Data-based decision-making has the potential to increase student achievement results. Data-based decision-making can be defined as teachers' systematic analysis of data sources in order to study and adapt their educational practices for the purpose of maximizing learning results. Teachers must apply the findings from their data use to their…

In the context of "academic momentum," a longitudinal study of university students (N = 904) showed high school achievement and ongoing university achievement predicted subsequent achievement through university. However, the impact of high school achievement diminished, while additive effects of ongoing university achievement continued.…

This study examined the relationship of student and faculty demographics on Science Technology Engineering and Mathematics (STEM) student success and persistence as mediated by student perceptions of faculty validation. This study will contribute to an understanding of the complex relationships that exist between these variables, an area that has…

Recent years have seen increased interest in data-driven decision making in education; that is, using various types of data, particularly quantitative assessment data, to inform a range of decisions in schools and classrooms. At the same time, districts, states, and schools have invested resources in tools designed to provide teachers, principals,…

The utility of several longitudinal data analysis models for use with educational attainment are discussed and illustrated on a large data set. Assumptions of the models, choice of scale units, and data transformations, as well as real-life implications are emphasized. (Author/JKS)

Duncan's interpretation of his research on the nature and process of the distribution of rewards in the U.S. stratification system is questioned. Statistical and conceptual flaws are noted in Duncan's work and their implications explored. A reanalysis of primary survey data is presented and, based on a reinterpretation of this data, a…

The authors' approach to using pattern-centered analyses and longitudinal data addresses how configurations of personal and contextual factors forecast the educational achievement and attainments of different youth across adolescence. Here, they discuss various types of pattern-centered analyses and provide an empirical illustration of how these…

Tries to develop a method for empirical evaluations of the impact of a school system on measurable cognitive and affective outcomes in students. Concentrates on the Partial Least Squares (PLS) methodology, and illustrates the potential of PLS for system analysis. (BW)

To track student progress and develop a model of the total academic process at Prince George's Community College (PGCC), the Office of Institutional Research and Analysis acquired 5 years of background, behavioral, and outcome data for a cohort of first-time students entering the college. The academic process was broken down into three divisions:…