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What is Structural Equation Modelling

Transforming Curriculum Through Teacher-Learner Partnerships
Structural equation modeling is a multivariate analytical approach used to simultaneously test and estimate complex causal relationships among variables.
Published in Chapter:
Integrating Service Learning Into Higher Education Curriculum: Developing Business Undergraduates' Competencies
Vinitha Guptan (Saito University College, Malaysia), Ratneswary Rasiah (Taylor's University, Malaysia), and Jason James Turner (Asia Pacific University of Technology and Innovation, Malaysia)
Copyright: © 2021 |Pages: 21
DOI: 10.4018/978-1-7998-6445-5.ch007
Abstract
This study aims to assess the effectiveness of integrating service learning into the business curriculum of a higher education provider to enhance learners' competencies and reflective learning. Founded on the educational theories of constructivism and social learning, this research consolidates and takes research forward in the understanding of how transforming the business curriculum by integrating service learning through teacher-learner partnerships enhances a students' ability for reflective learning. Using a self-administered questionnaire-based survey with 256 respondents, the data were analysed using variance based PLS-SEM to reveal that service learning had a significant positive influence on reflective learning and on student competency development. The results indicate the positive impact that team-based service learning through teacher-learner partnerships had on the learners' experience. These findings offer some interesting insight for educators, researchers, and policy makers as a means to enhance the learning experience of students in tertiary education in Malaysia.
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More Results
Interpretive Structural Modeling: Background, Concepts, and Application
It is a multivariate statistical analysis technique that is used to analyze structural relationships. This technique is the combination of factor analysis and multiple regression analysis, and it is used to analyze the structural relationship between measured variables and latent constructs.
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Explaining Consumer Behavior in the Hospitality Industry: CSR Associations and Corporate Image
It is a statistical technique for testing and estimating causal relations using a combination of statistical data and qualitative causal assumptions.
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The Mediating Role of E-Consumer Informedness Between Digital Usability and Responsible E-Shopping: Post-COVID-19 Period
It`s a statistical technique used to analyse the relationships between latent variables (non-observable constructs) and observable variables in a theoretical model.
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Artificial Intelligence Effectiveness in Customer Experience at Retail
Multivariate method that allows testing hypotheses regarding the influences among interacting variables.
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