Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Exploring Saudi EFL Learners’ Engagement with ChatGPT: A Mixed-Methods Study of Perceptions, Attitudes, and Intentions
3
Zitationen
2
Autoren
2025
Jahr
Abstract
This study explores Saudi EFL learners’ perceptions, attitudes, and intentions regarding using ChatGPT as an AI-mediated tool for English language learning. Employing a mixed-methods design, 181 students completed a survey, and 4 participated in follow-up interviews to offer a more nuanced understanding of learner experiences. Quantitative findings reveal high perceived usefulness ( M = 3.9), a generally pleasant user experience ( M = 3.95), and a firm intention to continue using the tool ( M = 3.7). Pearson correlation analysis confirmed significant positive relationships between perception and intention ( r = .797, p < .001) and between attitude and intention ( r = .733, p < .001), thereby reinforcing the explanatory power of the Technology Acceptance Model (TAM) in the Saudi EFL context. Qualitative findings add depth to the statistical trends, showcasing that Saudi EFL considered ChatGPT not merely a functional platform but an emotionally supportive and context-sensitive mediator in their academic language development. Students demonstrated critical agency, using the tool strategically for scaffolding, meaning-making, and managing learning anxiety while remaining vigilant about its limitations. Participants expressed concerns about over-reliance on AI, warning against diminished critical thinking, intellectual complacency, and the erosion of human interaction in education. Framed through the dual lenses of TAM and sociocultural theory, the study argues that learners do not passively adopt ChatGPT; instead, they negotiate its role as a complementary and temporary scaffold that enhances but does not replace human faculties and social learning environments. Thus, the study underscores the need for pedagogically grounded and ethically informed integration of AI into language education. These findings offer valuable implications for designing more balanced, culturally responsive, and learner-centered approaches to technology use in Saudi EFL classrooms.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.239 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.095 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.463 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.428 Zit.