The Networks for Social Impact
in Education Series
The reports in this series include:
- Report 1: Networks that create a social impact
- Report 2: Equity and empowerment in education networks
- Report 3: Effective data practices support learning and systems alignment
- Report 4: Navigating network change (expected June 2021)
- Appendix: The networks that participated in this research
This research was supported by a grant from the Army Research Office (W911NF-16-1-0464) and the School of Communication, Northwestern University.
Achieving social impact is rare and time-consuming. This research investigates whether network activity resulted in improved 4th-grade reading, 8th-grade reading, and high school graduation at the district level or across the set of districts the network serves. Out of the 26 networks in this study, we found conclusive evidence of social impact attributable to eight networks’ activities. All the networks that achieved social impact were at least three years old, consistent with previous research that suggests system-level change requires a minimum of three to five years.
Stronger adherence to initial collective impact tenets does not result in a more significant social impact, as measured in this research. Only one of the eight networks with evidence of social impact (i.e., 4th-grade reading, 8th-grade reading, high school graduation above expected values) adhered to the collective impact model. Instead, networks adopted different models, including community-based schools, community empowerment models, Campaign for Grade-Level Reading programs, and My Brother’s Keeper initiatives. In short, our research suggests that there is more than one way to achieve social impact when measured as improved student achievement.
NNSI investigated the network designs associated with district-level student achievement. We found that there were two designs, almost equally likely to result in social impact.
● Four of the successful networks combined learning and systems-alignment logics of change to make a social impact. Learning-based mechanisms focus on improving the quality of services that organizations already offer. In systems alignment, diverse network members coordinate their joint services to explore service gaps. These networks use robust data models to identify both gaps in services and improve existing programs’ quality.
● In communities above the national poverty line, networks using distributed governance models and a project model of change significantly improved students’ outcomes in their community. Network members share power and responsibility in distributed governance. A project logic of change creates social impact by delivering new programs from the network’s joint activity. Three of the successful networks in our research used this model.
Community involvement is essential for empowerment but rarely embraced. One network approach to address inequity is involvement practices. Involvement practices include network methods to engage and connect with the communities they serve. The two networks with the most impactful involvement practices embed community members in the decision-making process. Community members have leadership and governance roles in the network and can influence network priorities and outcomes directly. However, most networks sought community feedback and limited their involvement to working groups or action teams.
Networks rarely use systems-change approaches that challenge power structures. A network that has adopted a systems-change approach identifies systems or structural barriers as the root problem for the issues they aim to better, then actively seeks to deconstruct and rebuild systems in more equitable ways. Networks embracing systems change do not ignore systems-caused inequity or rely on market solutions to address inequity. They conduct an in-depth analysis of root causes and are proactive in reorganizing power structures. In contrast, most networks in our study focused their efforts on providing better programs and services and using these programs to address opportunity gaps.
Networks used varied approaches to evidence, but the most successful networks using learning and system-alignment theories of change used data effectively to make decisions. Using data to improve learning in networks and promote system alignment is one path to successful social impact. We make suggestions for networks both collecting and reporting data. If organizational partners commit to using the same metrics and tools, data collection is indeed a worthwhile investment. Standardizing metrics and measures, especially at the outset of a partnership, allows for aligned conversations on network processes and outcomes. Successful networks do not avoid the difficult conversations that data may uproot. Instead, they anticipate and address conflicts that may arise within the data collection or reporting process. Finally, successful networks disaggregate data to pinpoint specific improvement areas and utilize data in refining their decision-making.
Katherine R. Cooper
University of Connecticut
University of Kentucky
Jack L. Harris
SUNY at New Paltz
Northwestern University Undergraduate Research Assistants
High School Intern