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Bridging Academic Vocabulary Learning and Technology in Higher Education: An Exploratory Study (104466)

Session Information: Foreign Languages Education and Applied Linguistics
Session Chair: Ricky Fernandes
This presentation will be live-streamed via Zoom (Online Access)

Friday, 27 March 2026 15:40
Session: Session 3
Room: Live-Stream Room 4
Presentation Type: Live-Stream Presentation

All presentation times are UTC + 9 (Asia/Tokyo)
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Academic vocabulary plays a critical role in higher education, yet it continues to present challenges for many language learners. Although Generative AI (GenAI) offers new opportunities for autonomous learning, little is known about how students utilise these tools for vocabulary development or the factors that influence their learning behaviours. Our exploratory study investigated the adoption of GenAI for academic vocabulary learning among undergraduate students in the Chinese mainland. Findings indicate that most participants have incorporated GenAI into their learning and employ a range of metacognitive, cognitive, and memory strategies to support the process. Follow-up interview responses revealed that individual differences, particularly language proficiency and disciplinary background, influence the selection and application of these strategies. The study offers insights into the evolving landscape of autonomous learning and highlights the increasingly sophisticated role of technology in vocabulary acquisition.

Authors:
Mi Zhang, Guangzhou Xinhua University, China
Edsoulla Chung, Hong Kong Metropolitan University, Hong Kong


About the Presenter(s)
Edsoulla Chung, an Assistant Professor at Hong Kong Metropolitan University, specialises in teacher development and English language education. Her recent publications have appeared in Assessing Writing, System, and TESOL Quarterly.

Connect on ResearchGate
https://www.researchgate.net/profile/Edsoulla-Chung

Additional website of interest
https://www.hkmu.edu.hk/edsoulla

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Posted by James Alexander Gordon

Last updated: 2023-02-23 23:45:00