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Post-secondary Outcomes of Innovative High Schools: The Big Picture Longitudinal Study

by Karen D. Arnold & Georgiana Mihut - 2020

Context: Educational reform efforts have taken the form of different school models intended to reduce educational inequality. Personalized, interest-based schools and academically focused, “No Excuses” schools are two leading small-school designs with sharply contrasting approaches to innovation. Given mixed research findings about the successes and challenges of school reform models in the United States, it is imperative to understand how educational outcomes of students relate to the philosophy and distinguishing characteristics of particular school models such as these. At the same time, evaluating social mobility effects of high school education across educational reform models requires examination of common metrics such as high school graduation rate and college entrance and degree attainment.

Purpose: This study sought to establish whether and how a personalized, interest-based secondary school reform model is associated with graduates’ characteristics and post-secondary outcomes—and to place these findings in relation to student outcomes reported by a leading No Excuses school network.

Setting: Big Picture Learning is a network of innovative small schools that serves primarily low-income and minoritized students through an individualized, relational, real-world-based high school experience. The Big Picture educational model features individualized learning plans connected to extensive internships, independent learning organized around student interests, authentic assessments, and close, informal relationships between students and adults.

Research Design: The Big Picture Longitudinal Study tracked 1900 graduates from six graduating high school classes. Data sources included student and school advisor surveys, National Student Clearinghouse college enrollment data, and interviews with graduates’ former advisors. Published outcomes data for KIPP No Excuses schools provided comparative information. Analyses comprised descriptive statistics of survey data and multivariate regression analyses connecting high school exit data to college outcomes.

Findings: The Big Picture Learning model is extremely successful in meeting its stated goals of fostering positive relationships, helping students discover and pursue their interests, and promoting high school graduation and college entrance. Results for academic subject achievement and college persistence are mixed, however. Big Picture graduates have similar college matriculation rates but somewhat lower six-year graduation rates than alumni from the KIPP No Excuses school network. Alumni from both networks show high rates of college attrition.

Conclusion: When taken alone and in context of other innovative school models, the Big Picture results point to the difficulty of sustaining secondary school gains in the post-high school lives of low-income students and highlight shortcomings of traditional colleges in serving this population.

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Cite This Article as: Teachers College Record Volume 122 Number 8, 2020, p. 1-42
https://www.tcrecord.org ID Number: 23342, Date Accessed: 5/12/2021 8:32:19 PM

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About the Author
  • Karen Arnold
    Boston College
    E-mail Author
    KAREN ARNOLD, Ph.D., is Associate Professor of Higher Education at Boston College. She is the author of books and articles in the fields of college access, talent development, and longitudinal study methods. Her books include The Ecology of College Readiness and Lives of Promise: What Becomes of High School Valedictorians, both published by Jossey-Bass.
  • Georgiana Mihut
    Economic and Social Research Institute, Dublin
    E-mail Author
    GEORGIANA MIHUT is a postdoctoral research fellow at the Economic and Social Research Institute in Ireland. She recently received her Ph.D. in Higher Education from Boston College. Her work includes publications in comparative and international higher education and a dissertation investigating the impact of university prestige in three national labor markets using an experimental design.
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