Skip to main content

Language Learning and Second Language Acquisition

ww

New approaches to improving second language learning and teaching
 

This research area takes a cross-linguistic approach to exploring cognitive aspects of second language (L2) learning, phonology, language disorders, learner autonomy, and more. Led by Prof Angel Ma, the Department of Linguistics and Modern Language Studies (LML) corpus team has developed a corpus-based pedagogy that benefits L2 learners by training teachers. A survey of over 400 teachers has been conducted and studied to create a framework for measuring teachers' corpus literacy. A case study involving L2 teachers who bring corpus technology into their classrooms provides insights into corpus-informed L2 teaching practices. Additionally, research by LML colleagues focusing on L2 vocabulary instruction and collaborative learning explores self-regulated language learning in mobile-assisted contexts.

 

Collaborate with us

 

Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure posperity for all.

The research team contributes towards the following SDG(s):

 

The research addresses several issues related to L2 learning and teaching, including cognitive aspects of language acquisition, enhancing language learning through big data and digital technology, teacher training in corpus linguistics and its impact on L2 learners, integration of corpus technology in L2 learning and teaching, and self-regulated language learning in mobile-assisted language learning (MALL) contexts. This project leverages the expertise of LML colleagues in analysing large-scale datasets, including language corpora, to create tools and methods for investigating linguistic patterns. This can facilitate knowledge transfer projects and funding bids to sources such as the Innovation and Technology Fund (ITF).

 

ww

 

LML colleagues’ General Research Fund (GRF) projects, in collaboration with researchers from prestigious universities, empower L2 learners and teachers in Hong Kong and internationally by promoting effective use of corpus technology as a valuable learning and teaching tool. Their research explores how teachers develop corpus literacy and implement corpus-based language pedagogy, assessing its effects on student engagement and self-directed learning. Other LML colleagues are currently leading interdisciplinary research on L2 phonological acquisition and its relationship to corpus technology and other technologies.

 

This research has far-reaching impact, benefiting a diverse range of stakeholders. It enhances corpus literacy and classroom practices for L2 teachers in Hong Kong, mainland China, and internationally. The findings from surveys of more than 400 pre-service and in-service L2 teachers are already informing further teacher training. L2 teachers in Hong Kong and 50 other countries/regions benefit from pioneering studies on corpus technology, influencing student engagement and self-directed learning. Interdisciplinary projects on Asian English Literature benefit researchers in literature, culture, and education. The research studies’ use of big data and digital technology enhances L2 learning and teaching for a broad audience.

 

Externally Funded Research Projects 

Project

General Research Fund

A self-regulated and personalised vocabulary learning approach mediated by mobile technologies for university students

General Research Fund

Effects of phonological rule-based and acoustic perceptual-based instructions on the prosodic acquisition of English Word Stress by Chinese ESL learners

General Research Fund

Third language (L3) phonological development for multilingual learners in the Chinese context

Early Career Scheme

L2 Phonemic Quantity Contrasts: Production and Perception by Cantonese, French, English and Japanese Speakers

General Research Fund

Comparative Prosody Modelling across Languages

General Research Fund

Tonal effects on articulation: Acoustic analysis, ultrasound data, and articulatory synthesis

General Research Fund

Investigating student teachers’ TPACK development for corpus technology and their self-efficacies for independent language learning and teaching: a mixed method study

 

Selected Publications

  1. Ma, Q., Chiu, M.M. (2024). Self-regulated and Collaborative Personalised Vocabulary Learning Approach in MALL. Language Learning & Technology, 28(1), 1-28.
  1. Ma, Q., Yuan, R. E., Cheung, L. M. E., & Yang, J. (2024). Teacher paths for developing corpus-based language pedagogy: A case study. Computer Assisted Language Learning, 37(3), 461-492. doi: 10.1080/09588221.2022.2040537
  1. Ma, Q., Chiu, M. M., Lin, S., & Mendoza, N. B. (2023). Teachers’ perceived corpus literacy and their intention to integrate corpora into classroom teaching: A survey study. ReCALL, 35(1), 19-39. Retrieved from https://doi.org/10.1017/S0958344022000180
  1. Ma, Q., & Yan, J. (2022). How to empirically and theoretically incorporate digital technologies into language learning and teaching. Bilingualism: Language and Cognition, 25(3), 392-393. doi: 10.1017/S136672892100078X
  1. Chen, H. C., & Chan, J. H. (2024). L2 English listeners’ perceived comprehensibility and attitudes towards speech produced by L3 English learners from China. International Journal of Multilingualism. Online publication. https://doi.org/10.1080/14790718.2024.2379549
  1. Chen, H. C., & Tian, J. X. (2024). The roles of Cantonese speakers’ L1 and L2 phonological features in L3 pronunciation acquisition. International Journal of Multilingualism.21(1), 
    1-17. doi: 10.1080/14790718.2021.1993231
  1. Chen, H. C. & Han, Q. W. (2023). The effects of metaphonological awareness training on L3 Mandarin tone acquisition by Cantonese learners. International Journal of Multilingualism. 20(2), 388-407. doi: 10.1080/14790718.2020.1820509
  1. Chen, H. C., & Tian, J. X. (2022). Developing and evaluating a flipped corpus-aided English pronunciation teaching approach for pre-service teachers in Hong Kong. Interactive Learning Environments, 30(10), 1918-1931. doi:10.1080/10494820.2020.1753217
  1. Lee, A., & Ng, E. (2022). Hong Kong women project a larger body when speaking to attractive men. Frontiers in Psychology, 12. Retrieved fromhttps://doi.org/10.3389/fpsyg.2021.786507
  1. Lee, A., Prom-on, S., & Xu, Y. (2021). Pre-low raising in Cantonese and Thai: Effects of speech rate and vowel quantity. Journal of the Acoustical Society of America, 149(1), 179-190. doi: 10.1121/10.0002976
  1. Ma, Q., Mei, F., & Qian, B. (2024). Exploring EFL students’ pronunciation learning supported by corpus-based language pedagogy. Computer Assisted Language Learning. https://doi.org/10.1080/09588221.2024.2432965
  1. Ma, Q., Crosthwatie, P., Sun, D., & Zou, D. (2024). Exploring ChatGPT literacy in language education: A global perspective and comprehensive approach. Computers and Education: Artificial Intelligence, Artificial Intelligence, 7, 100278  https://doi.org/10.1016/j.caeai.2024.100278