As part of my PhD research, I investigate the influence of the use of social media by first year students in higher education. In this research I have lessened the amount of variables, from Tinto’s theory, by including only the best-proven predictive variables, based on previous studies. Hereby, avoiding the capitalization of chance and a more easy to use model for teachers and management has been built. The latent variable ‘satisfaction’ is constructed by using just a fraction of the original manifest variables and tested using principal component analysis to proof the model can be simplified. Furthermore, I enriched the model with the use of social media, in particular Facebook, to better suit students’ contemporary society in the developed world. With principal analysis on Facebook usage, I measured the purpose of Facebook use (information, education, social and leisure) and the use of different pages amongst students. This provided different integration/engagement components, which are also included in the simplified model. For the principal component-analysis, Cronbach’s alpha and Guttman’s lambda-2 showed internal consistency and reliability. 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 with the model to uncover the possible influences upon student success, engagement/satisfaction and social media use. Ultimately this paper will provide a better insight into what kind of influence social media can have upon student success.
|Title of host publication||ICERI2017 proceedings|
|Editors||L. Gómez Chova, A. López Martínez, I. Candel Torres|
|Publication status||Published - 2017|
|Event||10th annual International Conference of Education, Research and Innovation - Seville, Spain|
Duration: 16 Nov 2017 → 18 Nov 2017
|Conference||10th annual International Conference of Education, Research and Innovation|
|Period||16/11/17 → 18/11/17|