AI-Integrated IELTS Learning Experiences among Guangzhou Private University IELTS Students: A Phenomenological Study in Digital Classrooms
The AI(Artificial Intelligence) era has firmly embedded digital technologies into the fabric of higher education, with AI spearheading a transformation in language learning. This phenomenological study explores the lived experiences of International English Language Testing System (IELTS) students at private universities in Guangzhou, China, as they utilize AI-integrated tools in digital and hybrid classrooms. Through semi-structured, in-depth interviews with ten participants, this research sought to understand the essence of their learning journey, focusing on perceptions, benefits, challenges, and the overall nature of human-AI interaction in a high-stakes testing context. Thematic analysis of the data revealed four superordinate themes: (1) The AI as a 24/7 Personalized and Non-Judgmental Tutor, highlighting accessibility and instant feedback; (2) Navigating the Algorithm's Logic and Its Limitations, which encapsulates the struggle with the perceived rigidity and lack of nuanced understanding of AI tools; (3) A Double-Edged Sword of Learner Autonomy, describing the simultaneous empowerment and disorientation students felt; and (4) The Enduring Need for Human Connection in a Digital Space, underscoring the irreplaceable role of teachers and peers for affective and strategic support. The findings suggest that while students value AI for its efficiency and practice opportunities, their experience is a complex interplay of empowerment and frustration. The study concludes with implications for educators, AI developers, and institutional policymakers, advocating for a blended pedagogical approach that leverages AI's strengths while preserving the essential human element in language education.
Authors
- Shang Liang
Publication Details
- Journal
- Journal of International Education and Development
- Published
- 2025-01-01
- DOI
- https://doi.org/10.47297/wspiedwsp2516-250029.20250909
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00