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Ke-Hai Yuan; Yongfei Fang – Grantee Submission, 2023
Observational data typically contain measurement errors. Covariance-based structural equation modelling (CB-SEM) is capable of modelling measurement errors and yields consistent parameter estimates. In contrast, methods of regression analysis using weighted composites as well as a partial least squares approach to SEM facilitate the prediction and…
Descriptors: Structural Equation Models, Regression (Statistics), Weighted Scores, Comparative Analysis
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Alshurideh, Muhammad; Al Kurdi, Barween; Salloum, Said A.; Arpaci, Ibrahim; Al-Emran, Mostafa – Interactive Learning Environments, 2023
Despite the plethora of m-learning acceptance studies, few have tackled the importance of examining the actual use of m-learning systems from the lenses of social influence, expectation-confirmation, and satisfaction. Additionally, most of the prior technology adoption literature tends to use the structural equation modeling (SEM) technique in…
Descriptors: Electronic Learning, Prediction, Least Squares Statistics, Structural Equation Models
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López-Bonilla, Luis Miguel; López-Bonilla, Jesús Manuel – British Journal of Educational Technology, 2017
The debate about the role of attitude in the technology acceptance model (TAM) seems to have re-emerged in two prestigious journals in the field of educational technology. Among the publications on this debate, there are authors in favour of excluding the attitude of TAM, whereas others are in favour of including it. These opinions are derived…
Descriptors: Computer Attitudes, Adoption (Ideas), Models, Educational Technology
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Ravand, Hamdollah; Baghaei, Purya – Practical Assessment, Research & Evaluation, 2016
Structural equation modeling (SEM) has become widespread in educational and psychological research. Its flexibility in addressing complex theoretical models and the proper treatment of measurement error has made it the model of choice for many researchers in the social sciences. Nevertheless, the model imposes some daunting assumptions and…
Descriptors: Least Squares Statistics, Structural Equation Models, Nonparametric Statistics, Sample Size
Zhang, Ying – ProQuest LLC, 2011
Meta-analytic Structural Equation Modeling (MASEM) has drawn interest from many researchers recently. In doing MASEM, researchers usually first synthesize correlation matrices across studies using meta-analysis techniques and then analyze the pooled correlation matrix using structural equation modeling techniques. Several multivariate methods of…
Descriptors: Structural Equation Models, Multivariate Analysis, Meta Analysis, Least Squares Statistics
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Huang, Rui-Ting – Educational Technology & Society, 2014
Although a considerable number of studies have revealed that self-management of learning (SML) could be closely related to learning achievements, there is still a paucity of research investigating the moderating effect of self-management of learning on mobile learning outcomes. Accordingly, the primary purpose of this study was to explore the…
Descriptors: Foreign Countries, Self Management, Academic Achievement, Electronic Learning
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Eom, Sean B. – Journal of International Education in Business, 2012
Purpose: The majority of e-learning empirical research studies have focused on the two research streams: outcome comparison studies with classroom-based learning and studies examining potential predictors of e-learning success. The determinants of e-learning success include interactions, instructor support and mentoring, information delivery…
Descriptors: Business Education, Self Efficacy, Electronic Learning, Course Content
Pai, Tanusree – ProQuest LLC, 2010
As the use of contracting for Information Technology (IT) services steadily increases, IT managers are challenged with reconciling the need for flexibility achieved through the use of contract workers, with the need to understand the factors that maximize the performance and behaviors of contract and permanent IT workers. While several research…
Descriptors: Information Technology, Outsourcing, Employees, Employer Employee Relationship
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Lu, Irene R. R.; Thomas, D. Roland; Zumbo, Bruno D. – Structural Equation Modeling: A Multidisciplinary Journal, 2005
This article reviews the problems associated with using item response theory (IRT)-based latent variable scores for analytical modeling, discusses the connection between IRT and structural equation modeling (SEM)-based latent regression modeling for discrete data, and compares regression parameter estimates obtained using predicted IRT scores and…
Descriptors: Least Squares Statistics, Item Response Theory, Structural Equation Models, Comparative Analysis
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Moulder, Bradley C.; Algina, James – Structural Equation Modeling, 2002
Used simulation to compare structural equation modeling methods for estimating and testing hypotheses about an interaction between continuous variables. Findings indicate that the two-stage least squares procedure exhibited more bias and lower power than the other methods. The Jaccard-Wan procedure (J. Jaccard and C. Wan, 1995) and maximum…
Descriptors: Comparative Analysis, Estimation (Mathematics), Hypothesis Testing, Least Squares Statistics