Structural equation modeling and confirmatory factor analysis of social media use and education

• Published in: International Journal of Educational Technology in Higher Education Vol. 16; no. 1; pp. 1 - 25
• Main Authors: Abrahim, Shugufta, Mir, Bilal Ahmed, Suhara, Hayato, Mohamed, Fatin Amirah, Sato, Masahiro
• Format: Journal Article
• Language: English
• Published: Cham Springer Science and Business Media LLC 22.07.2019; Springer International Publishing; Springer Nature B.V; SpringerOpen
• Subjects: Asian students; Collaborative learning; Computer Appl. in Social and Behavioral Sciences; Computer Science; Computers and Education; Confirmatory factor analysis; Dependent variables; Digital media; Discriminant analysis; Education; Educational Objectives; Educational Technology; Facebook; Factor analysis; Foreign languages; Goodness of fit; Higher Education; Humanities; Independent variables; Information Systems Applications (incl.Internet); Information technology; Law; LC8-6691; Model testing; Non English Speaking; Research Article; Social media; Social networks; Special aspects of education; Statistics for Social Sciences; Structural equation modeling; Structural equation modelling; Structural Equation Models; Students; T58.5-58.64; Confirmatory factor analysis; Structural equation modelling; Facebook; Social media; Collaborative learning
• ISSN: 2365-9440; 2365-9440
• DOI: 10.1186/s41239-019-0157-y

The objective of this study is to design a structural equation model and test confirmatory factor analysis system in order to better explain how students could utilize social networking system (Facebook) for educational purposes. Thus, this paper seeks to examine the attitude, perception and behaviour of Japanese students’ towards social-networking sites, and how students from non-English speaking backgrounds (especially Japanese students) at the University of Toyama perceive the use of Facebook for learning English as a foreign language. Our Structural Equation Modelling system based Facebook model outline the relations among different types of independent, dependent variables and constructs. We tested our model using adequate fitting indices like Goodness of Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI), Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), Non-Normed Fit Index/Tucker Lewis index (NNFI/TLI) and Incremental Fit Index (IFI). The results of the proposed model confirmed the hypothesized latent structures and theoretical validity of probed factors. Conclusions drawn from this study might be useful to better understand the use of social networking tools in educational context.