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Servet Demir; Muhammet Usak – SAGE Open, 2025
This systematic review examines the application of Partial Least Squares Structural Equation Modeling (PLS-SEM) in educational technology research from 2013 to 2023. Following PRISMA guidelines, 57 studies were selected from Scopus and Web of Science databases. The review process involved rigorous screening, data extraction, and analysis using…
Descriptors: Educational Technology, Educational Research, Structural Equation Models, Least Squares Statistics
W. Holmes Finch – Educational and Psychological Measurement, 2024
Dominance analysis (DA) is a very useful tool for ordering independent variables in a regression model based on their relative importance in explaining variance in the dependent variable. This approach, which was originally described by Budescu, has recently been extended to use with structural equation models examining relationships among latent…
Descriptors: Models, Regression (Statistics), Structural Equation Models, Predictor Variables
Teague R. Henry; Zachary F. Fisher; Kenneth A. Bollen – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Model-Implied Instrumental Variable Two-Stage Least Squares (MIIV-2SLS) is a limited information, equation-by-equation, noniterative estimator for latent variable models. Associated with this estimator are equation-specific tests of model misspecification. One issue with equation-specific tests is that they lack specificity, in that they indicate…
Descriptors: Bayesian Statistics, Least Squares Statistics, Structural Equation Models, Equations (Mathematics)
Gyeongcheol Cho; Heungsun Hwang – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Generalized structured component analysis (GSCA) is a multivariate method for specifying and examining interrelationships between observed variables and components. Despite its data-analytic flexibility honed over the decade, GSCA always defines every component as a linear function of observed variables, which can be less optimal when observed…
Descriptors: Prediction, Methods, Networks, Simulation
Muhammad Farrukh Shahzad; Shuo Xu; Xin An; Muhammad Asif; Iqra Javed – Education and Information Technologies, 2025
Based on the self-determination theory (SDT), this evaluates the effects of generative artificial intelligence (Gen-AI) on learning performance within China's education sector, emphasizing the roles of social interaction, utilitarian benefit, knowledge acquisition, and epistemic curiosity. The study employs a dual method, using PLS-SEM and fsQCA…
Descriptors: Artificial Intelligence, Educational Benefits, Barriers, Learning Processes
Ram B. Basnet; David J. Lemay; Paul Bazelais – Knowledge Management & E-Learning, 2024
Academic and practitioner interest in data science has increased considerably. Yet scholarly understanding of what motivates students to learn data science is still limited. Drawing on the theory of planned behavior, we propose a research model to examine the determinants of behavioral intentions to learn data science. In the proposed research…
Descriptors: Student Attitudes, Intention, Data Science, Statistics Education
Ke-Hai Yuan; Zhiyong Zhang – Grantee Submission, 2022
Structural equation modeling (SEM) is a widely used technique for studies involving latent constructs. While covariance-based SEM (CB-SEM) permits estimating the regression relationship among latent constructs, the parameters governing this relationship do not apply to that among the scored values of the constructs, which are needed for…
Descriptors: Psychometrics, Structural Equation Models, Scores, Least Squares Statistics
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
Rajesh Kumar Sharma; Sukhpreet Kaur – International Journal of Educational Management, 2024
Purpose: The purpose of this paper is to analyse the mediating role of organisational citizenship behaviour between transformational leadership and successful implementation of education 4.0 in higher educational institutes using the PLS-SEM approach. Design/methodology/approach: The study uses cross-sectional and quantitative approach to decode…
Descriptors: Transformational Leadership, Organizational Climate, Citizenship, Higher Education
Aykut Durak; Vahide Bulut – Technology, Knowledge and Learning, 2025
The study uses the partial least squares-structural equation modeling (PLS-SEM) algorithm to predict the factors affecting the programming performance (PPE) (low, high) of the students receiving computer programming education. The participants of the study consist of 763 students who received programming education. In the analysis of the data, the…
Descriptors: Prediction, Low Achievement, High Achievement, Academic Achievement
Jalal, Azlin Abd; Hamid, Harris Shah Abd; Zulnaidi, Hutkemri – Malaysian Online Journal of Educational Sciences, 2023
In this new era drenched with data, statistical literacy becomes more essential for individuals to be able to read, communicate, and make informed decisions. Moreover, statistical literacy is highly essential for education policy makers who are highly accountable for all policy outcomes including school improvement, resource allocation, curriculum…
Descriptors: Statistics, Literacy, Educational Policy, Mathematics Anxiety
Analyzing Predictors of Perceived Graduate Employability from Sufficiency and Necessity Perspectives
Yin Ma; Dawn Bennett – Higher Education: The International Journal of Higher Education Research, 2024
This study aims to understand the sufficient, necessary, and critical factors of students' perceived employability (PE). It employs an innovative combination of Partial Least Squares Structural Equation Modeling (PLS-SEM), Necessary Condition Analysis (NCA), and Importance-Performance Matrix Analysis (IPMA). PE is conceptualized as five…
Descriptors: Predictor Variables, College Graduates, Employment Potential, Human Capital
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
Kang Wang; Yu-Yuan Qu; Siew-Ping Wong – Education and Information Technologies, 2025
This research delves into the factors that shape Chinese college students' engagement with Generative AI (GenAI) for career exploration purposes, employing the lenses of the Comprehensive Model of Information Seeking (CMIS) and the Technology Acceptance Model (TAM). Utilizing a mixed-methods design, which integrates partial least squares…
Descriptors: College Students, Artificial Intelligence, Technology Uses in Education, Career Development
Abdul Raof, Shuhada; Musta'amal, Aede Hatib – European Journal of Educational Research, 2022
Competent instructors need to have the skills, abilities, and competencies to perform tasks effectively, which will affect student learning achievement. This study is guided by the theory of Boyatzis developed by Spencer and Spencer. The Iceberg Competency Model was used as a guideline to identify the competency elements of educators from the…
Descriptors: Agricultural Education, Vocational Education, Agriculture Teachers, Teacher Competencies

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