When performing an aggregate data meta-analysis of a continuous outcome, researchers often come across primary studies that report the sample median of the outcome. However, standard meta-analytic methods typically cannot be directly applied in this setting. In recent years, there has been substantial development in statistical methods to…

Item response theory (IRT) models typically rely on a normality assumption for subject-specific latent traits, which is often unrealistic in practice. Semiparametric extensions based on Dirichlet process mixtures (DPMs) offer a more flexible representation of the unknown distribution of the latent trait. However, the use of such models in the IRT…

Undergraduate institutions serve as stepping stones to students' careers. Teaching and learning in science classrooms require quality and integrated teaching-research learning experiences that prepare students to advance their careers. Using publicly available data sets and open-access data analyses software can be impactful for engaging students…

In order to promote the use of increasingly available large-scale assessment data in education and expand the scope of analytic capabilities among applied researchers, this study provides step-by-step guidance, and practical examples of syntax and data analysis using Maples. Concise overview and key unique aspects of large-scale assessment data…

Structural equation models comprise a large class of popular statistical models, including factor analysis models, certain mixed models, and extensions thereof. Model estimation is complicated by the fact that we typically have multiple interdependent response variables and multiple latent variables (which may also be called random effects or…

Background: Several statistical applications including Mplus, STATA, and R are available to conduct analyses such as structural equation modeling and multi-level modeling using large-scale assessment data that employ complex sampling and assessment designs and that provide associated information such as sampling weights, replicate weights, and…

The purpose of this study was to write programs to define sampling sizes and observation units by probability sampling methods and to provide an idea for software developers. The algorithms of the programs were written in Python 3. The programs may be run by double-clicking on the Windows operating system or by the command prompt of the DOS…

This guide will help researchers design and implement impact studies in education so that the findings are more generalizable to the study's target population. Guidance is provided on key steps that researchers can take, including defining the target population, selecting a sample of schools--and replacement schools, when needed--managing school…

Background: Standard methods for analysing data from large-scale assessments (LSA) cannot merely be adopted if hierarchical (or multilevel) regression modelling should be applied. Currently various approaches exist; they all follow generally a design-based model of estimation using the pseudo maximum likelihood method and adjusted weights for the…

Within psychology and the social sciences, Ordinary Least Squares (OLS) regression is one of the most popular techniques for data analysis. In order to ensure the inferences from the use of this method are appropriate, several assumptions must be satisfied, including the one of constant error variance (i.e. homoskedasticity). Most of the training…

The rapid development in the world of technology and communication has contributed directly to the teaching and learning process in schools. Therefore, a paradigm shift towards learning methods in the education system needs to be implemented to meet the educational aims of the 21st century. This is due to the current methods of delivery in…

The objectives of this research on Cognitive Technology for Academic Counselling in the New Normal were (1) to design an architecture of cognitive technology for academic counselling in the new normal, (2) to develop a system of cognitive technology for academic counselling in the new normal, (3) to assess the academic performance of students…

RTI International created a geospatial grid-based sampling methodology that: achieved a probability-based household sample and unbiased estimates; was comparable across countries; used simple frame data available from the in-country census; and was efficient with minimal training to local field staff. The methodology used 1 km[superscript 2]…

Increasingly students, particularly those in the social sciences, work with survey data collected through a more complex sampling method than a simple random sample. Failing to understand how to properly approach survey data can lead to inaccurate results. In this article, we describe a series of online data visualization applications and…

In this research, it is aimed to examine the graduate theses done about flipped classroom model in Turkey according to some variables. The data of this descriptive study which was conducted by a qualitative research approach was obtained from 105 master's and doctoral theses accessed from CoHE National Thesis Center database. The data were…