Knowledge tracing is a fundamental area of educational data modeling that aims at gaining a better understanding of the learning occurring in tutoring systems. Knowledge tracing models fit various parameters on observed student performance and are evaluated through several goodness of fit metrics. Fitted parameter values are of crucial interest in…

This rejoinder keeps the original focus on statistical computing pertaining to the correlation of student achievement between mathematics and science from the Trend in Mathematics and Science Study (TIMSS). Albeit the availability of student performance data in TIMSS and the emphasis of the inter-subject connection in the Next Generation Science…

Regression, weighting and related approaches to estimating a population mean from a sample with nonrandom missing data often rely on the assumption that conditional on covariates, observed samples can be treated as random. Standard methods using this assumption generally will fail to yield consistent estimators when covariates are measured with…

A common strategy for estimating treatment effects in observational studies using individual student-level data is analysis of covariance (ANCOVA) or hierarchical variants of it, in which outcomes (often standardized test scores) are regressed on pretreatment test scores, other student characteristics, and treatment group indicators. Measurement…

Growth curve models with different types of distributions of random effects and of intraindividual measurement errors for robust analysis are compared. After demonstrating the influence of distribution specification on parameter estimation, 3 methods for diagnosing the distributions for both random effects and intraindividual measurement errors…

Recent data have suggested that despite massive outlays on educational reform Qatar consistently ranks as one of the least academically proficient countries in key areas of literacy. Of the seventy-four countries that participated in PISA 2009 Qatar ranked between sixty-seven and sixty-nine in mathematics, reading and science literacy. Although…

There is widespread interest in using various statistical inference tools as a part of the evaluations for individual teachers and schools. Evaluation systems typically involve classifying hundreds or even thousands of teachers or schools according to their estimated performance. Many current evaluations are largely based on individual estimates…

Newer statistical procedures are typically introduced to help address the limitations of those already in practice or to deal with emerging research needs. Quantile regression (QR) is introduced in this paper as a relatively new methodology, which is intended to overcome some of the limitations of least squares mean regression (LMR). QR is more…

Because random assignment is not possible in observational studies, estimates of treatment effects might be biased due to selection on observable and unobservable variables. To strengthen causal inference in longitudinal observational studies of multiple treatments, we present 4 latent growth models for propensity score matched groups, and…

This paper investigates how the precision and stability of a teacher's value-added estimate relates to the characteristics of the teacher's students. Using a large administrative data set and a variety of teacher value-added estimators, it finds that the stability over time of teacher value-added estimates can depend on the previous achievement…

This report examines the differences in impact estimates and standard errors that arise when these are derived using state achievement tests only (as pre-tests and post-tests), study-administered tests only, or some combination of state- and study-administered tests. State tests may yield different evaluation results relative to a test that is…

In organizational studies involving multiple levels, the association between a covariate and an outcome often differs at different levels of aggregation, giving rise to widespread interest in "contextual effects models." Such models partition the regression into within- and between-cluster components. The conventional approach uses each…

This report summarizes research findings and implementation practices for teacher and principal value-added models (VAMs), as a first step in the Team Pennsylvania Foundation's (Team PA) pilot project to inform the development of a full, statewide model evaluation system. We have selected 21 studies that represent key issues and findings in the…

In this report, the authors describe the value-added models used as part of teacher evaluation systems in the District of Columbia Public Schools (DCPS) and in eligible DC charter schools participating in Race to the Top. They estimated (1) teacher effectiveness in DCPS and eligible DC charter schools during the 2011-2012 school year; and (2)…

Past estimates of the effect of family income on child development have often been plagued by endogeneity and measurement error. In this paper, we use two simulated instrumental variables strategies to estimate the causal effect of income on children's math and reading achievement. Our identification derives from the large, non-linear changes…