The current research aimed to examine the relationships among three key aspects of the language learning process, namely, foreign language boredom (FLB), English language engagement (ELE), and academic buoyancy (AB), utilizing data collected from 2,992 Chinese language learners. In order to strengthen the accuracy and robustness of the results, we…

The aim of this research is intended to examine the effect of mathematics and statistics perception towards students' statistical literacy. The research utilized a survey method with quantitative approach. The research population was undergraduate students from major informatics in one of university in Jakarta. The sample consisted of 80 students,…

Today, 35 states use performance-based funding models tying appropriations directly to educational outcomes. Financial incentives should induce colleges to improve performance, but there are several well-documented reasons why this is unlikely to occur. We examine how two of the most robust performance funding states--Tennessee and Ohio--responded…

Whether supervision of doctoral students is best pursued individually or collectively is a recurring but unresolved question in debates on higher education. The rarity of longitudinal data and the common usage of qualitative methods to analyse a limited number of cases have left the effectiveness of either model largely untested. To assist with…

We present a short, inquiry-based learning course on concepts and methods underlying ordinary least squares (OLS), least absolute deviation (LAD), and quantile regression (QR). Students investigate squared, absolute, and weighted absolute distance functions (metrics) as location measures. Using differential calculus and properties of convex…

Multilayer perceptron neural networks, Gaussian naive Bayes, and logistic regression classifiers were compared when used to make early predictions regarding one-year college student persistence. Two iterations of each model were built, utilizing a grid search process within 10-fold cross-validation in order to tune model parameters for optimal…

Specialized imputation routines for multilevel data are widely available in software packages, but these methods are generally not equipped to handle a wide range of complexities that are typical of behavioral science data. In particular, existing imputation schemes differ in their ability to handle random slopes, categorical variables,…

We propose new methods for identifying and classifying aberrant response patterns (ARPs) by means of functional data analysis. These methods take the person response function (PRF) of an individual and compare it with the pattern that would correspond to a generic individual of the same ability according to the item-person response surface. ARPs…

This article discusses the basics of the "4 scales of measurement" and how they are applicable to research or everyday tools of life. To do this you will be able to list and describe the four types of scales of measurement used in quantitative research; provide examples of uses of the four scales of measurement; and determine the…

When given the opportunity, liars will embed their lies into otherwise truthful statements. In what way this embedding affects the quality of lies, however, remains largely unknown. This study investigated whether lies that are embedded into truthful stories are richer in detail and contain higher quality details compared to lies that are part of…

Despite the prevalence of quantitative approaches in applied linguistics (AL) and second language acquisition (SLA) research (Gass, 2009), evidence indicates a need for improvement in analyzing and reporting SLA data (e.g., Larson-Hall & Plonsky, 2015). However, to improve quantitative research, researchers must possess the statistical…

Rater fit analyses provide insight into the degree to which rater judgments correspond to expected properties, as defined within a measurement framework. Parametric models such as the Rasch model provide a useful framework for evaluating rating quality; however, these models are not appropriate for all assessment contexts. The purpose of this…

Research on statistical education in childhood is recent in Brazil. The research has been mainly driven by curriculum reforms and the creation of research groups that investigate teaching, learning, and teacher education practices. The present paper emerges from this scenario and has the aim of investigating practices of creative insubordination…

We trained a computational model (the Chunk-Based Learner; CBL) on a longitudinal corpus of child-caregiver interactions in English to test whether one proposed statistical learning mechanism--backward transitional probability--is able to predict children's speech productions with stable accuracy throughout the first few years of development. We…

In order to reach valid and reliable test scores, various test theories have been developed, and one of them is nonparametric item response theory (NIRT). Mokken Models are the most widely known NIRT models which are useful for small samples and short tests. Mokken Package is useful for Mokken Scale Analysis. An important issue about validity is…