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Singh, Akansha; Uwimpuhwe, Germaine; Li, Mengchu; Einbeck, Jochen; Higgins, Steve; Kasim, Adetayo – International Journal of Research & Method in Education, 2022
In education, multisite trials involve randomization of pupils into intervention and comparison groups within schools. Most analytical models in multisite educational trials ignore that the impact of an intervention may be school dependent. This study investigates the impact of statistical models on the uncertainty associated with an effect size…
Descriptors: Randomized Controlled Trials, Effect Size, Hierarchical Linear Modeling, Least Squares Statistics
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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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Uanhoro, James O.; Wang, Yixi; O'Connell, Ann A. – Journal of Experimental Education, 2021
The standard regression technique for modeling binary response variables in education research is logistic regression. The odds ratios from these models are used to quantify and communicate variable effects. These effects are sometimes pooled together as in a meta-analysis. We argue that this process is problematic as odds ratios calculated from…
Descriptors: Probability, Effect Size, Regression (Statistics), Educational Research
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Carannante, Maria; Davino, Cristina; Vistocco, Domenico – Studies in Higher Education, 2021
Massive Open Online Courses, universally labelled as MOOCs, become more and more relevant in the era of digitalization of higher education. The availability of free education resources without access restrictions for a plenty of potential users has changed the learning market in a way unthinkable only few decades ago. This form of web-based…
Descriptors: Online Courses, Structural Equation Models, Least Squares Statistics, Measurement
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Kilty, Joel M.; McAllister, Alex M. – PRIMUS, 2020
In our modern world, we are inundated and grapple with data daily. As mathematicians, we are often more comfortable discussing the behavior of functions presented analytically, in contrast with the data-driven or tabular presentations of functions ubiquitous in our culture. This paper introduces an entry-level course, Mathematical Modeling and…
Descriptors: Calculus, Teaching Methods, Mathematics Instruction, College Mathematics
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Lin, Hung-Ming; Lee, Min-Hsien; Liang, Jyh-Chong; Chang, Hsin-Yi; Huang, Pinchi; Tsai, Chin-Chung – British Journal of Educational Technology, 2020
Partial least squares structural equation modeling (PLS-SEM) has become a key multivariate statistical modeling technique that educational researchers frequently use. This paper reviews the uses of PLS-SEM in 16 major e-learning journals, and provides guidelines for improving the use of PLS-SEM as well as recommendations for future applications in…
Descriptors: Least Squares Statistics, Structural Equation Models, Electronic Learning, Educational Research
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Taylor, John M. – Practical Assessment, Research & Evaluation, 2019
Although frequentist estimators can effectively fit ordinal confirmatory factor analysis (CFA) models, their assumptions are difficult to establish and estimation problems may prohibit their use at times. Consequently, researchers may want to also look to Bayesian analysis to fit their ordinal models. Bayesian methods offer researchers an…
Descriptors: Bayesian Statistics, Factor Analysis, Least Squares Statistics, Error of Measurement
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Huang, Chun-Hsiung – Education Sciences, 2021
This research explores the influencing factors of learning satisfaction in blended learning. Three dimensions are proposed: perceived usefulness, perceived ease of use, and learning motivation. It studied how these variables affect students' learning satisfaction. The research hypotheses are: (1) Perceived ease of use positively affects perceived…
Descriptors: Blended Learning, Student Satisfaction, Usability, Learning Motivation
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Davis, Richard A. – Chemical Engineering Education, 2020
A case study of regression analysis based on modeling Gilliland's correlation was described for use in a computational methods course. The case study uses a familiar example to train students in nonlinear least squares regression and to use standardized residual plots for model assessment. Previously published equations for Gilliland's correlation…
Descriptors: Case Studies, Regression (Statistics), Correlation, Least Squares Statistics
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Kane, Michael T.; Mroch, Andrew A. – ETS Research Report Series, 2020
Ordinary least squares (OLS) regression and orthogonal regression (OR) address different questions and make different assumptions about errors. The OLS regression of Y on X yields predictions of a dependent variable (Y) contingent on an independent variable (X) and minimizes the sum of squared errors of prediction. It assumes that the independent…
Descriptors: Regression (Statistics), Least Squares Statistics, Test Bias, Error of Measurement
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Schijns, Jos M. C. – Tertiary Education and Management, 2021
The aim of this study is to analyze, evaluate and validate the NSE (National Student Enquiry) as a service quality measure helping both higher education institutions (HEIs) and students in their decision making. Every year the Dutch foundation 'Studiekeuze123' sends out a survey (the NSE) to collect data on service quality regarding education at…
Descriptors: Virtual Universities, Educational Quality, Foreign Countries, Student Surveys
Moeyaert, Mariola; Akhmedjanova, Diana; Ferron, John; Beretvas, S. Natasha; Van den Noortgate, Wim – Grantee Submission, 2020
The methodology of single-case experimental designs (SCED) has been expanding its efforts toward rigorous design tactics to address a variety of research questions related to intervention effectiveness. Effect size indicators appropriate to quantify the magnitude and the direction of interventions have been recommended and intensively studied for…
Descriptors: Effect Size, Research Methodology, Research Design, Hierarchical Linear Modeling
Miocevic, Milica; Klaassen, Fayette; Geuke, Gemma; Moeyaert, Mariola; Maric, Marija – Grantee Submission, 2020
Single-Case Experimental Designs (SCEDs) have lately been recognized as a valuable alternative tolarge group studies. SCEDs form a great tool for the evaluation of treatment effectiveness in heterogeneous and low-incidence conditions, which are common in the field of communication disorders. Mediation analysis is indispensable in treatment…
Descriptors: Bayesian Statistics, Computation, Intervention, Case Studies
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Kirkup, Les; Frenkel, Bob – Physics Education, 2020
When the relationship between two physical variables, such as voltage and current, can be expressed as y = bx where b is a constant. b may be estimated by least squares, or by averaging the values of b obtained for each x-y data pair. We show for data gathered in an experiment, as well as through Monte Carlo simulation and mathematical analysis,…
Descriptors: Comparative Analysis, Least Squares Statistics, Monte Carlo Methods, Physics
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Liang, Xinya; Kamata, Akihito; Li, Ji – Educational and Psychological Measurement, 2020
One important issue in Bayesian estimation is the determination of an effective informative prior. In hierarchical Bayes models, the uncertainty of hyperparameters in a prior can be further modeled via their own priors, namely, hyper priors. This study introduces a framework to construct hyper priors for both the mean and the variance…
Descriptors: Bayesian Statistics, Randomized Controlled Trials, Effect Size, Sampling
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