The aim of this study is to develop a reliable and valid scale to determine individuals' attitudes toward artificial intelligence. The study was conducted during the spring semester of 2024 with the participation of pre-service teachers studying at the Faculty of Education at Mugla Sitki Koçman University in Turkey. A total of 410 pre-service…

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…

Computational thinking is a way of thinking that covers 21st century skills and includes new generation concepts such as robotics, coding, informatics and information construction. Computational thinking has reached an important point especially in the field of science in line with the rapid developments in technology. Robotics applications,…

A promising "underlying bivariate normal" approach was proposed by Jöreskog and Moustaki for use in the factor analysis of ordinal data. This was a limited information approach that involved the maximization of a composite likelihood function. Its advantage over full-information maximum likelihood was that very much less computation was…

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,…

Objective: Based on the technology acceptance model (TAM), we explored the nationally-bounded roles of four predictors (subjective norms, entertainment, recordability, and networkability) in determining the TAM variables of perceived usefulness (PU), perceived ease of use (PEOU), and behavioral intention (BI) to use diet/fitness apps on…

The purpose of this study was to investigate whether achievement motivations influence the adoption of learning strategies and learning strategies influence studying behavior in an online learning environment. The Goal Orientation Questionnaire was used to measure achievement motives, and the Motivated Strategies for Learning Questionnaire was…

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.…

CEFA 3.02(Browne, Cudeck, Tateneni, & Mels, 2008) is a factor analysis computer program designed to perform exploratory factor analysis. It provides the main properties that are needed for exploratory factor analysis, namely a variety of factoring methods employing eight different discrepancy functions to be minimized to yield initial…

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…

Takes several goodness-of-fit statistics as measures of variable selection and develops backward elimination and forward selection procedures in exploratory factor analysis. A newly developed variable selection program, SEFA, can print several fit measures for a current model and models obtained by removing an internal variable or adding an…

Exploratory factor analysis (EFA) is a frequently used multivariate analysis technique in statistics. Jennrich and Sampson (1966) solved a significant EFA factor loading matrix rotation problem by deriving the direct Quartimin rotation. Jennrich was also the first to develop standard errors for rotated solutions, although these have still not made…

Considers models incorporating principal components from the perspectives of structural-equation modeling. These models include the following: (1) the principal-component analysis of patterned matrices; (2) multiple analysis of variance based on principal components; and (3) multigroup principal-components analysis. Discusses fitting these models…

Describes a method for evaluating results of Procrustean rotation to a target factor pattern matrix in exploratory factor analysis. The approach, based on the bootstrap method, yields empirical approximations of the sampling distributions of: (1) differences between target elements and rotated factor pattern matrices; and (2) the overall…