The Left Hand of Data

Designing Education Data for Justice

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On sale Apr 23, 2024 | 212 Pages | 9780262547529
A speculative framework that imagines how we can use education data to promote play, creativity, and social justice over normativity and conformity.

Educational analytics tend toward aggregation, asking what a “normative” learner does. In The Left Hand of Data, educational researchers Matthew Berland and Antero Garcia start from a different assumption—that outliers are, and must be treated as, valued individuals. Berland and Garcia argue that the aim of analytics should not be about enforcing and entrenching norms but about using data science to break new ground and enable play and creativity. From this speculative vantage point, they ask how we can go about living alongside data in a better way, in a more just way, while also building on the existing technologies and our knowledge of the present.

The Left Hand of Data explores the many ways in which we use data to shape the possible futures of young people—in schools, in informal learning environments, in colleges, in libraries, and with educational games. It considers the processes by which students are sorted, labeled, categorized, and intervened upon using the bevy of data extracted and collected from individuals and groups, anonymously or identifiably. When, how, and with what biases are these data collected and utilized? What decisions must educational researchers make around data in an era of high-stakes assessment, surveillance, and rising inequities tied to race, class, gender, and other intersectional factors? How are these complex considerations around data changing in the rapidly evolving world of machine learning, AI, and emerging fields of educational data science? The surprising answers the authors discover in their research make clear that we do not need to wait for a hazy tomorrow to do better today.
Matthew Berland is Professor of Design, Informal, and Creative Education in the Department of Curriculum and Instruction and Affiliate Faculty in Information Studies, Computer Sciences, Educational Psychology, and Science/Technology Studies at University of Wisconsin–Madison.

Antero Garcia is Associate Professor in the Graduate School of Education at Stanford University. He has authored or edited more than a dozen books about the possibilities of literacies, play, and civics in transforming schooling in America.
Acknowledgments vii
1 Introduction 1
2 The Anonymity Spectrum 15
3 AnSpec Research Methodologies 33
4 Assessment Futures 47
Interlude: Assessment 65
5 Schools and Formal Learning Organizations 77
Interlude: Schools 99
6 Museums, Libraries, Informal, and Voluntary Learning Spaces 105
Interlude: Museums and Libraries 123
7 Games and Learning 131
Interlude: Games 147
8 Making, Creative Learning, Technocentrism, and Hope 153
Interlude: Making 167
9 Conclusions and Reimaginings 171
Notes 181
References 183
Index 191

About

A speculative framework that imagines how we can use education data to promote play, creativity, and social justice over normativity and conformity.

Educational analytics tend toward aggregation, asking what a “normative” learner does. In The Left Hand of Data, educational researchers Matthew Berland and Antero Garcia start from a different assumption—that outliers are, and must be treated as, valued individuals. Berland and Garcia argue that the aim of analytics should not be about enforcing and entrenching norms but about using data science to break new ground and enable play and creativity. From this speculative vantage point, they ask how we can go about living alongside data in a better way, in a more just way, while also building on the existing technologies and our knowledge of the present.

The Left Hand of Data explores the many ways in which we use data to shape the possible futures of young people—in schools, in informal learning environments, in colleges, in libraries, and with educational games. It considers the processes by which students are sorted, labeled, categorized, and intervened upon using the bevy of data extracted and collected from individuals and groups, anonymously or identifiably. When, how, and with what biases are these data collected and utilized? What decisions must educational researchers make around data in an era of high-stakes assessment, surveillance, and rising inequities tied to race, class, gender, and other intersectional factors? How are these complex considerations around data changing in the rapidly evolving world of machine learning, AI, and emerging fields of educational data science? The surprising answers the authors discover in their research make clear that we do not need to wait for a hazy tomorrow to do better today.

Author

Matthew Berland is Professor of Design, Informal, and Creative Education in the Department of Curriculum and Instruction and Affiliate Faculty in Information Studies, Computer Sciences, Educational Psychology, and Science/Technology Studies at University of Wisconsin–Madison.

Antero Garcia is Associate Professor in the Graduate School of Education at Stanford University. He has authored or edited more than a dozen books about the possibilities of literacies, play, and civics in transforming schooling in America.

Table of Contents

Acknowledgments vii
1 Introduction 1
2 The Anonymity Spectrum 15
3 AnSpec Research Methodologies 33
4 Assessment Futures 47
Interlude: Assessment 65
5 Schools and Formal Learning Organizations 77
Interlude: Schools 99
6 Museums, Libraries, Informal, and Voluntary Learning Spaces 105
Interlude: Museums and Libraries 123
7 Games and Learning 131
Interlude: Games 147
8 Making, Creative Learning, Technocentrism, and Hope 153
Interlude: Making 167
9 Conclusions and Reimaginings 171
Notes 181
References 183
Index 191