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AMOS ile Yapısal Eşitlik Modellemesi

The pros and cons of a study choice test

First year undergraduate students at the Amsterdam University of Applied Sciences of two different departments, were asked to join self-reported surveys in two succeeding years. Along with background variables, effort and commitment, the surveys asked elements of engagement. The later was analysed with factor analysis. The data of the surveys together with the results of the exams from the first year, were investigated to find out if the mandatory study choice test (SCT) taken before entering the faculty, had any predictive effect on their success. Not only basic statistical analysis like correlation was performed, but also more advanced analysis such as structural equation modelling (SEM) was used to uncover the value of the SCT. After a model was built, the normed fit index (NFI), the comparative fit index (CFI), the Tucker-Lewis Index (TLI) and the root mean square error of approximation (RMSEA), were used to determine the fit of the model. By comparing the influence of the variables on the SCT, the benefits of the latter will be determined and ultimately enhance the knowledge about influences upon student success in higher education.

Attrition in higher education

In this research, which is part of my PhD research into the influence of the use of social media in higher education, I have lessened the amount of variables, from Tinto’s integration theory. By including only the best-proven predictive variables, based on previous studies, I avoid the capitalization of chance and have built a more easy to use model for teachers and management. The latent variable ‘satisfaction’ is constructed by using just a fraction of the original manifest variables. The simplified model is tested using principal component analysis (PCA), to prove its fit. Furthermore, to better suit students’ contemporary society in the developed world, the model is enriched with the use of social media, in this case Facebook. The purpose of Facebook use (information, education, social and leisure) and the use of different pages amongst students were also measured with PCA. This provided a better insight in the integration/engagement components, which are also included in the new model. According by the measurements of Cronbach’s alpha and Guttman’s lambda-2, the new components showed internal consistency and reliability. In addition, SPSS AMOS was used for testing the fit of the model and showed reasonable values for the normed fit index (NFI), the comparative fit index (CFI), the Tucker-Lewis Index (TLI) and the root mean square error of approximation (RMSEA). This study will compare different background variables within the model to uncover the possible influences upon students’ attrition (and therefor also their success), engagement/satisfaction and social media use. Ultimately this paper will provide jet another piece to the puzzle for a better insight into the factors of students’ attrition and/or success.

Acceptance of Technologies for Aging in Place: A Conceptual Model

BACKGROUND: Older adults want to preserve their health and autonomy and stay in their own home environment for as long as possible. This is also of interest to policy makers who try to cope with growing staff shortages and increasing health care expenses. Ambient assisted living (AAL) technologies can support the desire for independence and aging in place. However, the implementation of these technologies is much slower than expected. This has been attributed to the lack of focus on user acceptance and user needs.OBJECTIVE: The aim of this study is to develop a theoretically grounded understanding of the acceptance of AAL technologies among older adults and to compare the relative importance of different acceptance factors.METHODS: A conceptual model of AAL acceptance was developed using the theory of planned behavior as a theoretical starting point. A web-based survey of 1296 older adults was conducted in the Netherlands to validate the theoretical model. Structural equation modeling was used to analyze the hypothesized relationships.RESULTS: Our conceptual model showed a good fit with the observed data (root mean square error of approximation 0.04; standardized root mean square residual 0.06; comparative fit index 0.93; Tucker-Lewis index 0.92) and explained 69% of the variance in intention to use. All but 2 of the hypothesized paths were significant at the P<.001 level. Overall, older adults were relatively open to the idea of using AAL technologies in the future (mean 3.34, SD 0.73).CONCLUSIONS: This study contributes to a more user-centered and theoretically grounded discourse in AAL research. Understanding the underlying behavioral, normative, and control beliefs that contribute to the decision to use or reject AAL technologies helps developers to make informed design decisions based on users' needs and concerns. These insights on acceptance factors can be valuable for the broader field of eHealth development and implementation.

Adolescents’ expectations about the timing of family life events

Intergenerational continuity in family behaviors partly results from socialization processes in the parental home. However, socialization is a multidimensional process. This article tests hypotheses about the relative importance of value transmission and modeling in explaining expectations of adolescence concerning the timing of leaving home, and entry into cohabitation, marriage, and parenthood. Structural equation modeling on multiactor data from over 1,000 parent–adolescent child couples in the Netherlands is used to test hypotheses. Results suggest that, in general, both value transmission and modeling are important predictors of adolescents’ expectations concerning the timing of major family events. Moreover, no differences between mothers and fathers and between boys and girls are observed in the strength of the intergenerational relationships studied.

The development and validation of a five factor model of sources of self-efficacy in clinical nursing education

Background: The aim of this study is to validate a newly developed nurses' self-efficacy sources inventory. We test the validity of a five-dimensional model of sources of self-efficacy, which we contrast with the traditional four-dimensional model based on Bandura's theoretical concepts. Methods: Confirmatory factor analysis was used in the development of the newly developed self-efficacy measure. Model fit was evaluated based upon commonly recommended goodness-of-fit indices, including the χ2 of the model fit, the Root Mean Square Error of approximation (RMSEA), the Tucker-Lewis Index (TLI), the Standardized Root Mean Square Residual (SRMR), and the Bayesian Information Criterion (BIC). Results: All 22 items of the newly developed five-factor sources of self-efficacy have high factor loadings (range .40-.80). Structural equation modeling showed that a five-factor model is favoured over the four-factor model. Conclusions and implications: Results of this study show that differentiation of the vicarious experience source into a peer- and expert based source reflects better how nursing students develop self-efficacy beliefs. This has implications for clinical learning environments: a better and differentiated use of self-efficacy sources can stimulate the professional development of nursing students.