The use of machine translation has become a topic of debate in language learning, which highlights the need to thoroughly examine the appropriateness and role of machine translation in educational settings. Under the theoretical framework of task-technology fit, this explanatory case study set out to investigate the predictive role of machine…

Grounded in the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), this study investigates the interplay between key UTAUT2 constructs and motivation modeled by Self-Determination Theory (SDT) in shaping English as a Foreign Language (EFL) learners' behavioral intention and actual use of generative AI tools. Accordingly, three research…

Advanced modeling of item response data through the item response theory (IRT) or item factor analysis frameworks is becoming increasingly popular. In the social and behavioral sciences, the underlying structure of tests/assessments is often multidimensional (i.e., more than 1 latent variable/construct is represented in the items). This review…

Interest in Bayesian analysis of item response theory (IRT) models has grown tremendously due to the appeal of the paradigm among psychometricians, advantages of these methods when analyzing complex models, and availability of general-purpose software. Possible models include models which reflect multidimensionality due to designed test structure,…

The method of least-squares (LS) has a built-in procedure for estimating the standard errors (SEs) of the adjustable parameters in the fit model: They are the square roots of the diagonal elements of the covariance matrix. This means that one can use least-squares to obtain numerical values of propagated errors by defining the target quantities as…

This research is a descriptive study based on the testing of a structural model developed by considering the effects of perceived social support and subjective well-being on adolescents' risky behaviors, and the possible mediating role of self-esteem. Participants consisted of 676 high school students attending formal education institutions,…

The "e-rater"® automated essay scoring system is used operationally in the scoring of the argument and issue tasks that form the Analytical Writing measure of the "GRE"® General Test. For each of these tasks, this study explored the value added of reporting 4 trait scores for each of these 2 tasks over the total e-rater score.…

In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…

This comprehensive "Handbook" focuses on the most used polytomous item response theory (IRT) models. These models help us understand the interaction between examinees and test questions where the questions have various response categories. The book reviews all of the major models and includes discussions about how and where the models…

Structural equation models require formidable computational techniques. Testing the goodness of fit involves discrepancies between original correlations among variables and correlations estimated by solved path coefficients. A BASIC computer program which solves these problems is presented and discussed. (Author/GDC)

Since computer programs have been available for estimating and testing linear causal models, these models have been used increasingly in the behavioral sciences. This paper discusses the problem that very different causal structures may fit the same set of data equally well. (Author/LMO)

Two-level data sets are frequently encountered in social and behavioral science research. They arise when observations are drawn from a known hierarchical structure, as when individuals are randomly drawn from groups that are randomly drawn from a target population. When the covariance structures in the group level and the individual level are the…

Using data from High School and Beyond, this study empirically investigated the extent of within-variable, between-occasion error covariances among variables included in educational achievement models. Little evidence was found to support the statement that reliability estimates for social background variables are inflated because of correlated…

This study examined the effect of type of correlation matrix on the robustness of LISREL maximum likelihood and unweighted least squares structural parameter estimates for models with categorical manifest variables. Two types of correlation matrices were analyzed; one containing Pearson product-moment correlations and one containing tetrachoric,…

The advantages of applying confirmatory factor analysis (CFA) to multitrait-multimethod (MTMM) data are widely recognized. However, because CFA as traditionally applied to MTMM data incorporates single indicators of each scale (i.e., each trait/method combination), important weaknesses are the failure to: (1) correct appropriately for measurement…