Application Of Structural Equation Modeling In Educational Research And Practice
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Application of Structural Equation Modeling in Educational Research and Practice
Author: Myint Swe Khine
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-10-30
Structural Equation Modeling (SEM) is a statistical approach to testing hypothesis about the relationships among observed and latent variables. The use of SEM in research has increased in psychology, sociology, and economics in recent years. In particular educational researchers try to obtain the complete image of the process of education through the measurement of personality differences, learning environment, motivation levels and host of other variables that affect the teaching and learning process. With the use of survey instruments and interviews with students, teachers and other stakeholders as a lens, educators can assess and gain valuable information about the social ecology of the classrooms that could help in improving the instructional approach, classroom management and the learning organizations. A considerable number of research have been conducted to identify the factors and interactions between students’ characteristics, personal preferences, affective traits, study skills, and various other factors that could help in better educational performance. In recent years, educational researchers use Structural Equation Modeling (SEM) as a statistical technique to explore the complex and dynamic nature of interactions in educational research and practice. SEM is becoming a powerful analytical tool and making methodological advances in multivariate analysis. This book presents the collective works on concepts, methodologies and applications of SEM in educational research and practice. The anthology of current research described in this book will be a valuable resource for the next generation educational practitioners.
Structural Equation Modeling in Educational Research
Over the years, researchers have developed statistical methods to help them investigate and interpret issues of interest in many discipline areas. These methods range from descriptive to inferential to multivariate statistics. As the psychometrics measures in education become more complex, vigorous and robust methods were needed in order to represent research data efficiently. One such method is Structural Equation Modeling (SEM). SEM is a statistical technique that allows the simultaneous analysis of a series of structural equations. It also allows a dependent variable in one equation to become an independent variable in another equation. It is a comprehensive statistical approach to testing hypotheses about relations among observed and latent variables. SEM is commonly known as causal modeling, or path analysis, which hypothesizes causal relationships among variables and tests the causal models with a linear equation system. As educational research questions become more complex, they need to be evaluated with more sophisticated tools. The pervasive use of SEM in the literature has shown that SEM has a potential to be of assistance to modern educational researchers. This book will bring together prominent educators and researchers from around the world to share their contemporary research on structural equation modeling in educational settings. The chapters provide information on recent trends and developments and effective applications of the different models to answer various educational research questions. This book is a critical and specialized source that describes recent advances in SEM in international academia.
Research Methodology in Education and Application of Statistics
Research Methodology in Education and Application of Statistics for students and educators delving into educational research. The book meticulously outlines key research designs, data collection methods, and the application of statistical techniques essential for analyzing educational data. It bridges theoretical concepts with practical examples, enabling readers to conduct robust and meaningful studies. Additionally, the text includes exercises and case studies that enhance understanding and application of research principles, making it an invaluable resource for those aiming to advance their expertise in educational research and statistical analysis.