A Framework for Learning About Big Data with Mobile Technologies for Democratic Participation: Possibilities, Limitations, and Unanticipated Obstacles

As Big Data becomes increasingly important in policy-making, research, marketing, and commercial applications, we argue that literacy in this domain is critical for engaged democratic participation and that peer-generated data from mobile technologies offer rich possibilities for students to learn a...

Full description

Saved in:
Bibliographic Details
Published inTechnology, knowledge and learning Vol. 18; no. 3; pp. 103 - 120
Main Authors Philip, Thomas M., Schuler-Brown, Sarah, Way, Winmar
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.10.2013
Springer
Springer Nature B.V
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:As Big Data becomes increasingly important in policy-making, research, marketing, and commercial applications, we argue that literacy in this domain is critical for engaged democratic participation and that peer-generated data from mobile technologies offer rich possibilities for students to learn about this new genre of data. Through the lens of what we term the paradigms of technology and cutting-edge content as an educational end, means, and equalizer, we explore how learning about Big Data with mobile technologies exists at the critical intersection of issues such as the purpose of schooling, global competitiveness, corporate profit, student agency, and democratic participation. These competing interests surface tensions at the classroom, institutional, and societal levels. Engaging these tensions, we offer a framework of student objectives for learning about Big Data with mobile technologies. Through a reflection on the challenges we continue to encounter as we attempt to implement innovative curriculum within the constraints of urban public schools, we hope to prompt dialogue and changes in practice with respect to what it means to learn for democratic participation using Big Data.
ISSN:2211-1662
2211-1670
DOI:10.1007/s10758-013-9202-4