this talk, informed by ethnographic research on the development and deployment of predictive modeling at a large public university in the U.S., I ask what kinds of data subjects are produced through modeling efforts. In particular, I focus on the rendering of students as primed to become, as one student put it, “as close to robot as possible” through visions of what students could be if they acted on their data.
