Contexts, critiques, and consequences: A discussion about educational data mining and learning analytics

The capture, aggregation, and analysis of student data is becoming ubiquitous at all levels of education—from primary to post-secondary—as institutions increase their adoption of information technologies to serve administrative and educational ends. In part, this has led to a growing interest among education scientists and administrators in strategically mining and analyzing troves of data in order to uncover student behaviors and intervene in student life. As is the case in other contexts where actors are pursuing Big Data's supposed benefits, educational data mining is fraught with moral, ethical, and political conflict. The panel is composed of four researchers who analyze and critique educational data mining practices and learning analytics initiatives in particular micro-and macro-contexts, including academic libraries and professional advising, urban schools, graduate-level online learning, and higher education generally. Each panelist also represents a unique conceptual background, pulling from work in information ethics and policy, critical data studies, documentation studies, and higher education policy to empirically analyze and critically evaluate tools, systems, practices, policies, and values. Through their individual but thematically intertwined perspectives, the panelists will present their research and lead audience members in discussion.