The Random Assignment of Students Into Elementary Classrooms

Paufler, Noelle A.; Amrein‐Beardsley, Audrey

doi:10.3102/0002831213508299

Cited by 46 publications

(19 citation statements)

References 36 publications

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“…A recent study by Paufler and Amrein-Beardsley (2014) provides insight into what those student assignment mechanisms might be. The authors surveyed over 300 elementary school principals in Arizona, 98% of whom reported using student and teacher information during the placement process in an effort to match learning and teaching styles, personalities, and special needs with the objective of maximizing student outcomes.…”

Section: Implications To Practices For Reducing Summer Biasesmentioning

confidence: 99%

The effect of summer on value-added assessments of teacher and school performance

Palardy

Peng

2015

EPAA

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This study examines the effects of including the summer period on value-added assessments (VAA) of teacher and school performance at the early grades. The results indicate that 40-62% of the variance in VAA estimates originates from the summer period, depending on the outcome (i.e., reading or math achievement gains). Furthermore, when summer is omitted from the VAA model, 51-61% of the teachers and 58-61% of the schools change performance quintiles, with many changing 2-3 quintiles. Extensive statistical controls for student background and classroom and school context reduce the summer effect, but 36-47% of the teachers and 42-49% of the schools are still in different quintiles. Furthermore, besides misclassifying teachers and schools, the results show that including summer tends to bias VAA estimates against schools with concentrated poverty. The results suggest that removing summer effects from VAA estimates will likely require biannual achievement assessments (i.e., fall and spring). Keywords: accountability; school effectiveness; teacher evaluation; high stakes testing. Los efectos de la inclusión del verano en las evaluaciones de valor añadido de docentes y escuelas. Education Policy Analysis Archives Vol. 23 No. 922 Resumen: Este estudio analiza los efectos de incluir el período de verano en las evaluaciones de valor añadido (EVA) de docentes y de rendimiento escolar en los primeros grados. Los resultados indican que el 40-62% de la varianza en las estimaciones de EVA se originan en el período de verano, dependiendo del resultado (es decir, ganancias de logros en lectura o en matemáticas). Por otra parte, cuando el verano se omite del modelo EVA, desde 51-61% de los profesores y de 58-61% de las escuelas cambian sus quintiles de desempeño, y muchas cambian 2-3 quintiles. Controles estadísticos extensivos de las características de los estudiantes y de contexto escolar reducen el efecto de verano, pero 36-47% de los profesores y de 42-49% de las escuelas están todavía en diferentes quintiles. Estos resultados sugieren que la eliminación de los efectos de verano, de las estimaciones EVA probablemente requerirá evaluaciones de rendimiento bianuales (es decir, de otoño y primavera). Por otra parte, además de clasificar erróneamente a docentes y las escuelas, los resultados muestran que la inclusión de verano tiende a sesgar las estimaciones EVA en contra de las escuelas con mayores concentraciones de estudiantes en situación de pobreza. Palabras clave: rendición de cuentas; eficacia de la escuela; evaluación docente; exámenes de consecuencias severas. Os efeitos da inclusão de verão nas avaliações de valor agregado de professores e escolas.Resumo: O presente estudo analisa os efeitos de incluir o período de Verão nas avaliações de valor agregado (AVA) de professores e desempenho escolar nas séries iniciais. Os resultados indicam que 40-62% da variação nas estimativas de AVA se originam no período de verão, dependendo do resultado (ou seja, os ganhos de desempenho em leitura ou matemática). Além disso...

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Section: Implications To Practices For Reducing Summer Biasesmentioning

confidence: 99%

The effect of summer on value-added assessments of teacher and school performance

Palardy

Peng

2015

EPAA

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“…The placement of students into teachers’ classrooms occurs more or less at random, so really any effects that might be observed among teachers might be reasonably attributed to students’ teachers provided advanced statistical tools and techniques are used. The assignment of students to classrooms (and teachers to classrooms, as well as students and teachers to schools) is much farther from random than is often assumed, and this biases VAM estimates and weakens arguments that teachers, not students, were responsible for the effects observed (see, for example, Bausell, 2013; Braun, 2005; Paufler & Amrein-Beardsley, 2014; Rothstein, 2009, 2010, 2014).…”

Section: Resultsmentioning

confidence: 99%

Value-Added Models for Teacher Evaluation and Accountability: Commonsense Assumptions

Amrein‐Beardsley

Holloway

2017

Educational Policy

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Despite the concerns regarding value-added models (VAMs), advocates hold strong to VAMs’ theoretical strengths and potentials, while adopting a set of agreed-upon albeit “heroic” set of assumptions, without research in support. These assumptions transcend promotional, policy, media, and research-based pieces, but they have never been made explicit as analyzed as a set or whole. The purpose of this study was to make unambiguous the assumptions that have been made within the VAM narrative that have often been accepted without challenge, and situate these assumptions within the research. Sources for analyses included 470 pieces, published within traditional and nontraditional outlets, from which we derived 27 prevailing assumptions.

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“…This is appropriate for some universities and some selective primary and secondary schools (e.g., if using ACT scores both for admissions and as a covariate in the model). It is also applicable for teacher evaluation within schools where students may be streamed into a class based on previous performance (Paufler & Amrein-Beardsley, 2014). This is important because sometimes these methods are used to estimate teacher effectiveness (Amrein-Beardsley, 2014).…”

Section: Simulation Methodsmentioning

confidence: 99%

Allocation to groups: Examples of Lord's paradox

Wright

2019

Brit J of Edu Psychol

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Background. Educational and developmental psychologists often examine how groups change over time. Two analytic procedures-ANCOVA and the gain score model-each seem well suited for the simplest situation, with just two groups and two time points. They can produce different results, what is known as Lord's paradox. Aims. Several factors should influence a researcher's analytic choice. This includes whether the score from the initial time influences how people are assigned to groups. Examples are shown which will help to explain this to researchers and students, and are of educational relevance. It is shown that a common method used to measure school effectiveness is biased against schools that serve students from groups that are historically poor performing. Methods & Results. The examples come from sports and measuring educational effectiveness (e.g., for teachers or schools). A simulation study shows that if the covariate influences group allocation, the ANCOVA is preferred, but otherwise the gain score model may be appropriate. Regression towards the mean is used to account for these findings. Conclusions. Analysts should consider the relationship between the covariate and group allocation when deciding upon their analytic method. Because the influence of the covariate on group allocation may be complex, the appropriate method may be complex. Because the influence of the covariate on group allocation may be unknown, the choice of method may require several assumptions.

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The Random Assignment of Students Into Elementary Classrooms

Cited by 46 publications

References 36 publications

The effect of summer on value-added assessments of teacher and school performance

The effect of summer on value-added assessments of teacher and school performance

Value-Added Models for Teacher Evaluation and Accountability: Commonsense Assumptions

Allocation to groups: Examples of Lord's paradox

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