Amsterdam University of Applied Sciences (NETHERLANDS)
About this paper:
Appears in: INTED2018 Proceedings
Publication year: 2018
Pages: 1478-1485
ISBN: 978-84-697-9480-7
ISSN: 2340-1079
doi: 10.21125/inted.2018.0252
Conference name: 12th International Technology, Education and Development Conference
Dates: 5-7 March, 2018
Location: Valencia, Spain
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.
Attrition, student success, higher education, social media, Facebook, structural model.