This dissertation's two primary purposes were to construct an alternative socioeconomic status model and estimate how it predicts student success in higher education. This research filled a gap in knowledge about the widely acknowledged disparities in higher education based on socioeconomic status. Prior research has often relied on parental…

Today's schools emphasize the use of student data to make instructional decisions. Standardized tests determine funding and teacher advancement (Datnow, Park, & Wholstetter, 2007; Gullo, 2013; Marchant & Paulson, 2009; Schraw, 2010). To evaluate learning before these tests, teachers must utilize their own assessments and data. Formative…

The present article aims to show how to model longitudinal change in cohort sequential data applying latent true change models using Mplus' multi-group approach. The underlying modeling ideas are described and explained in this article. As an example, change in internalizing problem behaviors between the age of 8 and 13 years is modeled and…

It is an exhilarating and important time for conducting research on learning, with unprecedented quantities of data available. There is a danger, however, in thinking that with enough data, the numbers speak for themselves. In fact, with larger amounts of data, theory plays an ever-more critical role in analysis. In this introduction to the…

This paper explores how factors operating at the state and community levels are associated with the prevalence of late school enrolment in Nigeria. We investigate the following three research themes. First, whether late entry varies across states and across communities and how much of this variation can be explained by the composition of…

Mathematics competency is fast becoming an essential requirement in ever greater parts of day-to-day work and life. Thus, creating strategies for improving mathematics learning in students is a major goal of education research. However, doing so requires an ability to look at many aspects of mathematics learning, such as demographics and…

Analyzing data that possess some form of nesting is often challenging for applied researchers or district staff who are involved in or in charge of conducting data analyses. This report provides a description of the challenges for analyzing nested data and provides a primer of how multilevel regression modeling may be used to resolve these…

Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. "Regression Analysis by Example, Fifth Edition" has been expanded and thoroughly…

This paper draws attention to a subtle, but concerning, empirical challenge common in panel data models that seek to estimate the relationship between student transfers and district academic performance. Specifically, if such models have a dynamic element, and if the estimator controls for unobserved traits by including district-level effects,…

The use of dual credit has been expanding rapidly. Dual credit is a college course taken by a high school student for which both college and high school credit is given. Previous studies provided limited quantitative evidence that dual credit/dual enrollment is directly connected to positive student outcomes. In this study, predictive statistics…

The authors examined the needs of digital information service web portal users. More specifically, the needs of Korean cultural portal users were examined as a case study. The conceptual framework of a web-based portal is that it is a complex, web-based service application with characteristics of information systems and service agents. In…

The goal of this article is to present a series of conceptual, statistical, and practical issues in the modeling of multi-level dyadic data. Distinctions are made between distinguishable and undistinguishable dyads and several types of independent variables modeled at the dyadic level of analysis. Multi-level modeling equations are explained in a…

Community colleges continue to experience growth in online courses. This growth reflects the need to increase the numbers of students who complete certificates or degrees. Retaining online students, not to mention assuring their success, is a challenge that must be addressed through practical institutional responses. By leveraging existing student…

Data mining of IPEDS data is used to develop models that calculate predicted graduation rates for two- and four-year institutions. (Contains 7 tables and 5 figures.)

Earlier studies have suggested that higher education institutions could harness the predictive power of Learning Management System (LMS) data to develop reporting tools that identify at-risk students and allow for more timely pedagogical interventions. This paper confirms and extends this proposition by providing data from an international…