Researchers increasingly identify virtual reality (VR) simulations as a potentially effective professional development tool. However, simulations used in education and behavior analysis typically require active oversight from technicians and instructors. "Smart" VR integrated with artificial intelligence could independently administer…

New questions and concerns arise every day about the impact of AI in schools, such as how teachers will learn about AI and leverage it in their classrooms, how they can use it to develop their own teaching expertise, and if AI for educators really leads to better teaching and learning. The authors believe that AI can help teachers become more…

We present a bias-adjusted three-step estimation approach for multilevel latent class models (LC) with covariates. The proposed approach involves (1) fitting a single-level measurement model while ignoring the multilevel structure, (2) assigning units to latent classes, and (3) fitting the multilevel model with the covariates while controlling for…

The purpose of this single-case experimental design (SCED) study is to investigate how adaptive prompts in virtual reality (VR)-based social skills training affect the social skills performance of autistic children. Adaptive prompts are driven by autistic children's emotional states. To integrate adaptive prompts in VR-based training, we conducted…

Immersive technologies have gained attention in design pedagogy due to their potential as effective tools for teaching and learning. Virtual reality (VR) has been extensively explored in the design discipline for tasks such as interpretation, visualization, and collaboration. However, most applications of VR have focused on replacing traditional…

This report provides advice to policymakers and school leaders on the use of assessment centres as part of a teacher selection approach. It discusses the relationship between assessment centre scores prior to joining teaching, and teacher effectiveness over a six-year period. It draws from various stages of a wider research project, the overall…

Individuals with homonymous visual field loss (HVFL) fail to perceive visual information that falls within the blind portions of their visual field. This places additional burden on memory to represent information in their blind visual field, which may make visual changes in the scene more difficult to detect. Failing to detect changes could have…

Detection methods for item preknowledge are often evaluated in simulation studies where models are used to generate the data. To ensure the reliability of such methods, it is crucial that these models are able to accurately represent situations that are encountered in practice. The purpose of this article is to provide a critical analysis of…

The objective of this study is to identify and analyze the scientific literature with a bibliometric analysis to find the main topics, authors, sources, most cited articles, and countries in the literature on virtual reality in education. Another aim is to understand the conceptual, intellectual, and social structure of the literature on the…

The aim of this study is to compare reading comprehension levels of two groups of students--an experimental and a control group--who read the same texts in course books using either augmented reality technique or traditional reading technique. Barrett's taxonomy, which proposes a classification of reading comprehension, consisting of literal…

Augmented Reality Game-Based Learning (ARGBL) is becoming increasingly relevant in Technology-Enhanced Learning. Games with AR characteristics, or even AR applications structured with rules and game elements, are proving to be effective and successful learning experiences. There is a need to include teachers in the design process. In this paper,…

A common problem in the analysis of multiple data sources, including individual participant data meta-analysis (IPD-MA), is the misclassification of binary variables. Misclassification may lead to biased estimators of model parameters, even when the misclassification is entirely random. We aimed to develop statistical methods that facilitate…

As diagnostic classification models become more widely used in large-scale operational assessments, we must give consideration to the methods for estimating and reporting reliability. Researchers must explore alternatives to traditional reliability methods that are consistent with the design, scoring, and reporting levels of diagnostic assessment…

The aim of this study is to investigate the impact of different logistic regression estimators applied to RDS studies via simulation and the analysis of empirical data. Four simulated populations were created with different connectivity characteristics. Each simulated individual received two attributes, one of them associated to the infection…

Missing data complicates statistical analyses in multi-site studies, especially when it is not feasible to centrally pool individual-level data across sites. We combined meta-analysis with within-site multiple imputation for one-step estimation of the average causal effect (ACE) of a target population comprised of all individuals from all…