The developmental trajectory of L2 students’ positive achievement emotions and flow experience within AI-enhanced classrooms: A latent growth curve modeling (LGCM)

Abstract

The integration of artificial intelligence (AI) in L2 classrooms has garnered remarkable attention due to its potential to enhance students’ language achievements. While existing research has highlighted the implications of incorporating AI into L2 classrooms, there remains a gap in understanding how this incorporation may affect students’ achievement emotions and flow experiences. To narrow this gap, this intervention study sought to assess the influence of AI-enhanced instruction on L2 students’ positive achievement emotions: pride, hope, enjoyment, and their flow experiences. Furthermore, with the aid of latent growth curve modeling (LGCM), the study tried to track the developmental trajectory of L2 students’ positive achievement emotions and flow experiences over the course of a semester. To these aims, a large sample of 217 L2 students was recruited and randomly divided into the control or experimental groups. To measure participants’ flow and positive achievement emotions, two questionnaires were administered to them at distinct intervals throughout the intervention. The results evinced a notable enhancement in both the flow experience and positive achievement emotions of participants who were exposed to AI-enhanced instruction. This research underscores the critical role of AI-enhanced instruction in fostering students’ positive achievement emotions and flow experiences within L2 classrooms.