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Shengyu Jiang; Jiaying Xiao; Chun Wang – Grantee Submission, 2022
An online learning system has the capacity to offer customized content that caters to individual learner's need and has seen growing interest from industry and academia alike in recent years. Different from traditional computerized adaptive testing setting which has a well-calibrated item bank with new items periodically added, online learning…
Descriptors: Item Response Theory, Item Banks, Bayesian Statistics, Learning Management Systems
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Haiyan Liu; Sarah Depaoli; Lydia Marvin – Structural Equation Modeling: A Multidisciplinary Journal, 2022
The deviance information criterion (DIC) is widely used to select the parsimonious, well-fitting model. We examined how priors impact model complexity (pD) and the DIC for Bayesian CFA. Study 1 compared the empirical distributions of pD and DIC under multivariate (i.e., inverse Wishart) and separation strategy (SS) priors. The former treats the…
Descriptors: Structural Equation Models, Bayesian Statistics, Goodness of Fit, Factor Analysis
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Erik-Jan van Kesteren; Daniel L. Oberski – Structural Equation Modeling: A Multidisciplinary Journal, 2022
Structural equation modeling (SEM) is being applied to ever more complex data types and questions, often requiring extensions such as regularization or novel fitting functions. To extend SEM, researchers currently need to completely reformulate SEM and its optimization algorithm -- a challenging and time-consuming task. In this paper, we introduce…
Descriptors: Structural Equation Models, Computation, Graphs, Algorithms
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Ning, Ling; Luo, Wen – Journal of Experimental Education, 2018
Piecewise GMM with unknown turning points is a new procedure to investigate heterogeneous subpopulations' growth trajectories consisting of distinct developmental phases. Unlike the conventional PGMM, which relies on theory or experiment design to specify turning points a priori, the new procedure allows for an optimal location of turning points…
Descriptors: Statistical Analysis, Models, Classification, Comparative Analysis
Zhang, Zhiyong; Jiang, Kaifeng; Liu, Haiyan; Oh, In-Sue – Grantee Submission, 2018
To answer the call of introducing more Bayesian techniques to organizational research (e.g., Kruschke, Aguinis, & Joo, 2012; Zyphur & Oswald, 2013), we propose a Bayesian approach for meta-analysis with power prior in this article. The primary purpose of this method is to allow meta-analytic researchers to control the contribution of each…
Descriptors: Bayesian Statistics, Meta Analysis, Correlation, Statistical Analysis
Makela, Susanna; Si, Yajuan; Gelman, Andrew – Grantee Submission, 2018
Cluster sampling is common in survey practice, and the corresponding inference has been predominantly design-based. We develop a Bayesian framework for cluster sampling and account for the design effect in the outcome modeling. We consider a two-stage cluster sampling design where the clusters are first selected with probability proportional to…
Descriptors: Bayesian Statistics, Statistical Inference, Sampling, Probability
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Opic, Siniša – Cypriot Journal of Educational Sciences, 2020
Regression is one of the dominant analysis methods used in the social sciences and educational sciences. There are different regression methods based on the type of research that is being conducted. The probit and logit regression models are regression methods which are being used recently by most researchers. However, their interpretations are…
Descriptors: Regression (Statistics), Statistical Analysis, Differences, Educational Research
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Thompson, W. Burt; Garry, Amanda; Taylor, John; Radell, Milen L. – Psychology Learning and Teaching, 2020
When people interpret the outcome of a research study, do they consider other relevant information such as prior research? In the current study, 251 college graduates read a single brief fictitious news article. The article summarized the findings of a study that found positive results for a new drug. Three versions of the article varied the…
Descriptors: College Graduates, Statistics, Misconceptions, Probability
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Ghasemy, Majid; Teeroovengadum, Viraiyan; Becker, Jan-Michael; Ringle, Christian M. – Higher Education: The International Journal of Higher Education Research, 2020
The relevance and prominence of the partial least squares structural equation modeling (PLS-SEM) method has recently increased in higher education research, especially in explanatory and predictive studies. We therefore first aim to assess previous PLS-SEM applications by providing a systematic review; second, we aim to highlight and summarize…
Descriptors: Least Squares Statistics, Structural Equation Models, Higher Education, Educational Research
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Dunn, Peter K.; Marshman, Margaret – Australian Mathematics Education Journal, 2020
This article is the first in a series about teaching statistics. The authors discuss the role of statistics and the difference between mathematics and statistics.
Descriptors: Mathematics Education, Mathematics Instruction, Statistics, Definitions
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van Doorn, Johnny; Matzke, Dora; Wagenmakers, Eric-Jan – Psychology Learning and Teaching, 2020
Sir Ronald Fisher's venerable experiment "The Lady Tasting Tea" is revisited from a Bayesian perspective. We demonstrate how a similar tasting experiment, conducted in a classroom setting, can familiarize students with several key concepts of Bayesian inference, such as the prior distribution, the posterior distribution, the Bayes…
Descriptors: Bayesian Statistics, Statistical Inference, Statistical Distributions, Sequential Approach
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Doleck, Tenzin; Lemay, David John; Basnet, Ram B.; Bazelais, Paul – Education and Information Technologies, 2020
Large swaths of data are readily available in various fields, and education is no exception. In tandem, the impetus to derive meaningful insights from data gains urgency. Recent advances in deep learning, particularly in the area of voice and image recognition and so-called complete knowledge games like chess, go, and StarCraft, have resulted in a…
Descriptors: Learning Analytics, Prediction, Information Retrieval, Accuracy
Ajao, Adeola; Fitzallen, Noleine; Chick, Helen; Oates, Greg – Mathematics Education Research Group of Australasia, 2023
In this paper, the SOLO taxonomy is used to identify different levels of student understanding of the statistical concepts associated with sampling distribution. This study was part of a research project investigating students' conceptual understanding of concepts of hypothesis testing taught with the support of simulation learning activities. The…
Descriptors: Taxonomy, Statistics Education, Learning Activities, Simulation
Western Interstate Commission for Higher Education, 2023
This report outlines key data elements related to the Western Undergraduate Exchange (WUE), Western Regional Graduate Program (WRGP), and Professional Student Exchange Program (PSEP) for the 2022-23 academic year and is a core resource for policymakers, institutional leaders, counselors and other stakeholders across the region. This report…
Descriptors: Access to Education, Graduate Study, Data, Undergraduate Study
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Sisso, Danielle; Bass, Nicole; Williams, Immanuel – Teaching Statistics: An International Journal for Teachers, 2023
This paper provides introductory statistics instructors with the capacity to use engaging National Basketball Association (NBA) data within a web application to either strengthen students' understanding or introduce the concept of variance and one-way analysis of variance. Using engaging data within the classroom provides context to data that…
Descriptors: Statistics Education, Teaching Methods, Statistical Analysis, Introductory Courses
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