This project adopts a mixed-method design and seeks to examine how and why Hong Kong university students engage in informal digital learning of English (IDLE) activities in the wider out-of-class and digitalized learning ecology. We mainly build on two complementary theories—motivation (Dörnyei, 2009) and investment (Darvin & Norton, 2015; Norton, 1995) that dissects the extent to which individuals are able to engage with and commit to L2 learning from a psychological perspective and a sociocultural lens respectively. By providing a fuller understanding of students’ dynamic IDLE learning realities in English as a second language (ESL) settings, this project may contribute to the field and generate pedagogical implications for Hong Kong ESL instructors to bridge formal instruction and students' self-directed digital learning practices beyond the classroom.

Our project investigates the role of a critical pedagogy informed by World Englishes (WE) in influencing how multilingual students in Hong Kong invest in the Englishes of their own linguistic repertoire. It specifically focuses on learning activities in an undergraduate WE course in a local public university: (1) instructor-led discussions supplemented by learner pre-discussion notes, (2) learner-led collection of authentic linguistic data involving varieties of English in Hong Kong from their peer network(s) in the form of sociolinguistic interviews, time-aligned transcriptions, and corpus compilation, and (3) a collaborative mini-research project between learners that showcases how they connect and apply WE-related concepts to real-life scenarios with empirical evidence. We examine how these activities jointly shape the investment trajectories of students over time by conducting multiple-case studies.

The interactions between China and neighboring East Asian regions have led to multilingual practices such as code-switching and even the emergence of hybrid languages. These practices often display variability that reflect their complex origins and sociolinguistic contexts, and they are subject to change due to ongoing contact between speech communities. Research on the interactions between Sinitic languages and East Asian languages is growing, but there is still much to learn about the sociolinguistic patterns across Chinese-related linguistic practices. This project seeks to answer questions about how age, sex, region, and sentence type influence these patterns, and whether there is any evidence of change over time. Additionally, it will explore the extent to which patterns of variation among these multilingual practices exhibit similarities with each other, which can help to test the validity of sociolinguistic theories in East Asia.

I focus on Lánnang-uè, Colloquial Singapore English, Philippine English, and Hong Kong English using a sociolinguistic variationist framework. Data (e.g.,online and verbal communication data) tagged with social metadata (e.g., region, sex, age) collected from surveys or derived computationally will be collected, pre-processed, and added to existing databanks managed by me. Existing self-developed programs will be improved. Relationships between social and linguistic variables extracted from these databanks will be analyzed, and patterns within and between these Chinese-influenced varieties will be examined. The project will build on my previous (e.g., dissertation data) and ongoing work but also generate new insights that will broaden our understanding of the complex sociolinguistic realities of the East Asia.

The project aims to explore the multilingual and multicultural diversity of the region, focusing on the visible language in public spaces. The Greater Bay Area encompasses a significant economic hub in southern China, including Hong Kong, Macau, and several cities in Guangdong province. This project seeks to investigate the representation and use of different languages, scripts, and visual images in public spaces, such as streets, shops, and transportation hubs. By examining the linguistic landscape, this project aims to gain insights into the social, political, and cultural dynamics of the Greater Bay Area and contribute to a better understanding of the complex relationships between language and identity.

Our project examines the prevalence of code-mixing practices in Hong Kong through an under-researched digital medium. Prior research on code-alternation practices has often been limited to exploring either the social or linguistic constraints of code-switching in spoken or written communication. Our project takes a holistic approach to analyzing code-switching in a hybrid medium that exhibits features of both spoken and written discourse. The project shed some light on at least some of the locally embedded social meaning(s) of this linguistic practice in a digital context.

Most research on ‘Hong Kong English’ (HKE) in the past have implicitly framed HKE as a single monolithic variety – that is, they tend to characterize it as possessing a single set of distinctive features and patterns, used by Hong Kong residents of Cantonese heritage (Setter et al. 2010). While there have been some efforts to reverse this trend through the study of variation and change in HKE (Hansen Edwards 2018), little progress has been made, especially since the late 2010s. This makes it difficult to generalize on HKE. Not enough social and linguistic features have been investigated; we have also yet to know whether the trends observed in the past hold in other sets of data and other long-time residents of HK. The proposed study aims to fill these gaps by investigating variation and change in HK Englishes in-depth. This study diverges from existing studies because it is based on Computer-Mediated-Communication and “sociolinguistic interview” data from the 2020s (Schleef and Meyerhoff 2010); it highlights unexplored linguistic and social variables using a variationist, multiple Englishes or “internal differentiation” framework (Schneider 2003).

The study will draw on two complementary datasets: a 100-million-word sub-databank containing online communication data and a sub-databank of transcribed verbal communication data. The first will be compiled from public Tweets using an existing program I created (Gonzales 2021b) and anonymized WhatsApp messages collected manually with assistants. The second will be derived from the transcribed discussion and narrative recordings of 51 English-using residents of HK, stratified by region and ethnicity. Both sub-corpora will be tagged with social metadata using manual and computational methods, filtered, and coded for three linguistic features of interest: (1) the use of double tense markers (e.g., did + past-tense verb, e.g., did played) (Setter et al. 2010:48), (2) copula deletion (e.g., he __ handsome), and (3) clause-final adverbs (e.g., I go already.) (Hiramoto 2015). Then, I will analyze these in relation to five social variables: age (e.g., older vs. younger), gender, region (e.g., Hong Kong Island), ethnicity (e.g., Mainland Chinese, Cantonese), and year.

The results – tested with statistical modeling – will advance our current understanding of HKE past and present, promote the use of state-of-the-art methodologies from the field of data science and sociolinguistics in the field of world Englishes, and bring much-needed attention to peripheral groups in HK and how they and their use of English are intertwined with the cultural fabric of HK.