Learning About Big Data for Democratic Participation

• In Event: Distributing, Learning, and Making STEM Arguments in Public Media

Abstract

Objectives & Significance

Big data has recently garnered tremendous interest in the public media, the corporate world, and the STEM research community. Big data refers to large and complex collections of data, which are often comprised of multiple formats such as images, text, and audio. The enormity and messiness of these data require novel tools and methodologies for collection, analysis, visualization, and representation. From marketing to public health, and from national defense to education, people are turning to big data to better understand and solve pressing problems. However, the skills, knowledge, and technological capacities to carry out analyses of big data are increasingly concentrated in certain government and corporate entities, raising new questions about the ways in which big data will (re)shape democratic participation. This paper explores the unique challenges that emerge when teaching high school students about big data for democratic participation.

Theoretical Framework

Roth and Désautels (2004) argue that the literature on scientific literacy has largely focused on how knowledge and skills in science might be used by the citizenry to make informed democratic decisions. They highlight that this approach often sets scientific reasoning apart from other ways of knowing, which undermines true democratic participation. Roth and Désautels (2004) contend that “one must begin with the notion of an active and critical citizenry and then problematize science and technology in its service” (p. 3).Building on this perspective, we critically examine and re-envision the challenges that emerged during an implementation of a curriculum that attempted to teach high school students about big data for democratic participation.

Data Sources & Methods

The arguments developed in this paper are based on classroom observations and video-recordings of four urban high school classrooms that implemented a six-week curriculum to learn about the collection, analysis, and representation of big data as well as its implications for the students as individuals, for their communities, and for society at large. The data sources for this study also included student work and interviews with students and teachers. Employing Wetherell and Potter’s (1992) approach to discourse analysis, the corpus of data was analyzed for how knowledge about big data was discursively linked to democratic participation and decision-making by the teachers and students within the context of the curriculum.


Substantiated Conclusions

Both implicitly and explicitly, the implementation of the curricular unit promoted the idea that knowledge about big data will allow students to make informed decisions about issues that affect them and their communities. The discourse about data restricted the types of questions that students could explore and inadvertently reproduced deficit understandings of students and communities of color. The emphasis on making informed decisions based on STEM knowledge undermined other important analyses pertaining to issues such as poverty, immigration, and urban planning. Drawing on our findings that highlight the limitations of an approach that elevates STEM reasoning, we explore the possibilities of teaching about big data from a multidisciplinary perspective that begins with a notion of an active and engaged citizenry.

Authors

• Thomas M. Philip, University of California - Los Angeles

• Maria C. Olivares Pasillas, University of California - Los Angeles

• Janet Rocha, University of California - Los Angeles