Momentary emotions emerge and evolve differently, yet are surprisingly stable within students

Abstract

Research on academic emotions has explored different granularities that range from a full program to a single task. Yet, most of the existing research stems from cross-sectional studies. While immensely useful, lacking a temporal depth obfuscates the process of emotions into a flat process. To fill this gap, this study takes a process-oriented approach to study the momentary changes in academic emotions as they unfold in time into phases, changes, and successions of sequences during two lectures. We use intensive longitudinal data from 104 students attending a German University in the form of ecological momentary surveys. We rely on mixture models to cluster the data into states, use sequence analysis to map the longitudinal unfolding and mixture hidden Markov models to answer why certain longitudinal patterns emerge. Our findings point to differences among students in their reactions to contextual variables, yet, such reactions are relatively stable within students. In other words, students may have different emotional profiles, but these emotional profiles are surprisingly stable across time and contexts. © 2024 IEEE.