Exploring factors influencing L2 learners’ use of GAI-assisted writing technology: based on the UTAUT model
Yang Yang
Abstract
Generative Artificial Intelligence (GAI) can assist in second language writing, yet limited research has focused on the actual utilization of this technology by L2 learners. To fill these gaps in the existing literature, this study, framed with the Unified Theory of Acceptance and Use of Technology (UTAUT), aims to explore factors influencing L2 learners’ usage behavior of GAI in second language writing, along with the moderating effects of gender, experience, and language proficiency. The data for this study were collected from 419 graduate students in China. Data were analyzed by employing the Partial Least Squares Structural Equation Modelling (PLS-SEM) approach. The findings revealed that: 1) performance expectancy (PE), effort expectancy (EE), and social influence (SI) significantly impacted learners’ behavioral intention (BI); 2) behavioral intention (BI) and facilitating conditions (FCs) were significant predictors of usage behavior (AU); 3) performance expectancy was more salient for male users, while social influence was more significant for female users; inexperienced users exhibited a stronger behavioral intention driven by performance expectancy; language proficiency did not moderate any of the relationships. The results of this study provide theoretical support for the UTAUT model and practical implications for the application of GAI technology in L2 writing education.