Hyeryoung holds two master's degrees: an MA in TESOL from the UCL Institute of Education (2020), and an MA in Language, Cultural Diversity from King's College London (2022). She also obtained a TESOL Certificate from the Australian TESOL Training Centre in Sydney, Australia.

Before undertaking her 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 strongly influenced her academic interests, which centre on Technology-Enhanced Language Learning (TELL), with a particular focus on Mobile-Assisted Language Learning (MALL), Second Language Acquisition (SLA), and psycholinguistics.

Her broader research interest lies in understanding how digital innovation and AI-powered tools can transform language pedagogy, support learner autonomy, and enhance engagement in diverse EFL contexts. Her doctoral research explores the effectiveness of AI-powered mobile application in enhancing English vocabulary acquisition among adult Korean learners preparing for the TOEIC test.

Thesis

A Comparative Study of Vocabulary Learning Approaches: The Role of AI-Powered Mobile Apps in Adult Learners' Vocabulary Acquisition, and Self-Directed Learning in Korea.

Abstract

This research investigates the effectiveness of AI-powered mobile applications in enhancing English vocabulary acquisition and promoting self-directed learning among adult Korean EFL learners preparing for the TOEIC test. Adapting a mixed-methods, quasi-experimental design, the study compares three learning conditions - non-digital, non-AI digital, and AI-powered applications - to examine how adaptive features such as personalised feedback, spaced repetition, and progress tracking influence learners’ vocabulary development, engagement, and self-directed learning behaviours over time.The research involves adult learners in a private language institute, and data are collected through both quantitative and qualitative approaches to capture learning outcomes and learner experiences comprehensively. The findings are expected 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 in technology-enhanced vocabulary learning.

Principal supervisor: Dr Christina Richardson

Secondary supervisor: Dr Clyde Ancarno