Affiliation:
1. New York University
2. Oregon State University
3. University of Illinois at Urbana-Champaign
Abstract
Effectively educating the large English learner population requires policymakers to ensure developmentally appropriate settings and services throughout the time students are learning English, as well as during their transition to fluent English proficient status—a process termed reclassification. Using longitudinal student-level data from two U.S. states ( N = 107,549), the authors implemented recent advances in multi-site regression discontinuity designs to assess the effects of reclassification policies across districts. They found that reclassification decisions are heavily influenced by state criteria; however, there is considerable variability across districts in the extent of state-level influence. The authors also found robust evidence of between-district heterogeneity in the effects of reclassification on subsequent achievement and graduation. They discuss the implications of these findings for reclassification policies and future research on the topic. Looking toward the next century of education research, the authors discuss ways that multi-site regression discontinuity designs can be combined with qualitative research to enable policymakers and practitioners to better understand variation in effects of policies across contexts as well as the mechanisms underlying those effects.
Publisher
American Educational Research Association (AERA)
Cited by
34 articles.
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