Positive emotions, digital skills and reflection predict academics' perceived development of online teaching expertise: An experience sampling study

Abstract

The increasing adoption of online teaching in higher education (HE), especially in the post-pandemic era and with the rise of artificial intelligence, highlights the need to better understand how online teaching expertise evolves. Recognising that such developments may fluctuate across contexts and time, this study employed an experience sampling method (ESM) to investigate both within-teacher variability and between-teacher differences in time-variant predictors of perceived expertise development in online teaching. The sample consisted of 25 university teachers, representing a substantial size for intensive longitudinal research using ESM in HE. Participants provided repeated diary entries via a mobile app before and after teaching or planning sessions. These entries captured emotional valence, digital skills, reflection and perceived development of online teaching expertise. Bayesian cumulative mixed-effects analyses revealed that state positive emotions during teaching and planning sessions were positively associated with perceived development of online teaching expertise. Momentary perceptions of digital skilfulness during sessions were more influential than stable trait-level differences between individuals. Furthermore, teachers who engaged more frequently in reflective practices across sessions reported greater cumulative expertise development. These findings underline the importance of within-teacher dynamics in emotions and digital skills and between-teacher differences in reflection in shaping the development of online teaching expertise. The implications of the study and future research are discussed.