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The purpose of this paper is to present results from two school improvement efforts to personalize learning for students and their families, particularly related to college readiness; to discuss methodological challenges in implementation research, particularly in measuring fidelity of implementation in school improvement efforts; and to share a new approach called Adaptive Implementation (AI). Across two development grants in the course of six years from the Investing in Innovation (i3) fund, we developed a school-wide program through building partnerships, using student data, and personalizing instruction for students. A major challenge was measuring fidelity of implementation for a developing school improvement model. Rather, AI utilizes a continuous improvement cycle that captures and learns from adaptations in implementation.
Ryoko Yamaguchi, Plus Alpha Research & Consulting, LLC
Laureen G. Avery, University of California - Los Angeles
Jason A. Cervone, University of California - Los Angeles
Lisa D. Dimartino
Adam Hall, University of North Carolina - Greensboro