The main purpose of this study is to improve estimation efficiency in obtaining maximum marginal likelihood estimates of contextual effects in the framework of nonlinear multilevel latent variable model by adopting the Metropolis-Hastings Robbins-Monro algorithm (MH-RM). Results indicate that the MH-RM algorithm can produce estimates and standard…

The main purpose of this study is to improve estimation efficiency in obtaining maximum marginal likelihood estimates of contextual effects in the framework of nonlinear multilevel latent variable model by adopting the Metropolis-Hastings Robbins-Monro algorithm (MH-RM; Cai, 2008, 2010a, 2010b). Results indicate that the MH-RM algorithm can…

The main purpose of this study is to improve estimation efficiency in obtaining full-information maximum likelihood (FIML) estimates of contextual effects in the framework of a nonlinear multilevel latent variable model by adopting the Metropolis-Hastings Robbins-Monro algorithm (MH-RM; Cai, 2008, 2010a, 2010b). Results indicate that the MH-RM…

In this article, the change in examinee effort during an assessment, which we will refer to as persistence, is modeled as an effect of item position. A multilevel extension is proposed to analyze hierarchically structured data and decompose the individual differences in persistence. Data from the 2009 Program of International Student Achievement…

Are U.S. and, in particular, Hoosier students competitive and ready to succeed in an ever-changing and increasingly global economic landscape? This question is frequently considered by K-12 education stakeholders at all levels, including national, state, and local officials. One of the central ways in which education systems can compare themselves…

This report reviews the major international and regional large-scale educational assessments, including international surveys, school-based surveys and household-based surveys. The report compares and contrasts the cognitive and contextual data collection instruments and implementation methods used by the different assessments in order to identify…

Standards-based science education, with its emphasis on monitoring and accountability, is rapidly becoming a key part of the globalization of science education. Standards-based testing within countries is increasingly being used to determine the effectiveness of a country's educational system, and international testing programs such as Programme…

Monitoring Trends in Educational Growth (MTEG) offers a flexible, collaborative approach to developing and implementing an assessment of learning outcomes that yields high-quality, nationally relevant data. MTEG is a service that involves ACER staff working closely with each country to develop an assessment program that meets the country's…

While much of the work in language testing is concerned with constructing quality tests in order to measure language knowledge in reliable and valid ways, there has been a significant movement in language testing research that examines tests in the context of their use in education and society. This line of research exits from the notion that…

Differential item functioning (DIF) analysis is a statistical technique used for ensuring the equity and fairness of educational assessments. This study formulates a new DIF analysis method using the information similarity index (ISI). ISI compares item information functions when data fits the Rasch model. Through simulations and an international…

Many articles and reports have reviewed, researched, and commented on international assessments from the perspective of exploring what is relevant for the United States' education systems. Researchers make claims about whether the top-performing systems have transferable practices or policies that could be applied to the United States. However,…