Exploring Student-Teacher Interactions in Longitudinal Achievement Data

2009 ◽  
Vol 4 (4) ◽  
pp. 439-467 ◽  
Author(s):  
J. R. Lockwood ◽  
Daniel F. McCaffrey
Keyword(s):  
Total Variation ◽  
Value Added ◽  
Middle School Mathematics ◽  
Data Sources ◽  
Teacher Effects ◽  
Policy Makers ◽  
Teacher Effect ◽  
Achievement Data ◽  
Empirical Estimates ◽  
Interaction Terms

This article develops a model for longitudinal student achievement data designed to estimate heterogeneity in teacher effects across students of different achievement levels. The model specifies interactions between teacher effects and students' predicted scores on a test, estimating both average effects of individual teachers and interaction terms indicating whether individual teachers are differentially effective with students of different predicted scores. Using various longitudinal data sources, we find evidence of these interactions that is of relatively consistent but modest magnitude across different contexts, accounting for about 10 percent of the total variation in teacher effects across all students. However, the amount that the interactions matter in practice depends on the heterogeneity of the groups of students taught by different teachers. Using empirical estimates of the heterogeneity of students across teachers, we find that the interactions account for about 3–4 percent of total variation in teacher effects on different classes, with somewhat larger values in middle school mathematics. Our findings suggest that ignoring these interactions is not likely to introduce appreciable bias in estimated teacher effects for most teachers in most settings. The results of this study should be of interest to policy makers concerned about the validity of value-added teacher effect estimates.

scholarly journals Models for Value-Added Modeling of Teacher Effects

2004 ◽  
Vol 29 (1) ◽  
pp. 67-101 ◽  
Author(s):  
Daniel F. McCaffrey ◽  
J. R. Lockwood ◽  
Daniel Koretz ◽  
Thomas A. Louis ◽  
Laura Hamilton
Keyword(s):  
Student Development ◽  
Mixed Model ◽  
Value Added ◽  
Research Literature ◽  
Complex Data ◽  
Teacher Effects ◽  
Policy Makers ◽  
Special Cases ◽  
Different Populations ◽  
Over Time

The use of complex value-added models that attempt to isolate the contributions of teachers or schools to student development is increasing. Several variations on these models are being applied in the research literature, and policy makers have expressed interest in using these models for evaluating teachers and schools. In this article, we present a general multivariate, longitudinal mixed-model that incorporates the complex grouping structures inherent to longitudinal student data linked to teachers. We summarize the principal existing modeling approaches, show how these approaches are special cases of the proposed model, and discuss possible extensions to model more complex data structures. We present simulation and analytical results that clarify the interplay between estimated teacher effects and repeated outcomes on students over time. We also explore the potential impact of model misspecifications, including missing student covariates and assumptions about the accumulation of teacher effects over time, on key inferences made from the models. We conclude that mixed models that account for student correlation over time are reasonably robust to such misspecifications when all the schools in the sample serve similar student populations. However, student characteristics are likely to confound estimated teacher effects when schools serve distinctly different populations.

scholarly journals Can Value-Added Measures of Teacher Performance Be Trusted?

2015 ◽  
Vol 10 (1) ◽  
pp. 117-156 ◽  
Author(s):  
Cassandra M. Guarino ◽  
Mark D. Reckase ◽  
Jeffrey M. Wooldridge
Keyword(s):  
Value Added ◽  
Ordinary Least Squares ◽  
Data Sets ◽  
Teacher Effects ◽  
Achievement Data ◽  
Student Grouping ◽  
Teacher Assignment ◽  
Estimation Problems ◽  
Dynamic Relationships ◽  
Value Added Measures

We investigate whether commonly used value-added estimation strategies produce accurate estimates of teacher effects under a variety of scenarios. We estimate teacher effects in simulated student achievement data sets that mimic plausible types of student grouping and teacher assignment scenarios. We find that no one method accurately captures true teacher effects in all scenarios, and the potential for misclassifying teachers as high- or low-performing can be substantial. A dynamic ordinary least squares estimator is more robust across scenarios than other estimators. Misspecifying dynamic relationships can exacerbate estimation problems.

Validating Teacher Effects on Students’ Attitudes and Behaviors: Evidence from Random Assignment of Teachers to Students

2018 ◽  
Vol 13 (3) ◽  
pp. 281-309 ◽  
Author(s):  
David Blazar
Keyword(s):  
Test Scores ◽  
Student Outcomes ◽  
Classroom Teacher ◽  
Random Assignment ◽  
Teacher Effects ◽  
High Stakes ◽  
Policy Makers ◽  
Teacher Effect ◽  
Personnel Decisions ◽  
Students Attitudes

There is growing interest among researchers, policy makers, and practitioners in identifying teachers who are skilled at improving student outcomes beyond test scores. However, questions remain about the validity of these teacher effect estimates. Leveraging the random assignment of teachers to classes, I find that teachers have causal effects on their students’ self-reported behavior in class, self-efficacy in math, and happiness in class that are similar in magnitude to effects on math test scores. Weak correlations between teacher effects on different student outcomes indicate that these measures capture unique skills that teachers bring to the classroom. Teacher effects calculated in nonexperimental data are related to these same outcomes following random assignment, revealing that they contain important information content on teachers. However, for some nonexperimental teacher effect estimates, large and potentially important degrees of bias remain. These results suggest that researchers and policy makers should proceed with caution when using these measures. They likely are more appropriate for low-stakes decisions—such as matching teachers to professional development—than for high-stakes personnel decisions and accountability.

How Large Are Teacher Effects?

2004 ◽  
Vol 26 (3) ◽  
pp. 237-257 ◽  
Author(s):  
Barbara Nye ◽  
Spyros Konstantopoulos ◽  
Larry V. Hedges
Keyword(s):  
Student Achievement ◽  
Mathematics Achievement ◽  
Low Socioeconomic Status ◽  
Variance Components ◽  
Selection Effects ◽  
Teacher Effects ◽  
Low Socioeconomic ◽  
Achievement Gains ◽  
Teacher Effect ◽  
Teachers And Students

It is widely accepted that teachers differ in their effectiveness, yet the empirical evidence regarding teacher effectiveness is weak. The existing evidence is mainly drawn from econometric studies that use covariates to attempt to control for selection effects that might bias results. We use data from a four-year experiment in which teachers and students were randomly assigned to classes to estimate teacher effects on student achievement. Teacher effects are estimated as between-teacher (but within-school) variance components of achievement status and residualized achievement gains. Our estimates of teacher effects on achievement gains are similar in magnitude to those of previous econometric studies, but we find larger effects on mathematics achievement than on reading achievement. The estimated relation of teacher experience with student achievement gains is substantial, but is statistically significant only for 2nd-grade reading and 3rd-grade mathematics achievement. We also find much larger teacher effect variance in low socioeconomic status (SES) schools than in high SES schools.

scholarly journals Long-term Development of National Human Capital. Evidence from China and Poland

2020 ◽  
Vol 12 (3) ◽  
pp. 30-66
Author(s):  
Łukasz Bryl
Keyword(s):  
Human Capital ◽  
Research Collaboration ◽  
Tertiary Education ◽  
Value Added ◽  
Human Capital Development ◽  
Policy Makers ◽  
Industry Research ◽  
National Human ◽  
Capital Development

AbstractObjective: The aim of this paper is to present the long-term development of the chosen human capital indices that uncovers and compares the outcome of the national efforts performed by the two culturally distant countries (China and Poland) over the decade. Additionally, paper indicates the areas of further HC progress in both nations.Methodology: The study was based on measuring human capital with the help of deliberately chosen set of macroeconomic indices (28 items) referring to the nations’ capability to create innovations. Analysis was performed for the 2007–2017 years.Findings: Positive phenomena in the case of human capital development outperform the negative ones in both countries, however, the extent is more remarkable in the case of China. China managed to: improve greatly the pupil-teacher ratio (both in primary and secondary schools), increase secondary and tertiary education enrolment rate along with the rise of the no. of students from abroad. In Poland, the greatest increase was observed in the case of the number of researchers what consequently contributed to the improvement of number of scientific and technical articles and citable documents (h-index).Value Added: To the best Author’s knowledge this is the first paper that compares national human capital development in Poland and China with a set of indices focused on capability to create innovations and adopts longitudinal approach.Recommendations: Policy-makers in the case of Poland should concentrate on: fostering university/industry research collaboration, improving rank in worldwide QS classification and performing more efforts to attract and retain talents. Moreover, the negative trends should be reversed with regard to: PISA scores and general quality of education system. In turn, Chinese authorities should facilitate better PISA scores and increase the presence of scientific and technical articles.

On the Importance of the Tax System in Marginal Cost of Funds Calculations

2011 ◽  
Vol 11 (1) ◽  
Author(s):  
Mickael Beaud
Keyword(s):  
General Equilibrium ◽  
Marginal Cost ◽  
Analytical Formula ◽  
Value Added ◽  
Tax Revenue ◽  
Empirical Estimates ◽  
Analytical Formulas ◽  
The Impact ◽  
Labor Income Taxation ◽  
Marginal Cost Of Funds

Abstract Several papers have attempted to derive computable analytical formulas for the Marginal Cost of Funds (MCF). However, this literature is often cast in the pure labor supply general equilibrium model, which is not completely consistent with real tax systems where Labor Income Taxation (LIT) is not the only instrument used by governments. Hence, we explicitly introduce Value-Added Taxation (VAT) on consumption goods in the conventional model, and we derive an analytical formula for the MCF which does incorporate general equilibrium interactions between the different tax bases. Then, we illustrate how much this matter for empirical estimates of MCF using French data. Our numerical example suggests that, when computing MCF for a LIT reform, taking account of the impact of LIT reform on tax revenue from VAT can make a great deal of difference, typically increasing MCF and accounting for around 0.2 to 0.8 of estimates. In addition, MCF is then really less likely to be less than one than in the conventional framework.

Gender Differences in Reading, Writing and Language Development

2020 ◽  
Author(s):  
David Reilly
Keyword(s):  
Gender Differences ◽  
Language Development ◽  
Educational Achievement ◽  
Age Groups ◽  
Careful Evaluation ◽  
Language Abilities ◽  
Policy Makers ◽  
Achievement Data ◽  
Nationally Representative ◽  
Representative Samples

The topic of gender differences in reading, writing, and language development has long been of interest to parents, educators, and public-policy makers. While some researchers have claimed that gender differences in verbal and language abilities are disappearing, careful evaluation of the scientific research shows otherwise. Examination of nationally representative samples of educational achievement data show that there are moderately sized gender differences in reading achievement favoring girls and women (d = −0.19 to −0.44 across age groups), and substantially larger gender differences in writing (d = −0.42 to −0.62), spelling (d = −0.39 to −0.50), and grammar (d = −0.39 to −0.42). Explanations for observed gender differences in verbal and language abilities suggest a complex network of biological, social, and cultural forces rather than any single factor.

scholarly journals Estimating drowning mortality in Tanzania: a systematic review and meta-analysis of existing data sources

2018 ◽  
Vol 25 (5) ◽  
pp. 459-471 ◽  
Author(s):  
Sophie Sarrassat ◽  
Sigilbert Mrema ◽  
Kassimu Tani ◽  
Thomas Mecrow ◽  
Dan Ryan ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Complete Information ◽  
Population Based ◽  
Data Sources ◽  
Prevention Strategies ◽  
Policy Makers ◽  
Drowning Prevention ◽  
Study Sites ◽  
Global Datasets ◽  
Existing Data

BackgroundThe WHO advocates a 7-step process to enable countries to develop and implement drowning prevention strategies. We sought to assess, using existing data sources, the drowning situation in Tanzania as a first step in this process.MethodsWe searched for data on causes of death in Tanzania by reviewing existing literature and global datasets and by in-country networking. Authors and institutions were then contacted to request aggregate data on drowning mortality. Site-specific drowning estimates were combined using a random effects meta-analytic approach. We also tested for evidence of variations in drowning estimates by sex and by age group.ResultsWe acquired partial or complete information on drowning deaths for 13 data sources. We found strong evidence for substantial variations between study sites (p<0.001). Combining population-based data, we estimated an average of 5.1 drowning deaths per 100 000 persons per year (95% CI 3.8 to 6.3). The proportions of deaths due to drowning were 0.72% (95% CI 0.55 to 0.88) and 0.94% (95% CI 0.09 to 1.78) combining population-based data and hospital-based data, respectively. Males were at greater risk than females, while both under-five children and adults aged 45 years or more were at greater risk than those aged 5–44 years.ConclusionOur estimates of drowning burden are broadly in line with the 2016 Global Burden of Disease and the 2015 WHO Global Health Estimates. While this exercise was useful in raising the burden of drowning in Tanzania with policy makers, planning drowning prevention strategies in this country will require a better understanding of which subpopulations are at high risk.

Sign in / Sign up

Export Citation Format

Share Document