The Afterschool Alliance, in partnership with MetLife Foundation, is proud to present the final issue brief in their latest series of four issue briefs examining critical issues facing middle school youth and the vital role afterschool programs play in addressing these issues. This brief explores afterschool and data utilization to improve…

As educators are increasingly called on to use data to inform improvement initiatives (and are being held accountable for doing so), there is a corresponding need for program leaders to monitor progress. Program monitoring--the systematic and continual observation and recording of key program aspects--can provide leaders with realistic assessments…

Listening closely to what students say about their school experiences can be beneficial to educators for understanding and addressing school-related topics and problems and rethinking policies and practices. The purpose of this toolkit is to provide educators with a purposeful and systematic way to elicit and listen to student voice to inform…

This article describes an exciting exploration-based activity in which students develop an alternative definition of factor that can help them solve problems like the one presented above. Students work in groups to collect data, analyze the data to make conjectures, and then spend a significant amount of time debating and justifying their…

Statistics and probability have become an integral part of mathematics education. Therefore it is important to understand whether curricular materials adequately represent statistical ideas. The "Guidelines for Assessment and Instruction in Statistics Education" (GAISE) report (Franklin, Kader, Mewborn, Moreno, Peck, Perry, & Scheaffer, 2007),…

Estimating the effect of campus math tutoring support, this study demonstrates the use of propensity score weighted and matched-data analysis and examines the correspondence with results from parametric regression analysis.

Building on the work of Bollen (2007) and Bollen & Bauldry (2011), Bainter and Bollen (this issue) clarifies several points of confusion in the literature regarding causal indicator models. This author would certainly agree that the effect indicator (reflective) measurement model is inappropriate for some indicators (such as the social…

In a modern society, the schools have become very important entities because they form a social institution, which interests many people and involves the role of various interest groups and stakeholders in the society. The community where a school resides and the parents of children of those who go to that school will be proud if their school if…

The aprioristic (classical, naïve and symmetric) and frequentist interpretations of probability are commonly known. Bayesian or subjective interpretation of probability is receiving increasing attention. This paper describes an activity to help students differentiate between the three types of probability interpretations.

Standard 3.9 of the Standards for Educational and Psychological Testing ([, 1999]) demands evidence of model fit when item response theory (IRT) models are employed to data from tests. Hambleton and Han ([Hambleton, R. K., 2005]) and Sinharay ([Sinharay, S., 2005]) recommended the assessment of practical significance of misfit of IRT models, but…

Numbers of students of color enrolling in higher educational institutions is expected to increase across all racial groups. With continued increases in minority enrollments, minority-serving institutions have and will continue to play a major role in educating student of color. A large national data set was used to examine the numbers of…

In 2011, Grantmakers for Education (GFE) partnered with the Monitor Institute to develop the K-12 Education Strategy Landscape Tool--an asset mapping tool that used interactive data visualization to provide a clear picture of the who, what, where, and when of education grantmaking. The prototype launched in January of 2012. Over a dozen funders…

Sequence classification is an important problem in many real-world applications. Unlike other machine learning data, there are no "explicit" features or signals in sequence data that can help traditional machine learning algorithms learn and predict from the data. Sequence data exhibits inter-relationships in the elements that are…

We consider the relative performance of two common approaches to multiple imputation (MI): joint multivariate normal (MVN) MI, in which the data are modeled as a sample from a joint MVN distribution; and conditional MI, in which each variable is modeled conditionally on all the others. In order to use the multivariate normal distribution,…

Of the many inequities in the education system, gaps in access to strong teaching have proven to be among the most stubborn. That is not to say that there are not excellent teachers in high-poverty schools. Research shows an indisputable and wide-spread pattern in schools and districts across the country: Low-income children and children of color…