Based on the S-O-R model – how does interaction influence engineering students' English learning continuance on online platforms

Students' satisfaction and continuance intention are critical for the success of online courses. Extensive research has been conducted to explore the contributors of continuance intention, focusing on the student-related and technological elements. However, few attempts have been made to comprehensively explore the influence of online learning interaction on students' continuance intention. Based on the stimulus-organism-response (S-O-R) model, this study proposed a model taking online interactions as the stimulus variable, learners' satisfaction as the organism variable, and learners' continuance intention as the response variable. Data on student engagement, satisfaction, and persistence in online learning were collected from a sample of 771 engineering students, ranging from freshmen to postgraduates. The data were analysed using structural equation modelling (SEM) to validate the proposed theoretical model. The results indicate that student-content interaction exerts the most significant influence on students' continuance intention among the four types of online learning interactions, highlighting the importance of learning materials' content quality. Meanwhile, the other three types of online interaction also have considerable influence coefficient. The findings provide some advice on improving e-learning interactions to promote engineering students' online English learning satisfaction and continuance intention.