The present study illustrates the utility of applying multilevel mixture models in educational research, using data on the homework behavior of 1,812 Swiss eighth-grade students in French as a second language. A previous person-centered study identified 5 homework learning types characterized by different patterns of high or low homework time and…

In this study, international research collaboration (IRC) and international research orientation (IRO) have been studied at the micro-level of individual academics from the university sector (N = 8,466, 11 European systems). Both were studied cross-nationally, cross-disciplinarily, and cross-generationally. This study differs from most existing…

Despite a surge of empirical work on student participation in online learning environments, the causal links between the learning-related factors and processes with the desired learning outcomes remain unexplored. This study presents a systematic literature review of approaches to model learning in Massive Open Online Courses offering an analysis…

Higher education for the 21st century continues to promote discoveries in the field through learning analytics (LA). The problem is that the rapid embrace of of LA diverts educators' attention from clearly identifying requirements and implications of using LA in higher education. LA is a promising emerging field, yet higher education stakeholders…

Purpose: Across the United States, a large percentage of school districts are in need of facility improvements to provide safe and adequate buildings to facilitate student learning. To finance new construction, school districts traditionally have put proposals before local voters to fund construction through issuing long-term bonds to finance…

The purpose of this project is to demonstrate the practical methods developed to utilize a dataset consisting of both multivariate and multilevel effect size data. The context for this project is a large-scale meta-analytic review of the predictors of academic achievement. This project is guided by three primary research questions: (1) How do we…

Nearly all quantitative analyses in higher education draw from incomplete datasets-a common problem with no universal solution. In the first part of this paper, we explain why missing data matter and outline the advantages and disadvantages of six common methods for handling missing data. Next, we analyze real-world data from 5,905 students across…

With the goal of increasing students' academic readiness for college, high schools in the United States are increasingly offering "credit-based transition programs," including International Baccalaureate (IB), Advanced Placement (AP), and dual enrollment. Existing research points to the promise of IB, AP, and other credit-based…

The survey-based research reported here offers insights on community, resource, and economic development (CRED) Extension programming at the national and regional level. The results present a national picture of CRED programming, research, and potential future programming opportunities that Extension could capitalize on. The research shows that…

The present study aimed to identify and interpret concerns of the new faculty members in Jordanian universities. A total of 336 new faculty members who participated in this study were asked to rate their perceptions of issues related to teaching, research, service, balancing work and home life and the academic culture of their workplace. Means and…

A small multivariate data set is used to illustrate the usefulness of structure coefficients when interpreting results of educational experiments. Data are analyzed using a multivariate analysis of variance (MANOVA), and results are interpreted in three different ways to determine the contribution of individual variables to prediction: (1) using…

Commonality analysis may be used as an adjunct to general linear methods as a means of determining the degree of predictive ability shared by two or more independent variables. For each independent variable, commonality analysis indicates how much of the variance of the dependent variable is unique to the predictor and how much of the predictor's…

Advantages of the use of multivariate commonality analysis are discussed and a small data set is used to illustrate the analysis and as a model to enable readers to conduct such an analysis. A noteworthy advantage of commonality analysis is that commonality honors the relationships among variables by determining the degree to which predictors in a…

This paper discusses the principles underlying discriminant analysis and constructs a simulated data set to illustrate its methods. Discriminant analysis is a multivariate technique for identifying the best combination of variables to maximally discriminate between groups. Discriminant functions are established on existing groups and used to…

A review of 26 multivariate or "production function" studies provides the basis for this discussion of the determinants of student cognitive achievement in developing countries. The paper describes the studies and reviews the results for each of the major determinants of academic achievement--schooling characteristics, teacher attributes, and…