Remediating Systems, Not Students: Data-Use for Equitable Systems Change in Four District-Wide Computer Science Initiatives

• In Event: Understanding and Supporting District Systems Change Around Computer Science Education

Abstract

This study explores how district leaders use data to disrupt deficit-thinking and systemic inequities within the context of district-wide K12 computer science education (CSed) initiatives, highlighting exemplars of data-use practices, along with contextual dynamics that supported and mediated data-use practices.
As efforts to transform K12 school systems to include equitable CSed have spread in the United States, there is increasing interest in utilizing data-driven strategies such as continuous improvement (DeLyser et al, 2020). And while recent educational research reveals that districts’ data-use practices can support systems change (Coburn & Turner, 2011; Knapp, Copland, & Swinnerton, 2007; Marsh & Farrell, 2015), a subset of this research highlights how such practices are likely to reproduce inequities and reinforce deficit narratives of students, especially when assessment data gets positioned as the sole measure of students’ academic capability within the context of achievement gap discourses (Bertrand & Marsh, 2015; Diamond & Cooper, 2007; Garner, Thorne, & Horn, 2017; Lasater, Bengston, & Albiladi, 2020). This is a particularly pressing issue for computer science education reform efforts, where identity stereotypes persist about which students Computer Science is for, and which it is not (Lewis et al., 2016). In light of the negative consequences of well-intentioned data-use practices, it is important to develop guidance and exemplar cases of how districts can use data to support their systems change work in CSed while at the same time challenging deficit explanations of those they serve (Datnow & Park, 2018; Ishimaru, 2020).
This study draws on retrospective case studies of four school districts of varying size, region, and demographics. Each has been implementing CSed initiatives for at least two years, providing a robust opportunity to examine variations in data-use practices as they enacted multi-year reforms. Through interviews and district provided documentation, we collected data on how districts addressed issues of equity in terms of who, how, and what computer science was taught (Santo et al, 2019). Focusing our case narratives on instances of how district leaders used data to disrupt deficit-thinking and systemic inequities, our analysis is guided by critical and socio-cultural theories (Esmonde & Booker, 2017) which highlight the social, historical, and political dynamics at play within data-use practices.
Our findings highlight three equitable data-use practices that co-occurred in each of the cases, where districts used data to (a) make visible inequities in the implementation of district-wide CSed programs, (b) connect those inequities to issues within the instructional system (rather than framing them as reflections of students’ interest and abilities), and (c) transform instructional systems to proactively address the inequities. Additionally, each of the four cases reflects a different equity focus area in terms of problem-identification and subsequent reform - teacher capacity, and student access, participation, and experience around CS learning experiences (Warner et al., 2019).

This study provides theoretical insight for researchers interested in understanding district data- use practices that go beyond achievement-gap framings of student assessment data, and offers guidance for district leaders on how to equitably leverage data to promote systemic reform within computer science education efforts.

Authors

• David Phelps, CSforALL

• Rafi Santo, Telos Learning