Xiaoyu Xu is an Assistant Professor in the Department of English at City University of Hong Kong. She holds a PhD in English and Languages (applied linguistics), a MA TESOL, a Bachelor’s major degree in Sociology and a Bachelor’s minor in Accounting and Finance. She has previously taught at Coventry University in the UK. Her interests include English for Academic Purposes, Corpus Linguistics, Systemic Functional Linguistics, Discourse Analysis and Intercultural Communication. She has a particular interest in using Corpus methods and Discourse Analysis to explore argumentation in all kinds of discourse. Her previous research focuses particularly on stance and evaluation in academic discourse from a cultural perspective, using Appraisal Theory and UAM CorpusTool. She intends to continue her research on academic discourse and also extend it to popularised science and media discourse, and explore computational linguistic methods.
How Do Novice Academics and Experienced Academics Interact with Audience in Computer Science Conference Discussion Sessions?
Conference discussion sessions can turn out to be a challenging encounter for academics as unpredictable comments or questions can leave the presenter underprepared. Speakers have to make situationally appropriate responses to defend their research, persuade the audience, and manage interpersonal relationships. This is even more difficult for novice researchers as they socialize into such academic discourse, particularly those who are EFL speakers, because of the scant attention given to this discourse and a shortage of pedagogical materials. This study therefore attempts to bridge the gap by investigating the verbal interactive repertoire needed (i.e., used by experienced academics) in computer science conference discussion sessions but unacquired by novice academics. The identified features can be implemented into instructional materials for computer science PhD students in order to help them understand the communicative context as well as develop the skills to professionally articulate contextually situated arguments, manage interpersonal relationship and be self-confident.
A Corpus-based Analysis of Engagement Language in Successful Engineering MOOC Lectures
This project is situated in the global trend of online lectures, namely Massive Open Online Course (MOOC) lectures. This fast-spreading online genre of lecture is currently under investigated despite being criticised by practitioners. They particularly point out the lack of engagement between lecturers and students, perhaps caused by teachers' lack of awareness of the necessity to adapt their traditional lecturing techniques for the online context. Hence, this project aims to discover engaging strategies used in successful MOOCs by analysing 12 MOOC lectures collected from two popular and highly rated engineering courses on Coursera. The transcripts will be annotated using ten types of engagement language features from Appraisal Theory (Martin & White, 2005) and Hyland's engagement scheme (2005). Text extracts with engagement features highlighted will be made available as an outcome of the project with an objective to increase effective use of engagement lecture language in engineering higher education.