Skip to main content

Keynote speakers

plin |

Four experts will deliver keynote lectures on genre-related approaches:  

Mable Chan (Hong Kong Polytechnic University)

Mable ChanDr. Mable Chan is a Senior Lecturer at the Language Centre of Hong Kong Baptist University. Her main research and teaching interests include second language acquisition (SLA) at the interface with language education, and professional/workplace communication.  Dr. Chan has published widely in international journals and edited volumes and has authored and co-edited multiple books on SLA and business English. She has actively participated in the academic community, serving on several international conference committees and editorial boards of leading journals, demonstrating her passion and dedication to advancing knowledge in her fields of expertise. 

Genre based approaches to the teaching and learning of persuasive business discourse 

In this keynote speech, I will start by examining literature that utilizes genre-based approaches for analyzing persuasive business discourse, the key contributions and pedagogical implications. I will also present findings from my study, which investigates persuasive messaging in sales correspondence, invitations, and charity appeals through a genre-based framework. By employing Wmatrix, a corpus analysis tool, the research identifies persuasive strategies, namely logos, ethos, and pathos, and assesses their linguistic features across different text sections. The study uncovers unique structural patterns and linguistic characteristics specific to each message type. By analyzing sales letters, invitations, and charity requests, the research provides insights into persuasion mechanics and techniques for achieving it. The findings offer practical applications for educators developing business English materials intended for improving students’ persuasive skills in professional settings. Considering the influence of generative artificial intelligence (AI) on ESP/EAP pedagogy, the speech will conclude by proposing ways to incorporate AI into genre-based pedagogical practices in language classrooms. 

Bethany Gray (Iowa State University)

Bethany GrayBethany Gray is Professor of Applied Linguistics and Technology in the Department of English at Iowa State University. Her research employs corpus linguistics methodologies to explore register variation, with a focus on academic language, disciplinary variation, L1 and L2 writing development, and grammatical complexity. Her publications include monographs on academic research articles (2015, John Benjamins), historical change in writing (2016, Cambridge University Press), corpus design and representativeness (2022, Cambridge University Press), and the register-functional approach to grammatical complexity (2022, Routledge). She is a co-founding editor of the journal Register Studies, which has published empirical and theoretical research on register since its inaugural issue in 2019. Her work has appeared in journals such as Applied Linguistics, TESOL Quarterly,  International Journal of Corpus Linguistics, Journal of English for Academic Purposes, English for Specific Purposes, and Written Communication, among others. 

Introduction to genre and register studies

Charlene Polio (Michigan State University)

Charlene PolioCharlene Polio is a Professor and Interim Chair in the Department of Linguistics, Languages, and Cultures at Michigan State University, where she teaches in the TESOL and Second Language Studies programs. She is the current co-editor of TESOL Quarterly and a consulting editor for Research Methods in Applied Linguistics. Her research focuses on second language writing - particularly in terms of how it is related to language development - and the research methods used to study second language writing. Her current work focuses on analyses of published empirical studies showing how a better understanding of these research articles helps us teach academic writing across multiple paradigms and disciplines. 

Promoting genre awareness with diverse student groups

With an emphasis on genre-based approaches to teaching writing, some instructors aim to teach genre-specific knowledge for academic, non-academic, and multimodal writing. While such an approach can be appropriate and effective, it can be restrictive and challenging with heterogeneous student populations. Using Tardy et. al.’s (2020) framework of genre knowledge, I will suggest prioritizing genre awareness over genre-specific knowledge. I will provide examples from a range of context. First, I will show examples of mini-projects that can be completed by preservice teachers so that they better understand genre and genre-based instruction. Second, I will show activities for raising genre awareness with low-level learners. The third and largest portion of the talk will focus on academic writing and genre awareness. In this section of the talk, I will discuss research on academic writing (including my own, Gao, Pham, & Polio, 2022, 2023, in press) that shows why genre-specific focused instruction can be problematic. I will present activities for raising genre awareness in heterogeneous academic writing classes and in general academic classes that include both first and second language writers. Throughout the talk, I show how rhetorical move, corpus-based, and multimodal analyses, as well as rhetorical genre theory and AI, can be used by students to explore genre. 

Serge Sharoff (University of Leeds)

Serge Sharoff is Professor of Language Technology at the University of Leeds. Artificial Intelligence and Large Language Models have recently made a profound impact on how we interact with computers. He has been doing fundamental research in this area since his own PhD in the 1990s on a language model for Information Extraction.  The application domains for this kind of research in the Digital Humanities include text annotation, information retrieval, machine translation and computer-assisted language learning.  His research stresses the inherent multilingualism of NLP, which implies that tools and resources can be ported across languages.  With rise of LLMs, one of the important areas of his work concerns explainability of their operations to ensure that they make right predictions for the right reasons.

On automatic genre classification: Why linguists have job security

The rise of Large Language Models has led to the perception that many traditional problems in computational linguistics have been solved. However, linguistic knowledge remains crucial for  "saying sensible and  useful things about any text" (Halliday, 1985). In this talk, I will explore the continued relevance of linguistic analysis in the age of LLMs, focusing on three key aspects: (1) identifying the genres of texts used to train LLMs, (2) detecting the registerial features associated with these genres, and (3) analyzing discourse constructions relevant to them.