The structure of student engagement in online learning: A bi-factor exploratory structural equation modelling approach

Enhancing student engagement plays a critical role in reducing student drop-out rate in online learning as students usually feel isolated and disconnected in this learning environment. This requires a clear conceptualization of the student engagement construct and its underlying structure. However, the conceptual understanding of the student engagement construct has long been impeded by the inconsistency in its multidimensional structure and the conceptual ambiguity among its components. This study aims to examine the underlying structure of student engagement in online learning based on the bi-factor exploratory structure equation modelling framework (B-ESEM). Four competing models representing the underlying structure of student engagement in online learning were compared based on their degree of fit to survey data from 363 students in an online undergraduate program. Students' responses to the online learning engagement questionnaire were best represented by a B-ESEM model that provided simultaneous assessment of a global engagement factor and specific factors of behavioural, cognitive, affective and social engagement while controlling for item cross-loadings. However, behavioural engagement only retained limited specificity once the global engagement factor was taken into account. The study findings offer a solution to reconcile the inconsistency in the multidimensional structure of student engagement and reduce the conceptual ambiguity among its components, thus contribute to better measuring student engagement in online learning.

Automated summary

Enhancing student engagement is crucial in reducing student drop-out rates in online learning. This study used the B-ESEM framework to examine the underlying structure of student engagement in online learning, finding that a global engagement factor and specific factors of behavioral, cognitive, affective, and social engagement best represented students' responses. By reconciling inconsistencies in the multidimensional structure of student engagement, this study contributes to better measuring student engagement in online learning.