Machine learning and data mining techniques have been widely used in educational settings to identify the important features that tend to influence students' learning performance and predict their future performance. However, there is little to no research done in the context of Singapore's education. Hence, this study aims to fill the gap by…

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…

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…

Data simulation and Monte Carlo simulation studies are important skills for researchers and practitioners of educational and psychological measurement, but there are few resources on the topic specific to item response theory. Even fewer resources exist on the statistical software techniques to implement simulation studies. This article presents…

Aim/Purpose: This mixed-methods study aims to examine factors influencing academicians' intentions to continue using AI-based chatbots by integrating the Task-Technology Fit (TTF) model and social network characteristics. Background: AI-powered chatbots are gaining popularity across industries, including academia. However, empirical research on…

Cognitive diagnostic models (CDM) have been around for more than a decade but their application is far from widespread for mainly two reasons: (1) CDMs are novel, as compared to traditional IRT models. Consequently, many researchers lack familiarity with them and their properties, and (2) Software programs doing CDMs have been expensive and not…

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 purpose of the present study is to investigate indifference management structural model in education system of Ardabil Province. The research method was integration study using Alli modeling. Statistical society of research was 420 assistant professors of educational science, managers, and deputies of Ardabil's second period of high schools…

A corpus of current editions of statistics textbooks was assessed to compare aspects and levels of readability for the topics of "measures of center," "line of fit," "regression analysis," and "regression inference." Analysis with lexical software of these text selections revealed that the large corpus can…

We highlight critical conceptual and statistical issues and how to resolve them in conducting Satorra-Bentler (SB) scaled difference chi-square tests. Concerning the original (Satorra & Bentler, 2001) and new (Satorra & Bentler, 2010) scaled difference tests, a fundamental difference exists in how to compute properly a model's scaling correction…

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…