Tinto’s integration theory has highly influenced research on student success in Europe and America. However, due to the complexity of the theory and the enormous amount of variables, the theory is not suitable for use in regular evaluations in higher education.
By including only the best-proven predictive variables, I reduced the amount of variables from Tinto’s theory, avoiding the capitalization of chance and establishing a more easy to use model for teachers and management. The latent variable ‘satisfaction’ was built by using a fraction of the original manifest variables. It was tested, using principal component analysis, in a previous study to prove a good fit of the model. In this paper I focus on the role of background variables (gender, ethnicity, previous education and living situation), to measure their possible influence. A multi-group comparison (X2 difference test) in SPSS AMOS is conducted and path analysis is done to uncover differences on individual paths between the variables.
This paper is part of my PhD research, wherein I investigate the possible influence of the use of social media by first year students in higher education.