Social media is the platforms where users communicate, interact, share ideas, career interest, pictures, video, etc. Social media gives an opportunity to analyze the human behavior. Crime analysis using data from social media such as Newsfeeds, Facebook, Twitter, etc., is becoming one of the emerging areas of research for law enforcement…

Successful language acquisition hinges on organizing individual words into grammatical categories and learning the relationships between them, but the method by which children accomplish this task has been debated in the literature. One proposal is that learners use the shared distributional contexts in which words appear as a cue to their…

Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the…

Bayesian algorithms have been used successfully in the social and behavioral sciences to analyze dichotomous data particularly with complex structural equation models. In this study, we investigate the use of the Polya-Gamma data augmentation method with Gibbs sampling to improve estimation of structural equation models with dichotomous variables.…

Although hypothesis testing is ubiquitous in data analysis, research suggests it is commonly misunderstood. Simulation-based inference methods have potential to make student thinking visible, thus providing a valuable lens to analyze developing conceptions about inference. This paper identifies difficulties made visible through simulation-based…

We have been looking at two different numbers that have been used to describe the availability of physics in U.S. high schools: 60% and 95%. Last month we noted that the U.S. Department of Education Office of Civil Rights (OCR) includes over 7,000 more public schools in the denominator than American Institute of Physics (AIP) Statistics does.…

Although immediacy is one of the necessary criteria to show strong evidence of a causal relation in SCDs, no inferential statistical tool is currently used to demonstrate it. We propose a Bayesian unknown change-point model to investigate and quantify immediacy in SCD analysis. Unlike visual analysis that considers only 3-5 observations in…

This paper attempts to bridge the gap between classical test theory and item response theory. It is demonstrated that the familiar and popular statistics used in classical test theory can be translated into a Bayesian framework where all of the advantages of the Bayesian paradigm can be realized. In particular, prior opinion can be introduced and…

Student misconceptions have been studied for decades from a curricular/instructional perspective and from the assessment/test level perspective. Numerous misconception assessment tools have been developed in order to measure students' misconceptions relative to the correct content. Often, these tools are used to make a variety of educational…

Background: Despite the increasing need for STEM skills, to date, the connection between STEM subject choices and their impact on students' educational pathways has not been widely studied. Focusing on the mathematics choice (basic/advanced/no mathematics), a large register dataset that covered students admitted to Finnish universities during…

In this article, we map the extent of educational inequality within Tasmania, and between Tasmania and the rest of Australia, using "National Assessment Program--Literacy and Numeracy" (NAPLAN) and senior secondary attainment data. This analysis yields some surprising findings, showing the success of Tasmanian primary and high schools…

This study investigates how lower elementary students used the technical terms in the context of ecology. We interviewed 44 students using several scenarios related to the ecosystem. We determined the general frequency of technical terms used from a preselected list commonly employed by scientists in their discourse about ecosystems. Then, we…

Students often are confused about the differences between bar graphs and histograms. The authors discuss some reasons behind this confusion and offer suggestions that help clarify thinking.

Growth curve models are widely used in social and behavioral sciences. However, typical growth curve models often assume that the errors are normally distributed although non-normal data may be even more common than normal data. In order to avoid possible statistical inference problems in blindly assuming normality, a general Bayesian framework is…

Nonnormality of univariate data has been extensively examined previously (Blanca et al., 2013; Micceri, 1989). However, less is known of the potential nonnormality of multivariate data although multivariate analysis is commonly used in psychological and educational research. Using univariate and multivariate skewness and kurtosis as measures of…