Partially compensatory models may capture the cognitive skills needed to answer test items more realistically than compensatory models, but estimating the model parameters may be a challenge. Data were simulated to follow two different partially compensatory models, a model with an interaction term and a product model. The model parameters were…

Growth curve modeling provides a general framework for analyzing longitudinal data from social, behavioral, and educational sciences. Bayesian methods have been used to estimate growth curve models, in which priors need to be specified for unknown parameters. For the covariance parameter matrix, the inverse Wishart prior is most commonly used due…

A quantitative study was conducted to get the perspectives of IT experts about risks in enterprise cloud computing. In businesses, these IT experts are often not in positions to prioritize business needs. The business experts commonly known as business managers mostly determine an organization's business needs. Even if an IT expert classified a…

We present a logistic function of a monotonic polynomial with a lower asymptote, allowing additional flexibility beyond the three-parameter logistic model. We develop a maximum marginal likelihood based approach to estimate the item parameters. The new item response model is demonstrated on math assessment data from a state, and a computationally…

How to identify at-risk students in open online courses has received increasing attention, since the dropout rate is unexpectedly high. Most prior studies have focused on using machine learning techniques to predict student dropout based on features extracted from students' learning activity logs. However, little work has viewed the dropout…

Student engagement in education is key to ensuring successful learning. Engagement becomes crucial as students progress through high school and transition into young adulthood; however, engaging them in high school can be an arduous task. A career/education plan can help students make strong connections between their work in high school and their…

We examined Differential Item Functioning (DIF) and the size of cross-cultural performance differences in the Programme for International Student Assessment (PISA) 2012 mathematics data before and after application of propensity score matching. The mathematics performance of Indonesian, Turkish, Australian, and Dutch students on released items was…

While 'flipped' classrooms have been heralded as a valuable tool for student learning, little is known about the process by which students learn from the out-of-class resources. This study investigates 12 undergraduate students' sense-making activities while watching videos about topics in introductory statistics. Analysis of interview data…

We explore the transition from school to university through a commognitive (Sfard 2008) analysis of twenty-two students' examination scripts from the end of year examination of a first year, year-long module on Sets, Numbers, Proofs and Probability in a UK mathematics department. Our analysis of the scripts relies on a preliminary analysis of the…

Using propensity score matching method, this study examined the effect of boarding on campus on left-behind children (LBC)'s sense of school belonging and their academic achievement. The condition of boarding schools was also examined closely in this study. Data were collected from 6,638 students from 74 rural boarding schools in 11 provinces in…

This report contains reliability and validity evidence for the North Carolina Kindergarten Entry Assessment system (KEA) using a statewide sample of kindergarten children. The KEA was designed as a formative, developmental, authentic, and criterion referenced classroom resource for teachers. As a formative assessment, the KEA focuses on the…

Estimating the effect of campus math tutoring support, this study demonstrates the use of propensity score weighted and matched-data analysis and examines the correspondence with results from parametric regression analysis.

Although a large-scale experiment can provide an estimate of the average causal impact for a program, the sample of sites included in the experiment is often not drawn randomly from the inference population of interest. In this article, we provide a generalizability index that can be used to assess the degree of similarity between the sample of…

The aprioristic (classical, naïve and symmetric) and frequentist interpretations of probability are commonly known. Bayesian or subjective interpretation of probability is receiving increasing attention. This paper describes an activity to help students differentiate between the three types of probability interpretations.

We consider the relative performance of two common approaches to multiple imputation (MI): joint multivariate normal (MVN) MI, in which the data are modeled as a sample from a joint MVN distribution; and conditional MI, in which each variable is modeled conditionally on all the others. In order to use the multivariate normal distribution,…