This study explored the interaction between student characteristics and the online environment in predicting course performance and subsequent college persistence among students in a large urban U.S. university system. Multilevel modeling, propensity score matching, and the KHB decomposition method were used. The most consistent pattern observed…

This "Practitioner's Guide to Growth Models," commissioned by the Technical Issues in Large-Scale Assessment (TILSA) and Accountability Systems & Reporting (ASR), collaboratives of the "Council of Chief State School Officers," describes different ways to calculate student academic growth and to make judgments about the…

Disproportionately large numbers of Black youth experience repeated encounters with the juvenile justice system, and often these same youth present with a variety of school-related difficulties. Data from a sample of 842 Black males, assessed in five Ohio juvenile courts using the Global Risk Assessment Device (GRAD), are used to describe the…

This article reports a study on using data mining to predict K-12 students' competence levels on test items related to energy. Data sources are the 1995 Third International Mathematics and Science Study (TIMSS), 1999 TIMSS-Repeat, 2003 Trend in International Mathematics and Science Study (TIMSS), and the National Assessment of Educational…

Multi-group discriminant analysis was used to identify the pre-enrollment demographic and academic factors that best separate the success classes in the first-year examinations of science students at the University of Benin. The predictor of success was performance in specialist subjects of the matriculation examination. (Author/MLW)

Multivariate statistical analysis determined relationships between scores on the Otis-Lennon School Ability Test and the Stanford Achievement Test at grades 2, 4, and 6 for 272 students. The best predictor of achievement at a later grade was achievement at an earlier grade. Implications are discussed. (SLD)