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Zhao, Yu; Lei, Pui-Wa – AERA Online Paper Repository, 2016
Despite the prevalence of ordinal observed variables in applied structural equation modeling (SEM) research, limited attention has been given to model evaluation methods suitable for ordinal variables, thus providing practitioners in the field with few guidelines to follow. This study represents a first attempt to thoroughly examine the…
Descriptors: Factor Analysis, Monte Carlo Methods, Causal Models, Least Squares Statistics
Waheed, M.; Kaur, K.; Kumar, S. – Journal of Computer Assisted Learning, 2016
Quality knowledge has an impact on online students learning outcomes and loyalty. A framework that delineates the perceived eLearning knowledge quality (KQ) and its relationship with learning outcomes and loyalty is currently absent. Grounded in the KQ and information system success framework--this study presents the indicators of perceived…
Descriptors: Electronic Learning, Student Satisfaction, Outcomes of Education, Undergraduate Students
Ozel, Murat; Caglak, Serdar; Erdogan, Mehmet – Learning and Individual Differences, 2013
This study investigated how affective factors like attitude and motivation contribute to science achievement in PISA 2006 using linear structural modeling. The data set of PISA 2006 collected from 4942 fifteen-year-old Turkish students (2290 females, 2652 males) was used for the statistical analyses. A total of 42 selected items on a four point…
Descriptors: Factor Analysis, Science Achievement, Factor Structure, Structural Equation Models
Stamovlasis, D.; Kypraios, N.; Papageorgiou, G. – Science Education International, 2015
In this study, structural equation modeling (SEM) is applied to an instrument assessing students' understanding of chemical change. The instrument comprised items on understanding the structure of substances, chemical changes and their interpretation. The structural relationships among particular groups of items are investigated and analyzed using…
Descriptors: Structural Equation Models, Chemistry, Convergent Thinking, Logical Thinking
Ghanizadeh, Afsaneh; Ghonsooly, Behzad – Teacher Development, 2015
Causal attributions constitute one of the most universal forms of analyzing reality, since they fulfill basic functions in motivation for action. As a theory of causal explanations for success and failure, attribution research has found a natural context in the academic domain. Despite this, it appears that teacher attribution, in particular…
Descriptors: Foreign Countries, Language Teachers, English (Second Language), Attribution Theory
Ling, Guangming – ETS Research Report Series, 2012
To assess the value of individual students' subscores on the Major Field Test in Business (MFT Business), I examined the test's internal structure with factor analysis and structural equation model methods, and analyzed the subscore reliabilities using the augmented scores method. Analyses of the internal structure suggested that the MFT Business…
Descriptors: Factor Analysis, Construct Validity, Structural Equation Models, Correlation
Zeyer, Albert; Çetin-Dindar, Ayla; Md Zain, Ahmad Nurulazam; Juriševic, Mojca; Devetak, Iztok; Odermatt, Freia – Journal of Research in Science Teaching, 2013
The present study is based on the empathizing-systemizing (E-S) theory of cognitive science. It was hypothesized that the influence of students' gender on their motivation to learn science is often overestimated in the research literature and that cognitive style is more important for motivation than students' gender. By using structural equation…
Descriptors: Hypothesis Testing, Gender Differences, Student Motivation, Learning Motivation
Hwang, Gwo-Jen; Kuo, Fan-Ray – Australasian Journal of Educational Technology, 2015
Web-based problem-solving, a compound ability of critical thinking, creative thinking, reasoning thinking and information-searching abilities, has been recognised as an important competence for elementary school students. Some researchers have reported the possible correlations between problem-solving competence and information searching ability;…
Descriptors: Problem Solving, Structural Equation Models, Critical Thinking, Creative Thinking
Brauckmann, Stefan; Pashiardis, Petros – International Journal of Educational Management, 2011
Purpose: The overall purpose of the European Union-funded Leadership Improvement for Student Achievement (LISA) project was to explore how leadership styles, as conceptualized in the developed dynamic holistic leadership framework, directly or indirectly affect student achievement at the lower secondary level of education in seven European…
Descriptors: Foreign Countries, Faculty Development, Teacher Effectiveness, Leadership Styles
Sovajassatakul, Thanongsak; Jitgarun, Kalayanee; Shinatrakool, Raveewan – Journal of College Teaching & Learning, 2011
The purpose of the study reported on in this paper was to identify and compare instructors' and students' perceptions of Team-Based Learning (TBL). Participants were 270 instructors and 288 fourth year students from the faculties of Industrial Education at six universities in Bangkok. The data were analyzed using factor analysis and structural…
Descriptors: Instructional Design, Industrial Education, Student Attitudes, Structural Equation Models
Cambra-Fierro, Jesus; Cambra-Berdun, Jesus – Education & Training, 2007
Purpose: This paper aims to demonstrate that students' self-evaluations contribute to improving academic results and life skills. Design/methodology/approach: Taking as reference a group of previously validated scales (part 1: measurement), a causal model is developed. Hypotheses are tested through the structural equations methodology by using the…
Descriptors: Methods, Causal Models, Administrator Role, Academic Achievement

Schumacker, Randall E. – Mid-Western Educational Researcher, 1993
Structural equation models merge multiple regression, path analysis, and factor analysis techniques into a single data analytic framework. Measurement models are developed to define latent variables, and structural equations are then established among the latent variables. Explains the development of these models. (KS)
Descriptors: Causal Models, Data Analysis, Error of Measurement, Factor Analysis