scholarly journals A Structural Equation Modeling on Factors of How Experienced Teachers Affect the Students’ Science and Mathematics Achievements

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Serhat Kocakaya ◽  
Ferit Kocakaya
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Experienced Teachers ◽  
Equation Modeling ◽  
Expert Teachers ◽  
Fit Indices ◽  
School Students ◽  
Positive Effects ◽  
Dependent Variables ◽  
And Mathematics

The main purpose of this study was to propose a model for how elementary school students’ science and mathematics achievements in their schools and in Level Determination Exam (SBS) depend on the number of teachers and expert teachers in their schools. The sample of the study was 5672 elementary students for the purpose of the study, the number of teachers and expert teachers who worked in sample schools has been defined as independent variables, and students’ science and mathematics achievements in their schools and in SBS exam have been defined as dependent variables. The data obtained from school administrations were analyzed using structural equation modeling to analyze relations among students’ science and mathematics grades in their schools and science and mathematics achievements in SBS exam and the number of teachers and expert teachers in their school. As a result of the analysis, it has been observed that established model has acceptable fit indices and an increasing number of teachers and expert teachers have positive effects on students' science and mathematics achievements.

scholarly journals Women’s self-care behavior and its relationship with social capital in Yazd, Iran

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hamideh Shiri-Mohammadabad ◽  
Seyed Alireza Afshani
Keyword(s):  
Social Capital ◽  
Structural Equation ◽  
Self Care ◽  
Equation Modeling ◽  
Fit Indices ◽  
Factors Affecting ◽  
Positive Effects ◽  
The Social ◽  
The City ◽  
Care Behavior

Abstract Background Research on factors affecting self-care is scarce. The social factors, in particular, have not been yet investigated in Iran. Therefore, the present study aimed to investigate the relationship between self-care and social capital among women. Methods The participants were 737 women who were living in the marginal, middle and upper areas in the city of Yazd, Iran. Data were collected using a researcher-made self-care questionnaire and Harper’s (Off Natl Stat 11:2019, 2019) Social Capital Scale. The data were analyzed using structural equation modeling by SPSS and Amos v24. Results The results showed that the social capital had significant positive effects on the general self-care behavior of the participants (β = 0.56, p < 0.001). It also had significant positive effects on the self-care behavior of women living in the marginal (β = 0.58), middle (β = 0.49) and upper (β = 0.62) parts of the city (p < 0.001). Besides, the women living in the marginal parts had relatively lower levels of self-care compared to those living in the middle and upper parts of the city. The examination of the fit indices indicated that the model has a good fit (CMIN/DF = 2.087, NFI = 0.921, RMSEA = 0.027, CFI = 0.956, TLI = 0.940, GFI = 0.956, IFI = 0.957). Conclusion The findings of this study demonstrated that social capital has significant positive effects on the general self-care behavior of women. Therefore, improving their self-care can be achieved through promoting their social capital.

scholarly journals Investigating the reciprocal relations between academic buoyancy and academic adversity: Evidence for the protective role of academic buoyancy in reducing academic adversity over time

2019 ◽  
Vol 44 (4) ◽  
pp. 301-312 ◽  
Author(s):  
Andrew J. Martin ◽  
Herbert W. Marsh
Keyword(s):  
High School Students ◽  
Structural Equation ◽  
Protective Role ◽  
Theory And Practice ◽  
Equation Modeling ◽  
School Students ◽  
Positive Effects ◽  
Academic Buoyancy ◽  
One Year

What is the relationship between academic buoyancy and academic adversity? For example, does the experience of academic adversity help build students’ academic buoyancy in school—or, does academic buoyancy lead to decreases in subsequent academic adversity? This longitudinal study of 481 high school students (Years 7–12) investigated the relations between academic buoyancy and academic adversity. Harnessing a cross-lagged panel design spanning two consecutive academic years, we employed structural equation modeling to investigate the extent to which prior academic buoyancy predicted subsequent academic adversity and the extent to which prior academic adversity predicted subsequent academic buoyancy—beyond the effects of sociodemographics, prior achievement, and auto-regression. We found that prior academic buoyancy significantly predicted lower subsequent academic adversity, but prior academic adversity did not significantly predict higher subsequent academic buoyancy. Interestingly, however, there was a marginal interaction effect such that students who experienced academic adversity but who were also high in academic buoyancy were less likely to experience academic adversity one year later. We conclude that it is important to instill in students the capacity to effectively deal with academic adversity—that is, academic buoyancy. We also conclude that some experience of academic adversity can have positive effects but predominantly when accompanied by high levels of academic buoyancy. Implications for theory and practice are discussed.

Digital Adaptability: A New Measure for Digital Inequality Research

2020 ◽  
pp. 089443932092608
Author(s):  
Cassidy Puckett
Keyword(s):  
High School Students ◽  
Structural Equation ◽  
Discriminant Validity ◽  
New Technologies ◽  
Past Research ◽  
Equation Modeling ◽  
School Students ◽  
Digital Inequality ◽  
Eighth Grade Students ◽  
And Mathematics

Past research suggests the ability to adapt to technological change by learning new technologies is a core feature of technological competence and consequential for inequality. Yet there exists no definition or measure of what people do to learn technologies that are new to them and empirically link this to inequality. To address this gap, I conducted studies involving over 2,000 adolescents to develop and validate a measure of what I call “digital adaptability,” the use of five habits that help individuals learn technologies that are new to them. The studies included observation and cognitive interviews to describe adaptability and develop an initial item pool, a pilot to narrow items using structural equation modeling, a full test with 897 eighth-grade students in Chicago with analysis of convergent and discriminant validity, and a replication study with 1,285 high school students near Boston. Finally, using Chicago and Boston area data, I find adaptability correlates with students’ educational plans and career aspirations in science, technology, engineering, and mathematics —linking digital adaptability to students’ futures. Overall, the digital adaptability measure provides a critical theoretical and empirical tool for digital inequality research, practice, and policy.

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