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Viechtbauer, Wolfgang; López-López, José Antonio – Research Synthesis Methods, 2022
Heterogeneity is commonplace in meta-analysis. When heterogeneity is found, researchers often aim to identify predictors that account for at least part of such heterogeneity by using mixed-effects meta-regression models. Another potentially relevant goal is to focus on the amount of heterogeneity as a function of one or more predictors, but this…
Descriptors: Meta Analysis, Models, Predictor Variables, Computation
Kenneth Tyler Wilcox; Ross Jacobucci; Zhiyong Zhang; Brooke A. Ammerman – Grantee Submission, 2023
Text is a burgeoning data source for psychological researchers, but little methodological research has focused on adapting popular modeling approaches for text to the context of psychological research. One popular measurement model for text, topic modeling, uses a latent mixture model to represent topics underlying a body of documents. Recently,…
Descriptors: Bayesian Statistics, Content Analysis, Undergraduate Students, Self Destructive Behavior
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Thomas Mgonja; Francisco Robles – Journal of College Student Retention: Research, Theory & Practice, 2024
Completion of remedial mathematics has been identified as one of the keys to college success. However, completion rates in remedial mathematics have been low and are of much debate across America. This study leverages machine learning techniques in trying to predict and understand completion rates in remedial mathematics. The purpose of this study…
Descriptors: Predictor Variables, Remedial Mathematics, Mathematics Achievement, Graduation Rate
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Krenzke, Tom; Mohadjer, Leyla; Li, Jianzhu; Erciulescu, Andreea; Fay, Robert; Ren, Weijia; Van de Kerckhove, Wendy; Li, Lin; Rao, J. N. K. – National Center for Education Statistics, 2020
The Program for the International Assessment of Adult Competencies (PIAAC) is a multicycle survey of adult skills and competencies sponsored by the Organization for Economic Cooperation and Development (OECD). The survey examines a range of basic skills in the information age and assesses these adult skills consistently across participating…
Descriptors: Adults, Surveys, Statistical Analysis, Computation
Dakota W. Cintron – ProQuest LLC, 2020
Observable data in empirical social and behavioral science studies are often categorical (i.e., binary, ordinal, or nominal). When categorical data are outcomes, they fail to maintain the scale and distributional properties of linear regression and factor analysis. Attempting to estimate model parameters for categorical outcome data with the…
Descriptors: Factor Analysis, Computation, Statistics, Methods
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Krenzke, Tom; Mohadjer, Leyla; Li, Jianzhu; Erciulescu, Andreea; Fay, Robert; Ren, Weijia; Van de Kerckhove, Wendy; Li, Lin; Rao, J. N. K. – National Center for Education Statistics, 2020
The Program for the International Assessment of Adult Competencies (PIAAC) is a multicycle survey of adult skills and competencies sponsored by the Organization for Economic Cooperation and Development (OECD). The survey examines a range of basic skills in the information age and assesses these adult skills consistently across participating…
Descriptors: Adults, International Assessment, Adult Literacy, Competence
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Desoete, Annemie; Baten, Elke – International Electronic Journal of Elementary Education, 2022
Several factors seem important to understand the nature of mathematical learning. Byrnes and Miller combined these factors into the Opportunity-Propensity model. In this study the model was used to predict the number-processing factor and the arithmetic fluency in grade 4 (n = 195) and grade 5 (n = 213). Gender, intelligence and affect (positive…
Descriptors: Mathematics Education, Elementary School Mathematics, Elementary School Students, Grade 4
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Min, Wookhee; Frankosky, Megan H.; Mott, Bradford W.; Rowe, Jonathan P.; Smith, Andy; Wiebe, Eric; Boyer, Kristy Elizabeth; Lester, James C. – IEEE Transactions on Learning Technologies, 2020
A distinctive feature of game-based learning environments is their capacity for enabling stealth assessment. Stealth assessment analyzes a stream of fine-grained student interaction data from a game-based learning environment to dynamically draw inferences about students' competencies through evidence-centered design. In evidence-centered design,…
Descriptors: Game Based Learning, Student Evaluation, Artificial Intelligence, Models
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Danial Hooshyar; Nour El Mawas; Yeongwook Yang – Knowledge Management & E-Learning, 2024
The use of learner modelling approaches is critical for providing adaptive support in educational computer games, with predictive learner modelling being among the key approaches. While adaptive supports have been shown to improve the effectiveness of educational games, improperly customized support can have negative effects on learning outcomes.…
Descriptors: Artificial Intelligence, Course Content, Tests, Scores
Moeyaert, Mariola – Behavioral Disorders, 2019
Multilevel meta-analysis is an innovative synthesis technique used for the quantitative integration of effect size estimates across participants and across studies. The quantitative summary allows for objective, evidence-based, and informed decisions in research, practice, and policy. Based on previous methodological work, the technique results in…
Descriptors: Meta Analysis, Evidence, Correlation, Predictor Variables
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Goldin, Ilya; Galyardt, April – Journal of Educational Data Mining, 2018
Data from student learning provide learning curves that, ideally, demonstrate improvement in student performance over time. Existing data mining methods can leverage these data to characterize and improve the domain models that support a learning environment, and these methods have been validated both with already-collected data, and in…
Descriptors: Predictor Variables, Models, Learning Processes, Matrices
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Finch, W. Holmes; Finch, Maria E. Hernandez – Practical Assessment, Research & Evaluation, 2016
Researchers and data analysts are sometimes faced with the problem of very small samples, where the number of variables approaches or exceeds the overall sample size; i.e. high dimensional data. In such cases, standard statistical models such as regression or analysis of variance cannot be used, either because the resulting parameter estimates…
Descriptors: Sample Size, Statistical Analysis, Regression (Statistics), Predictor Variables
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Neeliah, Harris; Seetanah, Boopen – European Journal of Training and Development, 2016
Purpose: Real gross domestic product (GDP) growth for Mauritius has averaged more than 5 per cent since 1970 and GDP per capita has increased more than tenfold between 1970 and 2012, from less than $500 to more than $9,000. It has often been reported that human capital, along with other growth enablers, has played an important role in this…
Descriptors: Human Capital, Economic Development, Economic Impact, Predictor Variables
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Schoeneberger, Jason A. – Journal of Experimental Education, 2016
The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…
Descriptors: Sample Size, Models, Computation, Predictor Variables
Ostrow, Korinn; Donnelly, Chistopher; Heffernan, Neil – International Educational Data Mining Society, 2015
As adaptive tutoring systems grow increasingly popular for the completion of classwork and homework, it is crucial to assess the manner in which students are scored within these platforms. The majority of systems, including ASSISTments, return the binary correctness of a student's first attempt at solving each problem. Yet for many teachers,…
Descriptors: Intelligent Tutoring Systems, Scoring, Testing, Credits
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