Hyeryoung is a PhD candidate in Language, Discourse and Communication. She holds two master's degrees: an MA in TESOL from the UCL Institute of Education, and an MA in Language and Cultural Diversity from King's College London. She also obtained a TESOL teaching certificate from the Australian TESOL Training Centre in Sydney, Australia. 

Before undertaking postgraduate studies in the United Kingdom, she taught English to young EFL learners in South Korea and later served as an Assistant Headteacher at a private language institute. Her extensive teaching experience has informed her academic interests, which focus on technology-mediated Language Learning, Computer Assisted Language Learning (CALL), particularly Mobile-assisted Language Learning, Second Language Acquisition (SLA), and psycholinguistics.

Her broader research interests explore how digital innovation and AI-powered tools can transform language pedagogy, support learner's autonomy and enhance vocabulary learning outcomes in diverse EFL contexts. Her doctoral research investigates the effectiveness of AI-powered mobile applications for enhancing English vocabulary acquisition among adult Korean learners preparing for the TOEIC test.

Thesis

The Role of AI-Powered Mobile Apps in Adult EFL Learners’ Vocabulary Acquisition and Self-Regulated Learning in Korea

Abstract

This research investigates the effectiveness of AI-powered mobile applications in supporting English vocabulary acquisition and self-regulated learning among adult Korean EFL learners preparing for the TOEIC test. Adopting a mixed-methods, quasi-experimental design, the research compares three learning conditions – paper-based vocabulary lists, non-AI digital flashcards, and AI-powered applications – to examine how adaptive features such as personalised feedback, spaced repetition, and progress tracking influence learners’ vocabulary development, and self-regulated learning behaviours over time. The study involves adult learners enrolled in a private language institute in Korea, and data are collected through both quantitative and qualitative approaches to capture learning outcomes and learner experiences comprehensively. The findings aim to provide empirical evidence on the pedagogical value of AI-enhanced learning tools in exam-oriented EFL contexts and contribute to advancing theoretical and practical understanding of technology-enhanced vocabulary learning.

Principal supervisor: Dr Christina Richardson

Secondary supervisor: Dr Clyde Ancarno