Toward Culturally Sustaining Data Inquiry

• In Event: Principles for Educational Testing, Data Inquiry, and Classroom Assessment to Support Culturally Sustaining Ecosystems

Abstract

During the past decade, data inquiry has been at the forefront of school change efforts and interventions aimed at improving the teaching and learning of nondominant groups of students (e.g., students of color, low-income students, students with disabilities, English Language Learners, etc.). While data inquiry cycles in schools have importantly helped educators, administrators, and policymakers recognize disproportionate teaching and learning outcomes, the lenses used to interpret these gaps (e.g., deficit and colorblind) can also have detrimental effects on nondominant students and their families. The absence of critical perspectives in data inquiry contributes to persistent gaps in opportunity and outcome. Take mathematics as a content-specific example where frames of colorblindness often decouple racial gaps in achievement from critical analyses of how everyday racialized experiences and organizational structures shape access and opportunity in mathematics.

Mathematics has long been seen as race-neutral or separate from humanity and intimacy; however, math is a racialized experience. Studies have found that teachers of Black and Latinx students can place an overemphasis on monitoring behavior, resort to more teacher-centered and rote forms of mathematics learning, and frequently use exclusionary and isolatory discipline practices (Battey & Stark, 2009; Nasir, 2011; Snyder, Shah, & Ross, 2013). Furthermore, students of color overwhelmingly lack access to mathematics curriculum and pedagogy that is relevant to, and integrates, their racial, cultural, and linguistic backgrounds (Neri, Lozano, & Gomez, 2019). In these ways, mathematics classrooms are racialized spaces where “racial storylines” act as cultural artifacts that shape not only the way we collectively make sense of (and reproduce) achievement patterns, but also students’ perceptions of their ability to do mathematics (Martin, 2013; Nasir, 2011; Snyder et al., 2013). Without critical analyses of how issues of race and culture, like those described above, shape access and opportunity, colorblind interpretation of racial gaps in mathematics achievement can lead to stereotypes of Black and Latinx as non-math people. Gutierrez (2013) argues further that as our society has traditionally used mathematics achievement as a proxy for intelligence, these stereotypes of Black and Latinx as non-math people can also result in stereotypes about their levels of intelligence. Left unchallenged, these stereotypes reinforce and contribute further to the racialized experiences and organizational structures that shape access and opportunity.

In this paper, we reveal the many ways that current data inquiry practices (re)produce inequalities in education and offer a set of principles to guide our thinking toward culturally sustaining data inquiry practices. Specifically, we address how schools can: (1) draw upon asset-based frameworks to develop holistic, culturally sustaining data measures and grading practices; (2) collect, interpret, and use data to support student learning and wellbeing; (3) engage in ongoing conversations about what counts as data and how to align it to the needs and aspirations of families and the community; (4) engage in critical conversations and reflection about data that directly challenges stereotypical interpretation and centers critical examination of systemic inequities and injustices; (5) openly communicate with/provide feedback to students and families; and (6) support teachers in doing this work.

Authors

• Rebecca Colina Neri, Indiana University Bloomington

• Maritza Lozano, California State University - Fullerton