Providing Services without the Data: Constraints and Possibilities for CBOs Working in Urban Schools

Background and Purpose:

Non-profit community-based organizations (CBOs) increasingly take on important governance and service-provision functions within urban public education systems in the United States, utilizing data to support their efforts. However, since such organizations exist outside the public sector, they face barriers to obtaining the necessary data to carry out their work. In 2023, I partnered with Chicago Public Schools to investigate the data needs and practices of non-profit organizations that represent some of the school district’s closest community partners. This study aims to better understand how these organizations view data in the context of their broader work and what challenges they face in accessing useful data. The study aims to inform empathy-driven design in support of public education data-sharing initiatives geared toward non-profit community organizations.

Methods:

The data collected for this study come from a set of in-depth, semi-structured interviews with the leaders of 15 CBOs that take a variety of approaches to engage with education issues in Chicago. This study takes a grounded theory approach to understand how each organization’s approach to resolving education and community problems relates to their data needs. Potential CBOs were identified for the study based on their participation in state education initiatives and district community engagement activities. Ultimately, I selected a mix of CBOs that represented key geographic areas of the city and different geographic scales of operation. The interviews were transcribed verbatim and coded using NVivo software. The coding process followed a grounded theory approach, which involved three rounds of coding to identify key themes in the data, classify them based on their relationship to important phenomena, and then group them based on their relationships.

Findings:

The analysis reveals four distinct types of CBOs based on the way they frame education problems and go about resolving them. I call the four types: Local Policy Advocates, Community Conveners, Service Providers, and Community Organizers to capture their dominant approaches. I find that data needs and access vary based on CBO characteristics. In addition, I find that certain common data policies and practices implicitly support individual-level interventions over family and community-level interventions, hindering the ability of certain organizations to administer and advocate for resources.

Conclusion and Implications:

This work has important implications for how CPS and other local education authorities can better support organizations that provide critical services to marginalized students and their families. I show that a better understanding of CBOs' distinct approaches to supporting public education can explain key data needs and support an empathy-driven approach to designing data-sharing tools and processes. Specific possibilities for how school districts can better support CBOs through education data sharing include:

1. Increasing transparency around subgroups to enable CBOs to facilitate more nuanced policy advocacy.
2. Incorporating data on education inputs to enable CBOs to more strategically design programming.
3. Providing student-level data when appropriate would enable CBOs to more efficiently direct services to students and families in need.
4. Facilitating data access would allow CBOs to demonstrate the impact of their programs and ensure continued funding.