Speaker
Description
The rapid integration of Artificial Intelligence (AI) in higher education has created new opportunities to enhance language learning, particularly in listening comprehension and note-taking skills. This research investigates the effectiveness of AI-assisted instruction in improving listening and note-taking abilities among first-year English as a Foreign Language (EFL) students at a private university in Vietnam (HUFLIT). Adopting a mixed-methods design, the research involved 80 participants divided into an experimental group, which engaged with AI-based tools for listening practice and structured note-taking, and a control group receiving conventional instruction. Quantitative data were collected through pre- and post-tests and analyzed using paired and independent samples t-tests, while qualitative insights were obtained from student questionnaires and reflective journals. The findings indicate that students in the experimental group demonstrated statistically significant improvements in both listening comprehension and note-taking performance compared to their counterparts in the control group. Moreover, participants reported increased engagement, autonomy, and confidence when using AI tools, although some challenges related to over-reliance and technical limitations were noted. The research underscores the pedagogical potential of AI in supporting skill development in EFL contexts and highlights the need for guided implementation to maximize learning outcomes. These results contribute to the growing body of research on AI in language education and offer practical implications for curriculum design and instructional practices in similar tertiary settings.
