Language Learning and Identity Construction Through ChatGPT: Evidence from Jordanian Gen Z in English University Courses

Abstract

This study investigates how Jordanian Generation Z students use ChatGPT to support English language learning in eLearning environments, focusing on proficiency outcomes, code switching practices, and identity negotiation. Using a mixed methods approach, data were collected from 300 undergraduate students enrolled in English medium courses at two Jordanian private universities through surveys, pre and post tests, interaction logs, and semi structured interviews. Quantitative findings showed significant improvements in vocabulary and grammar, alongside moderate gains in writing organization, while listening comprehension demonstrated no measurable progress. Qualitative analysis revealed frequent code switching and hybrid linguistic forms in ChatGPT interactions, reflecting students’ authentic bilingual repertoires, although the system often normalized these toward standardized English. Interview data further indicated that students valued ChatGPT for its immediacy and its ability to enhance confidence in language use, while emphasizing the continued importance of teachers for providing cultural nuance, empathy, and critical feedback. Overall, the findings suggest that ChatGPT can serve as a valuable complement to eLearning by strengthening literacy-based skills and offering a low stakes environment for experimentation, while also raising concerns about linguistic homogenization and potential over reliance on AI tools. The study concludes that effective integration of AI in language education requires pedagogical strategies that recognize and support multilingual practices, policies addressing ethical and cultural considerations, and further research on the long-term implications of AI use for learner identity.