While correlated data methods (like random effect models and generalized estimating equations) are commonly applied in practice, students may struggle with understanding the reasons that standard regression techniques fail if applied to correlated outcomes. To this end, this article presents an in-class activity using results from Monte Carlo…

Interactive learning environments can generate massive learning behavior data and the support of learning behavior big data can ensure the completeness of data analysis and robustness of relationship verification. In this study, learning behaviors are divided into training set and testing set, BP neural network and recurrent Elman network are…

The MUSIC (eMpowerment, Usefulness, Success, Interest, Caring) Model of Academic motivation was developed to help instructors promote student motivation in the classroom. This study examines relationships among student perceptions of motivation and effort compared with their performance in undergraduate business analytics courses. Specifically,…

Background and Aims: The fastest growing group of students with disabilities are those with Autism Spectrum Disorder (ASD). States annually report on post-high school outcomes (PSO) of exited students. This study sought to fill two gaps in the literature related to PSO for exited high-school students with ASD and the use of state data and…

Between 1983 and 1993, grade 7/8 to grade 12 apparent retention rates more than doubled and secondary schools developed vocational education and training (VET) programmes as alternative pathways through secondary school. Previous research indicates that participation in VET programmes is associated with having low-educated parents and/or attending…

Researchers and data analysts are sometimes faced with the problem of very small samples, where the number of variables approaches or exceeds the overall sample size; i.e. high dimensional data. In such cases, standard statistical models such as regression or analysis of variance cannot be used, either because the resulting parameter estimates…

Educational materials focused on spatial data analysis often feature mathematical descriptions of methods and step-by-step instructions of software tools, but infrequently discuss the set of decisions involved in specifying a statistical model. Failing to consider model specification may lead to specification searching, or the process of repeating…

The purpose of the study is to analyze the affective traits that affect mathematics achievement through Structural Equation Modeling (SEM) as a traditional regression model and Multivariate Adaptive Regression Splines (MARS), as one of the data mining methods. Structural Equation Modeling, one of the regression-based methods, is quite popular for…

Previous U.K. population-based studies have found associations amongst early speech and language difficulties, socioeconomic disadvantage and children's word-reading ability later on. We examine the strength of these associations in a recent U.K. population-based birth cohort. Analyses were based on 13,680 participants. Linear regression models…

The deleterious effects of maternal depression on child emotional and behavioral development are well documented, yet many children exposed to maternal depression experience positive outcomes. The aim of this study was to identify psychosocial factors associated with the emotional-behavioral resilience of four-year-old children of first-time…

We perform two approaches of machine learning, logistic regressions and decision trees, to predict student dropout at the Karlsruhe Institute of Technology (KIT). The models are computed on the basis of examination data, i.e. data available at all universities without the need of specific collection. Therefore, we propose a methodical approach…

This article provides an analysis of the academic performance of higher education institutions (HEIs) in Vietnam with 50 universities and 50 colleges in 2011/12. The two-stage semiparametric data envelopment analysis is used to estimate the efficiency of HEIs and investigate the effects of various factors on their performance. The findings reveal…

Every day, students collect, organize, and analyze data to make decisions. In this data-driven world, people need to assess how much trust they can place in summary statistics. The results of every survey and the safety of every drug that undergoes a clinical trial depend on the correct application of appropriate statistics. Recognizing the…

The goal of this paper is to promote computational thinking among mathematics, engineering, science and technology students, through hands-on computer experiments. These activities have the potential to empower students to learn, create and invent with technology, and they engage computational thinking through simulations, visualizations and data…

This research predicts transfer readiness of student's characteristics and enrollment in CTE pathway; and most significantly addressed statewide CTE transfer students that meet the transfer requirements under CTE Taxonomy of program (TOP) code for students who transfer to a California State University (CSU), and Private or out-of-state university.…