A study on the influencing factors of university students’ online persistent learning supported by intelligent technology in the post-pandemic era: an empirical study with PLS-SEM

Abstract

ABSTRACT Online learning became more commonplace all over the world in the post-pandemic era; however, the research on how to promote Online Persistent Learning (OPL) was still in its infancy. Therefore, this study aimed to analyse the influencing factors of Online Persistent Learning Supported by Intelligent Technology (OPLSIT) based on the dimensions of user's stickiness, dispositional trust and learning satisfaction. The Partial Least Squares Structural Equation Model (PLS-SEM) method was used to analyse data collected from 385 students who experienced online learning supported by intelligent technology (OLSIT). The results showed that learning satisfaction has a significant positive impact on OPL. In addition, user stickiness and dispositional trust were also two important predictors of OPL. Learning intention, social presence and cognitive presence were positively correlated with learning satisfaction, which indirectly and positively influence OPL. Technology anxiety had a negatively impact on learning satisfaction, which indirectly and negatively affected the OPL. Therefore, suggestions that enhance OPLSIT were put forward from the perspectives of teaching presence, cognitive presence, social presence, emotional presence, learning intention and dispositional trust and user stickiness for the design and development of intelligent online learning tools.