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Ting-Ting Wu; Edi Sarwono; Yueh-Min Huang – Journal of Computer Assisted Learning, 2025
Background: Virtual laboratories are used to supplement or even replace physical laboratories in engineering education. Although these virtual laboratories allow students to learn foundational experimental skills, they do not provide the learners with the chance to develop higher-order thinking skills (HOTS). Computational thinking (CT) is an…
Descriptors: Computation, Thinking Skills, Computer Simulation, Laboratories
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Ye Ma; Deborah J. Harris – Educational Measurement: Issues and Practice, 2025
Item position effect (IPE) refers to situations where an item performs differently when it is administered in different positions on a test. The majority of previous research studies have focused on investigating IPE under linear testing. There is a lack of IPE research under adaptive testing. In addition, the existence of IPE might violate Item…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Response Theory, Test Items
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Mei-Shiu Chiu; Meihua Zhu – Education and Information Technologies, 2025
Virtual reality (VR) has gained prominence and a growing prevalence. However, parental attitudes toward using VR for educational purposes (i.e., educational VR (EVR)) are under-researched. This study investigates parents' perceptions and experiences regarding the use of EVR, focussing on mathematics learning. Using the technology acceptance model…
Descriptors: Computer Simulation, Educational Technology, Technology Uses in Education, Parent Attitudes
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Jean-Paul Fox – Journal of Educational and Behavioral Statistics, 2025
Popular item response theory (IRT) models are considered complex, mainly due to the inclusion of a random factor variable (latent variable). The random factor variable represents the incidental parameter problem since the number of parameters increases when including data of new persons. Therefore, IRT models require a specific estimation method…
Descriptors: Sample Size, Item Response Theory, Accuracy, Bayesian Statistics
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Austin C. Kozlowski; James Evans – Sociological Methods & Research, 2025
Large language models (LLMs), through their exposure to massive collections of online text, learn to reproduce the perspectives and linguistic styles of diverse social and cultural groups. This capability suggests a powerful social scientific application--the simulation of empirically realistic, culturally situated human subjects. Synthesizing…
Descriptors: Artificial Intelligence, Social Science Research, Computer Simulation, Research Methodology
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Signy Wegener; Anne Castles; Elisabeth Beyersmann; Kate Nation; Hua-Chen Wang; Erik D. Reichle – Reading Research Quarterly, 2025
Spreading out study opportunities over time improves the retention of verbal material compared to consecutive study, yet little is known about the influence of temporal spacing on orthographic learning specifically. The current study addressed four questions: (1) do readers' eye movements during orthographic learning differ under spaced and massed…
Descriptors: Eye Movements, Simulation, Intervals, Orthographic Symbols
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Maria F. Larrea; Steven Hodge; Timothy J. Mavin – Journal of Vocational Education and Training, 2025
This paper provides a sociocultural understanding of how airline cabin crew negotiate their learning for emergencies and challenges the conventional approach of relying solely on formal training. Drawing on ethnographic methods, our research offers insights into the learning trajectory of the cabin crew of a regional airline operating in the…
Descriptors: Air Transportation, Employees, Emergency Programs, Workplace Learning
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Thanapat Sripan; Pattarawat Jeerapattanatorn – Contemporary Educational Technology, 2025
Based on an analysis of 36 peer-reviewed publications from academic databases, including ERIC, Scopus, Web of Science, and Google Scholar, this review article provides an in-depth examination of the current trends, challenges, and future implications of metaverse-based learning in education. To ascertain the quality and applicability of the papers…
Descriptors: Computer Uses in Education, Educational Trends, Computer Simulation, Barriers
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Honora Quinn Burnett; Sandra Cherabie; Shelley Jackson Worstell; Karen Espinoza; Karen Sosa-Sanchez; Sonja O'Leary – Journal of School Health, 2025
Background: School-Based Health Centers (SBHCs) have the capacity to overcome youth barriers to care. However, most schools do not have on-campus SBHCs. At Denver Health, a large safety net hospital with 19 SBHCs in Denver Public Schools, we developed a SBHC virtual care program (VCP) to link school nurses with SBHC providers to provide medical…
Descriptors: Educational Development, School Health Services, Clinics, Computer Simulation
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Amanda J. Haskins; Jeff Mentch; Caitlin Van Wicklin; Yeo Bi Choi; Caroline E. Robertson – Journal of Autism and Developmental Disorders, 2024
Sensory differences are nearly universal in autism, but their genetic origins are poorly understood. Here, we tested how individuals with an autism-linked genotype, 16p.11.2 deletion ("16p"), attend to visual information in immersive, real-world photospheres. We monitored participants' (N = 44) gaze while they actively explored 360°…
Descriptors: Autism Spectrum Disorders, Computer Simulation, Sensory Experience, Genetic Disorders
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Hans-Peter Piepho; Johannes Forkman; Waqas Ahmed Malik – Research Synthesis Methods, 2024
Checking for possible inconsistency between direct and indirect evidence is an important task in network meta-analysis. Recently, an evidence-splitting (ES) model has been proposed, that allows separating direct and indirect evidence in a network and hence assessing inconsistency. A salient feature of this model is that the variance for…
Descriptors: Maximum Likelihood Statistics, Evidence, Networks, Meta Analysis
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Brinley N. Zabriskie; Nolan Cole; Jacob Baldauf; Craig Decker – Research Synthesis Methods, 2024
Meta-analyses have become the gold standard for synthesizing evidence from multiple clinical trials, and they are especially useful when outcomes are rare or adverse since individual trials often lack sufficient power to detect a treatment effect. However, when zero events are observed in one or both treatment arms in a trial, commonly used…
Descriptors: Meta Analysis, Error Correction, Computation, Simulation
Philip C. Duczyminski – ProQuest LLC, 2024
Firefighters face many high-risk situations, from battling fires to managing hazardous materials and medical emergencies. The inherent dangers of these scenarios are reflected in the statistics from the U.S. Fire Administration, which reported 141 on-duty firefighter fatalities in 2021. Recognizing the critical need for enhanced safety, the…
Descriptors: Fire Protection, Job Training, Simulation, Instructional Effectiveness
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Guido Schwarzer; Gerta Rücker; Cristina Semaca – Research Synthesis Methods, 2024
The "LFK" index has been promoted as an improved method to detect bias in meta-analysis. Putatively, its performance does not depend on the number of studies in the meta-analysis. We conducted a simulation study, comparing the "LFK" index test to three standard tests for funnel plot asymmetry in settings with smaller or larger…
Descriptors: Bias, Meta Analysis, Simulation, Evaluation Methods
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Zheng Zhong; Sijia Feng; Shuaizhen Jin – Education and Information Technologies, 2024
This study examines the impact of various factors on teachers' anxiety toward teaching in Virtual Reality (VR) environments. Specifically, the research proposes a hypothetical model and investigates the influence of technical proficiency, self-efficacy, and school support on VR teaching anxiety. A total of 329 teachers with prior experience in VR…
Descriptors: Influences, Anxiety, Computer Simulation, Educational Technology
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