Background: With the increasing interdisciplinarity between computer science (CS) and other fields, a growing number of non-CS students are embracing programming. However, there is a gap in research concerning differences in programming learning between CS and non-CS students. Previous studies predominantly relied on outcome-based assessments,…

Gross Domestic Product of any country often influence economic decisions by policy makers, market participants and econometricians on policy recommendations, evaluation and forecasting. However these decisions are often based on preliminary data announcements by statistical agencies. It is therefore important to ensure that the preliminary GDP…

There are many potential ways to represent arithmetical tasks, but students' choices may be limited by beliefs that only certain standardised representations are "legitimate" in school mathematics. Furthermore, concern for the quantity and speed of "work done" can override opportunities for meaningful engagement with the…

Even in primary school, mathematics achievement depends upon the efficiency of cognitive, metacognitive and self-regulatory processes. Thus, for pupils to carry out a computation, such as a written calculation, metacognitive mechanisms play a crucial role, since children must employ self-regulation to assess the precision of their own thinking and…

This article promotes the use of modern test theory in testing situations where sum scores for binary responses are now used. It directly compares the efficiencies and biases of classical and modern test analyses and finds an improvement in the root mean squared error of ability estimates of about 5% for two designed multiple-choice tests and…

Biased sampling occurs frequently in economics, epidemiology, and medical studies either by design or due to data collecting mechanism. Failing to take into account the sampling bias usually leads to incorrect inference. We propose a unified estimation procedure and a computationally fast resampling method to make statistical inference for…

Nonlinear multilevel latent variable modeling has been suggested as an alternative to traditional hierarchical linear modeling to more properly handle measurement error and sampling error issues in contextual effects modeling. However, a nonlinear multilevel latent variable model requires significant computational effort because the estimation…

In a selected response test, aberrant responses such as careless errors and lucky guesses might cause error in ability estimation because these responses do not actually reflect the knowledge that examinees possess. In a computerized adaptive test (CAT), these aberrant responses could further cause serious estimation error due to dynamic item…

The objective of this paper is to measure the efficiency of high schools in Tunisia. We use a statistical data envelopment analysis (DEA)-bootstrap approach with quasi-fixed inputs to estimate the precision of our measure. To do so, we developed a statistical model serving as the foundation of the data generation process (DGP). The DGP is…

The aim of the present paper is to examine the observed differences in Students' test performance across public and private-voucher schools in Spain. For this purpose, we explicitly consider that education is a multi-input multi-output production process subject to inefficient behaviors, which can be identified at student level using a parametric…

In this paper we examine the ultimatum game's income distribution and efficiency implications and modify the game to investigate the impact of re-distributional policies imposed on the parties.