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Jihong Zhang; Jonathan Templin; Xinya Liang – Journal of Educational Measurement, 2024
Recently, Bayesian diagnostic classification modeling has been becoming popular in health psychology, education, and sociology. Typically information criteria are used for model selection when researchers want to choose the best model among alternative models. In Bayesian estimation, posterior predictive checking is a flexible Bayesian model…
Descriptors: Bayesian Statistics, Cognitive Measurement, Models, Classification
Qi, Hongchao; Rizopoulos, Dimitris; Rosmalen, Joost – Research Synthesis Methods, 2022
The meta-analytic-predictive (MAP) approach is a Bayesian meta-analytic method to synthesize and incorporate information from historical controls in the analysis of a new trial. Classically, only a single parameter, typically the intercept or rate, is assumed to vary across studies, which may not be realistic in more complex models. Analysis of…
Descriptors: Meta Analysis, Prediction, Correlation, Bayesian Statistics
Xia, Xiaona – Interactive Learning Environments, 2023
The research of multi-category learning behaviors is a hot issue in interactive learning environment, and there are many challenges in data statistics and relationship modeling. We select the massive learning behaviors data of multiple periods and courses and study the decision application of regression analysis. First, based on the definition of…
Descriptors: Learning Analytics, Decision Making, Regression (Statistics), Bayesian Statistics
David Kaplan; Kjorte Harra – Large-scale Assessments in Education, 2024
This paper aims to showcase the value of implementing a Bayesian framework to analyze and report results from international large-scale assessments and provide guidance to users who want to analyse ILSA data using this approach. The motivation for this paper stems from the recognition that Bayesian statistical inference is fast becoming a popular…
Descriptors: Bayesian Statistics, Administrator Surveys, Teacher Surveys, Measurement
Hyemin Han; Kelsie J. Dawson – Journal of Moral Education, 2024
In the present study, we examined how the perceived attainability and relatability of moral exemplars predicted moral elevation and pleasantness among both adult and college student participants. Data collected from two experiments were analyzed with Bayesian multilevel modeling to explore which factors significantly predicted outcome variables at…
Descriptors: Moral Values, Prediction, Models, Behavior Patterns
Hao, Jia; Gan, Jianhou; Zhu, Luyu – Education and Information Technologies, 2022
In order to analyze the non-linear and uncertain relationships among the student-related features, curriculum-related features as well as the environment-related features, and then quantify the corresponding impacts on students' final MOOC performance in a valid way, we first construct a Students' performance Prediction Bayesian Network (SPBN) via…
Descriptors: Online Courses, Academic Achievement, Prediction, Student Improvement
Delianidi, Marina; Diamantaras, Konstantinos – Journal of Educational Data Mining, 2023
Student performance is affected by their knowledge which changes dynamically over time. Therefore, employing recurrent neural networks (RNN), which are known to be very good in dynamic time series prediction, can be a suitable approach for student performance prediction. We propose such a neural network architecture containing two modules: (i) a…
Descriptors: Academic Achievement, Prediction, Cognitive Measurement, Bayesian Statistics
XinXiu Yang – International Journal of Information and Communication Technology Education, 2024
The objective of this work is to predict the employment rate of students based on the information in the SSM (student status management) in colleges and universities. Firstly, the relevant content of SSM is introduced. Secondly, the BP (Back Propagation) neural network, the LM (Levenberg Marquardt) algorithm, and the BR (Bayesian Regularization)…
Descriptors: Prediction, Employment Patterns, College Students, Algorithms
Xie, Belinda; Hayes, Brett – Cognitive Science, 2022
According to Bayesian models of judgment, testimony from independent informants has more evidential value than dependent testimony. Three experiments investigated learners' sensitivity to this distinction. Each experiment used a social version of the balls-and-urns task, in which participants judged which of two urns was the most likely source of…
Descriptors: Evidence, Decision Making, Task Analysis, Beliefs
Mangino, Anthony A.; Finch, W. Holmes – Educational and Psychological Measurement, 2021
Oftentimes in many fields of the social and natural sciences, data are obtained within a nested structure (e.g., students within schools). To effectively analyze data with such a structure, multilevel models are frequently employed. The present study utilizes a Monte Carlo simulation to compare several novel multilevel classification algorithms…
Descriptors: Prediction, Hierarchical Linear Modeling, Classification, Bayesian Statistics
Jennifer L. Proper; Haitao Chu; Purvi Prajapati; Michael D. Sonksen; Thomas A. Murray – Research Synthesis Methods, 2024
Drug repurposing refers to the process of discovering new therapeutic uses for existing medicines. Compared to traditional drug discovery, drug repurposing is attractive for its speed, cost, and reduced risk of failure. However, existing approaches for drug repurposing involve complex, computationally-intensive analytical methods that are not…
Descriptors: Network Analysis, Meta Analysis, Prediction, Drug Therapy
Kjorte Harra; David Kaplan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The present work focuses on the performance of two types of shrinkage priors--the horseshoe prior and the recently developed regularized horseshoe prior--in the context of inducing sparsity in path analysis and growth curve models. Prior research has shown that these horseshoe priors induce sparsity by at least as much as the "gold…
Descriptors: Structural Equation Models, Bayesian Statistics, Regression (Statistics), Statistical Inference
Qi, Hongchao; Rizopoulos, Dimitris; Rosmalen, Joost – Research Synthesis Methods, 2023
The meta-analytic-predictive (MAP) approach is a Bayesian method to incorporate historical controls in new trials that aims to increase the statistical power and reduce the required sample size. Here we investigate how to calculate the sample size of the new trial when historical data is available, and the MAP approach is used in the analysis. In…
Descriptors: Sample Size, Computation, Meta Analysis, Bayesian Statistics
Joo, Seang-Hwane; Lee, Philseok – Journal of Educational Measurement, 2022
Abstract This study proposes a new Bayesian differential item functioning (DIF) detection method using posterior predictive model checking (PPMC). Item fit measures including infit, outfit, observed score distribution (OSD), and Q1 were considered as discrepancy statistics for the PPMC DIF methods. The performance of the PPMC DIF method was…
Descriptors: Test Items, Bayesian Statistics, Monte Carlo Methods, Prediction
Dalia Khairy; Nouf Alharbi; Mohamed A. Amasha; Marwa F. Areed; Salem Alkhalaf; Rania A. Abougalala – Education and Information Technologies, 2024
Student outcomes are of great importance in higher education institutions. Accreditation bodies focus on them as an indicator to measure the performance and effectiveness of the institution. Forecasting students' academic performance is crucial for every educational establishment seeking to enhance performance and perseverance of its students and…
Descriptors: Prediction, Tests, Scores, Information Retrieval