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Partnership for Building Integrated Logic Models and Databases to Open Pathways to College and Careers

Sat, April 9, 12:25 to 1:55pm, Convention Center, Floor: Level One, Room 102 B

Abstract

Objectives
This paper analyzes the work of an innovative partnership among four P-20 (preschool through graduate school) alliances in California and Colorado, each creating college-bound communities to increase college-going and completion among students from diverse low-income and traditionally non-college-going families in collaboration with school, college, and community partners. The ongoing partnership is building integrated logic models and databases to strengthen research and evaluation, investment policy, and practice.

Theoretical Framework
This collaboration draws on three theories about how partnerships with families, schools, communities, and higher education can create systemic change that increases college preparation, enrollment, and completion among educationally disadvantaged communities. Bridging Multiple Worlds Theory (Cooper, 2011) traces how youth build pathways to college and careers without losing their cultural identities. Oakes’ (2003) model of Six College-Going Conditions shows how college preparation and success rest on: creating college-going school cultures; increasing academic rigor; cultivating qualified teachers; providing intensive academic and social supports; providing ways for students to develop multicultural college and career identities; and building family/neighborhood/school connections bridging to higher education. The Diverse Learning Environments model (Hurtado et al., 2012), widely used among Hispanic-Serving Institutions to foster student retention and success, maps how social-historical, policy, institutional, and community contexts define climates for campus diversity, where curricular and co-curricular learning environments jointly shape student retention and achievement that can strengthen social equity, economic, and democratic outcomes.

Methods
Three university-community regional alliances, one university system team, and one statewide alliance have collaborated towards shared goals of increasing college access and completion for low-income and underrepresented students with their campus, regional, state, and national partners. Each alliance collects academic, survey, and focus group data; imports data from districts and the National Student Clearinghouse; and generates formative and summative reports for researchers, programs, partners, and funders.

Results
Each alliance developed an integrated logic model and database consistent with its theories of change (Moran et al., 2005). The alliances shared strategies for integrated databases that unify data from individual programs to link student-level data, academic performance (e.g., passing Algebra, A-G completion), and college enrollment and allow alliances to conduct longitudinal analyses within and across programs.

Shown in Figure 1, one alliance started its integrated logic model with four programs (EAOP, MESA, GEAR UP, and Cal-SOAP) within its overarching P-20 model, focusing on advising and staff development, a shared Individualized Academic Plan (IAP), and parallel grade-level advising strategies. To avoid the common pitfall of developing logic models but not using them during implementation (Hallimah, 2011), the alliance uses, revisits and revises its logic model regularly to recheck assumptions and foster continual program improvement. This alliance collaborated with university system leaders, who developed logic models across their 14-program portfolio towards a system-wide integrated logic model.

Significance
This collaboration revealed important synergies across interdisciplinary multi-level theories of institutional, relational, and individual change towards educational equity. Improving coordination across programs and alliances is providing clearer and more unified maps for students, families, programs, and private and public partners, as well as greater impact on college preparation, enrollment, retention, and completion.

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