TY - JOUR
T1 - Guest Editorial
T2 - Learning at the Intersection of Data Literacy and Social Justice
AU - Knight, Simon
AU - Matuk, Camillia
AU - DesPortes, Kayla
N1 - Funding Information:
We thank the set of authors and reviewers who have contributed to this special issue. The work originated in two symposia at the International Conference of the Learning Sciences (ICLS) with a wider group of participants and contributors (Arastoopour Irgens et al., 2020; Matuk, et al., 2020), to whom we are grateful for those initial discussions. We are particularly grateful to Susan Yoon, Alyssa Wise, and Golnaz Arastoopour Irgens for their support in developing the issue proposal. We also thank Keith Heggart at UTS for helpful discussions regarding justice citizenship
Publisher Copyright:
© 2022, Educational Technology and Society.All Rights Reserved.
PY - 2022
Y1 - 2022
N2 - With growing awareness of, and attention to, the potential of data to inform decisions across contexts, has come an increasing recognition and need to develop data literacy strategies that support people to learn to be critical of data, given this consequential nature of data use (and abuse). To achieve a just society, inequities in both capacity for data literacy, and the applications of data in society, must be addressed. A key aim is to create learning experiences that engage learners with issues of power and inequity, including those typically marginalized by data literacy education. In this way, data literacy and social justice learning goals are intertwined, and mutually supportive, in developing data literacy in learning about, through, and for social justice. This special issue assembles five empirical studies on learning at the intersection of data literacy and social justice, and that illustrate various approaches to intertwining data science and social justice learning goals. They moreover highlight the importance of the learning sciences as a perspective for understanding how people learn in specific contexts of data justice. This essay reflects on themes raised by these contributions, and offers a framework for conceptualizing the intersections between the learning of data literacy and justice.
AB - With growing awareness of, and attention to, the potential of data to inform decisions across contexts, has come an increasing recognition and need to develop data literacy strategies that support people to learn to be critical of data, given this consequential nature of data use (and abuse). To achieve a just society, inequities in both capacity for data literacy, and the applications of data in society, must be addressed. A key aim is to create learning experiences that engage learners with issues of power and inequity, including those typically marginalized by data literacy education. In this way, data literacy and social justice learning goals are intertwined, and mutually supportive, in developing data literacy in learning about, through, and for social justice. This special issue assembles five empirical studies on learning at the intersection of data literacy and social justice, and that illustrate various approaches to intertwining data science and social justice learning goals. They moreover highlight the importance of the learning sciences as a perspective for understanding how people learn in specific contexts of data justice. This essay reflects on themes raised by these contributions, and offers a framework for conceptualizing the intersections between the learning of data literacy and justice.
KW - Civics education
KW - Data justice
KW - Equity
KW - Mathematics education
KW - Numeracy
UR - http://www.scopus.com/inward/record.url?scp=85147020891&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85147020891&partnerID=8YFLogxK
M3 - Editorial
AN - SCOPUS:85147020891
SN - 1176-3647
VL - 25
SP - 70
EP - 79
JO - Educational Technology and Society
JF - Educational Technology and Society
IS - 4
ER -