Precisely estimating factor scores is challenging, especially when models are mis-specified. Stemming from network analysis, centrality measures offer an alternative approach to estimating the scores. Using a two-fold simulation design with varying availability of a priori theoretical knowledge, this study implemented hybrid centrality to estimate…

As evidence from evaluation and experimental studies continue to influence decision and policymaking, applied researchers and practitioners require tools to derive valid and credible inferences. Over the past several decades, research in causal inference has progressed with the development and application of propensity scores. Since their…

Traditional estimators of reliability such as coefficients alpha, theta, omega, and rho (maximal reliability) are prone to give radical underestimates of reliability for the tests common when testing educational achievement. These tests are often structured by widely deviating item difficulties. This is a typical pattern where the traditional…

There is a longstanding debate on whether the analysis of covariance (ANCOVA) or the change score approach is more appropriate when analyzing non-experimental longitudinal data. In this article, we use a structural modeling perspective to clarify that the ANCOVA approach is based on the assumption that all relevant covariates are measured (i.e.,…

The use of the aggregate scoring method for scoring concordance tests requires the weighting of test items to be derived from the performance of a group of experts who take the test under the same conditions as the examinees. However, the average score of experts constituting the reference panel remains a critical issue in the use of these tests.…

Though a substantial amount of research exists on imputing missing scores in educational assessments, there is little research on cases where responses or scores to an item are missing for all test takers. In this paper, we tackled the problem of imputing missing scores for tests for which the responses to an item are missing for all test takers.…

This study was conducted to further research into the impact of student-group item parameter drift (SIPD) --referred to as subpopulation item parameter drift in previous research-- on ability estimates and proficiency classification accuracy when occurring in the discrimination parameter of a 2-PL item response theory (IRT) model. Using Monte…

The aim of research is to reveal the effect of a training program based on the TAWOCK model for teaching computational thinking skills on teaching self-efficacy among computer teachers. It used the quasi-experimental approach, with a pre-test and post-test design with a control group. An electronic training program based on the TAWOCK model was…

Background/Context: Confirmatory factor analysis (CFA) model is a commonly adopted framework to estimate and test a measurement model. Once a well-fitting final CFA model is selected, the selected model may be used to test structural relationships of the latent constructs with other variables, to construct a test with desired reliability and…

The research aims to explore the acquisition of Computational Thinking (CT) sub-skills among 5th and 6th grade secondary school students in Turkey through a block-based programming application, code.org. It seeks to understand if mastering these skills is essential for students globally. This study involved seven volunteer students selected…

Background: Computational thinking (CT) is an essential skill for preparing the younger generation to succeed in an AI-driven world, with pair programming emerging as a widely used approach to foster these skills. However, the role of individual factors and mutual engagement in shaping CT skills within pair programming remains underexplored,…

We develop a "latent variable forest" (LV Forest) algorithm for the estimation of latent variable scores with one or more latent variables. LV Forest estimates unbiased latent variable scores based on "confirmatory factor analysis" (CFA) models with ordinal and/or numerical response variables. Through parametric model…

Technological Pedagogical Content Knowledge (TPACK) is a theoretical framework used to assess information teaching. However, its application and popularity in practice is limited due to usability and accuracy issues. This study presents a quantitative model called TPACK-Venn, which is based on the graphical calculation of a Venn diagram determined…

The multistage testing (MST) design has been gaining attention and popularity in educational assessments. For testing programs that have small test-taker samples, it is challenging to calibrate new items to replenish the item pool. In the current research, we used the item pools from an operational MST program to illustrate how research studies…

Although many textbooks on multivariate statistics discuss the common factor analysis model, few of these books mention the problem of factor score indeterminacy (FSI). Thus, many students and contemporary researchers are unaware of an important fact. Namely, for any common factor model with known (or estimated) model parameters, infinite sets of…