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Steffen Nestler; Sarah Humberg – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Several variants of the autoregressive structural equation model were suggested over the past years, including, for example, the random intercept autoregressive panel model, the latent curve model with structured residuals, and the STARTS model. The present work shows how to place these models into a mixed-effects model framework and how to…
Descriptors: Structural Equation Models, Computer Software, Models, Measurement
Kelvin T. Afolabi; Timothy R. Konold – Practical Assessment, Research & Evaluation, 2024
Exploratory structural equation (ESEM) has received increased attention in the methodological literature as a promising tool for evaluating latent variable measurement models. It overcomes many of the limitations attached to exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), while capitalizing on the benefits of each. Given…
Descriptors: Measurement Techniques, Factor Analysis, Structural Equation Models, Comparative Analysis
Liang Kong – International Journal of Mathematical Education in Science and Technology, 2024
The COVID-19 pandemic, like past historical events such as the Vietnam War or 9/11, will shape a generation. Mathematics educators can seize this unprecedented opportunity to teach the principles of mathematical modeling in epidemiology. Compartmental epidemiological models, such as the SIR (susceptible-infected-recovered), are widely used by…
Descriptors: Mathematics Instruction, Teaching Methods, Advanced Courses, Epidemiology
Yiting Wang; Tong Li; Jiahui You; Xinran Zhang; Congkai Geng; Yu Liu – ACM Transactions on Computing Education, 2025
Understanding software modelers' difficulties and evaluating their performance is crucial to Model-Driven Engineering (MDE) education. The software modeling process contains fine-grained information about the modelers' analysis and thought processes. However, existing research primarily focuses on identifying obvious issues in the software…
Descriptors: Computer Software, Engineering Education, Models, Identification
Daniel Seddig – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The latent growth model (LGM) is a popular tool in the social and behavioral sciences to study development processes of continuous and discrete outcome variables. A special case are frequency measurements of behaviors or events, such as doctor visits per month or crimes committed per year. Probability distributions for such outcomes include the…
Descriptors: Growth Models, Statistical Analysis, Structural Equation Models, Crime
Xu Qin – Asia Pacific Education Review, 2024
Causal mediation analysis has gained increasing attention in recent years. This article guides empirical researchers through the concepts and challenges of causal mediation analysis. I first clarify the difference between traditional and causal mediation analysis and highlight the importance of adjusting for the treatment-by-mediator interaction…
Descriptors: Causal Models, Mediation Theory, Statistical Analysis, Computer Software
Heungsun Hwang; Gyeongcheol Cho; Hosung Choo – Structural Equation Modeling: A Multidisciplinary Journal, 2024
GSCA Pro is free, user-friendly software for generalized structured component analysis structural equation modeling (GSCA-SEM), which implements three statistical methods for estimating models with factors only, models with components only, and models with both factors and components. This tutorial aims to provide step-by-step illustrations of how…
Descriptors: Research Tools, Structural Equation Models, Computer Software, Research Methodology
Pasty Asamoah; John Serbe Marfo; Matilda Kokui Owusu-Bio; Daniel Zokpe – Education and Information Technologies, 2024
In this brief we shift the current academic integrity conversation from "detecting and preventing plagiarism" to "examining how plagiarized contents can be corrected with an objective knowledge of the number of words to modify and properly acknowledged". We proposed a simple, yet useful and powerful mathematical model that is…
Descriptors: Error Correction, Plagiarism, Integrity, Prevention
Sarah Narvaiz; Qinyun Lin; Joshua M. Rosenberg; Kenneth A. Frank; Spiro J. Maroulis; Wei Wang; Ran Xu – Grantee Submission, 2024
Sensitivity analysis, a statistical method crucial for validating inferences across disciplines, quantifies the conditions that could alter conclusions (Razavi et al., 2021). One line of work is rooted in linear models and foregrounds the sensitivity of inferences to the strength of omitted variables (Cinelli & Hazlett, 2019; Frank, 2000). A…
Descriptors: Statistical Analysis, Computer Software, Robustness (Statistics), Statistical Inference
Tenko Raykov; Lisa Calvocoressi; Randall E. Schumacker – Measurement: Interdisciplinary Research and Perspectives, 2024
This paper is concerned with the process of selecting between the increasingly popular bi-factor model and the second-order factor model in measurement research. It is indicated that in certain settings widely used in empirical studies, the second-order model is nested in the bi-factor model and obtained from the latter after imposing appropriate…
Descriptors: Factor Analysis, Decision Making, Computer Software, Measurement Techniques
Paul Meara; Imma Miralpeix – Vocabulary Learning and Instruction, 2024
This paper is part 4 in a series of workshops that examine the properties of some simple models of vocabulary networks. This Workshop explores how the overall activity level of a vocabulary network can be altered by changing the connections in the network (i.e., by implementing relinking events). The Workshop is linked to an online practice room…
Descriptors: Vocabulary Development, Models, Simulation, Workshops
Selcuk Acar; Peter Organisciak; Denis Dumas – Journal of Creative Behavior, 2025
In this three-study investigation, we applied various approaches to score drawings created in response to both Form A and Form B of the Torrance Tests of Creative Thinking-Figural (broadly TTCT-F) as well as the Multi-Trial Creative Ideation task (MTCI). We focused on TTCT-F in Study 1, and utilizing a random forest classifier, we achieved 79% and…
Descriptors: Scoring, Computer Assisted Testing, Models, Correlation
Austin M. Shin; Ayaan M. Kazerouni – ACM Transactions on Computing Education, 2024
Background and Context: Students' programming projects are often assessed on the basis of their tests as well as their implementations, most commonly using test adequacy criteria like branch coverage, or, in some cases, mutation analysis. As a result, students are implicitly encouraged to use these tools during their development process (i.e., so…
Descriptors: Feedback (Response), Programming, Student Projects, Computer Software
Lennert J. Groot; Kees-Jan Kan; Suzanne Jak – Research Synthesis Methods, 2024
Researchers may have at their disposal the raw data of the studies they wish to meta-analyze. The goal of this study is to identify, illustrate, and compare a range of possible analysis options for researchers to whom raw data are available, wanting to fit a structural equation model (SEM) to these data. This study illustrates techniques that…
Descriptors: Meta Analysis, Structural Equation Models, Research Methodology, Data Analysis
Kurt VanLehn; Fabio Milner; Chandrani Banerjee; Jon Wetzel – International Journal of Artificial Intelligence in Education, 2024
An algebraic model uses a set of algebraic equations to describe a situation. Constructing such models is a fundamental skill, but many students still lack the skill, even after taking several algebra courses in high school and college. For such students, we developed instruction that taught students to decompose the to-be-modelled situation into…
Descriptors: Algebra, Mathematical Models, Low Achievement, Mathematics Instruction