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Consequences of Misassignment to Treatment: Examining Targeted Policy Interventions in Education
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Consequences of Misassignment to Treatment: Examining Targeted Policy Interventions in Education. |
| 개인저자 | Kennedy, Alec I. |
| 단체저자명 | University of Washington. Public Policy and Governance. |
| 발행사항 | [S.l.]: University of Washington., 2019. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
| 형태사항 | 136 p. |
| 기본자료 저록 | Dissertations Abstracts International 81-05A. Dissertation Abstract International |
| ISBN | 9781088327067 |
| 학위논문주기 | Thesis (Ph.D.)--University of Washington, 2019. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 81-05, Section: A.
Advisor: Long, Mark C. |
| 이용제한사항 | This item must not be sold to any third party vendors.This item must not be added to any third party search indexes. |
| 요약 | In education, students are often assigned to specialized programs or receive targeted interventions based on some standards and requirements. The criteria used to select the students for such targeted policies must weigh the trade-off between serving too many students and not serving enough. Under such selection criteria, I identify students who are selected into a treatment category that does not maximize their benefits as consequences of misassignment to treatment. As targeted policy interventions are aimed at providing supports for students with specific needs, it is important that we establish a firm understanding and provide guidance on how selection criteria should be designed and used to assure that all students are appropriately served. This dissertation explores several aspects of such selection criteria through the examination of three policies in education that seek to select students (or school districts) for targeted interventions and supports. The exploration provides learning and recommendations on how federal, state, and local governments can leverage data and analysis to limit the consequences of misassignment to treatment.The first chapter of this dissertation introduces a framework to facilitate in the understanding of the consequences to misassignment to treatment. The framework establishes a way of understanding how selection criteria for targeted policy interventions can fail and lead to losses of benefits for both targeted and non-targeted groups.The second chapter, Are We Correctly Measuring the Disproportionality of Minority Students in Special Education?, asks whether the current methods for measuring disproportionality in special education are accurately identifying school districts in need of a change of referral practices. Currently, the U.S. Department of Education's Office of Civil Rights (OCR) monitors whether school districts disproportionately refer minority students into special education services in an effort to prevent overreferral. However, these monitoring methods do not account for student-level factors (notably, socioeconomic status) which have been theorized to be positively associated with the presence of a learning disability. If minority students are more likely to experience low socioeconomic status than their White peers, then there may be good reason for minority students to be overrepresented in special education (i.e., the current measures of disproportionality could be susceptible to bias). In this chapter, I introduce an alternative measure for tracking disproportionality that removes this threat of bias. I then compare the performance of this alternative measure of disproportionality with the one currently in use and find that the currently used measure tends to overstate disproportionality. This finding suggests that current measures used by states to monitor disproportionality may incorrectly label some school districts as having an overrepresentation problem when, in fact, they do not.The third chapter, Successfully Transitioning English Language Learners into the Mainstream Classroom, investigates whether the state-established thresholds on language assessments used to determine whether English language learners (ELLs) are ready to transition from specialized services into the mainstream classroom are set in a way that maximizes the estimated benefits for ELLs in all instructional contexts. In this chapter, I find that the cutscores used to determine eligibility for ELL program exit in one state are generally set to promote the successful transition of ELLs into the mainstream classroom. However, I find that the cutscores do not work for all. Specifically, I find that Spanish-speaking students exiting bilingual programs struggle to succeed in English subjects after exiting ELL services. This finding suggests that the current thresholds are not working for all and should be modified in some way. This modification could involve the inclusion of teacher input into transitioning decisions or the close monitoring of recently exited ELL students in order to provide appropriate supports when needed.The fourth chapter, Making the Cut: An Optimization Approach for Setting Cutpoints in Targeted Policy Interventions in Education, provides an introduction to an optimization approach that can be used in Early Warning Indicators (EWI) or Early Warning Systems (EWS) to set optimal cutpoints on key leading indicators to determine eligibility for targeted supports. I apply the approach to two district examples of EWI/EWS to identify cutpoints that minimize misclassification rates. In the first example, I identify optimal cutpoints on kindergarten and first grade assessments to identify students who show evidence of having dyslexia and are in need of early literacy interventions. In the next example, I use the approach to produce thresholds that can be used to identify students at risk of becoming chronically absent in order to provide them with additional resources and support during the school year to help them overcome barriers to attendance. The approaches introduced and used in this chapter can offer guidance to districts or states seeking to establish EWI/EWS to identify students in need of targeted interventions or supports.The final chapter concludes this dissertation by presenting learning from each of the chapters on how selection criteria in targeted policy interventions can be better designed to limit consequences of misassignment to treatment. |
| 일반주제명 | Education policy. Public policy. Second language learning. English as a second language--ESL. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
