Factors Affecting the Acceptance of E-learning by Learners in the Context of the Covid-19 Pandemic: A Hybrid Artificial Neural Network - SEM Method

Abstract

This research aims to determine the factors affecting the student’s intention of E-learning adoption in the context of the Covid-19 pandemic in Vietnam. An online survey was used to assess the proposed psychological determinants of E-learning adoption. Confirmatory factor analysis and structural equation modeling were conducted on the collected data (n=310) using the SPSS 20 and the AMOS 24 statistical software. The reliability and validity of the measurement were examined via Cronbach’s alpha, EFA, CFA while the strength and direction of the hypothesized causal paths among the constructs were analyzed via SEM. Finally, the results from SEM were used as the inputs for an Artificial Neural Network (ANN) model to predict acceptance factors. The results of the study indicated that there was a significant positive relationship between the attitude toward risk (Covid-19), PU, PE and the intention of E-learning adoption. Furthermore, combining SEM and neural networks enabled the capture of linear and complex nonlinear relationships between predictors and the dependent variables.

Keywords

• E-learning
• intention to study
• attitude to study
• artificial neural networks
• Hybrid ANN - SEM