How generative AI enhances self-regulated learning in EFL learners: a chain mediation model of “intention to use” and “learning engagement”

Abstract

Generative Artificial Intelligence is transforming English as a Foreign Language writing instruction. While much research has focused on technology acceptance, limited attention has been paid to how AI influences learners’ psychological and behavioral processes, thereby affecting self-regulated learning. This study constructs and tests a theoretical model that examines the chain mediation of “intention to use → learning engagement” to explore how generative AI impacts self-regulated learning in EFL learners. Involving 386 Chinese EFL learners from universities, the study uses a questionnaire survey and structural equation modeling for data analysis. The findings show that the perceived ease of use, usefulness, and interactivity of generative AI significantly predict both intention to use and self-regulated learning. Intention to use is related to learning engagement, which in turn fosters self-regulated learning. Moreover, generative AI enhances self-regulated learning through intention to use and learning engagement, with these factors serving as key mediators. This study illuminates the pathway from “technology perception” to “behavioral intention, ” “immersive engagement, ” and “regulatory process, ” providing novel insights into AI-assisted second language writing learning and offering empirical evidence for designing effective human-computer collaborative EFL writing practices.