Next CLLEAR seminar: Beyond Borders, Beyond Words: Issues & Challenges in Developing An Open-Access Multimodal Corpus of L2 Academic English from A Sino-British University

CLLEAR

The next Centre for Linguistics, Language Education and Acquisition Research (CLLEAR) seminar will take place on Thursday 25th January 2018 at 16:00 in Room 1173, Building 65, Avenue Campus. The talk is entitled “Beyond Borders, Beyond Words: Issues & Challenges in Developing An Open-Access Multimodal Corpus of L2 Academic English from A Sino-British University” and will be delivered by Dr. Yu-Hua Chen from the University of Nottingham, Ningbo Campus. All welcome for the seminar and discussion!

Here is the abstract for this seminar:

The Corpus of UNNC Chinese Academic Written and Spoken English (UNNC CAWSE) is an ongoing project which aims to build a large collection of Chinese students’ English language samples from one of the few English-medium instruction (EMI) universities in China. The campus creates a unique environment for teaching and learning and also provides exciting opportunities for linguistic studies into Academic English from diverse theoretical and analytical perspectives. The project collects students’ language samples from a variety of assessment tasks (both written and spoken) and speech events (spoken and multi-modal) from the preliminary-year programme at UNNC. The final product of UNNC CAWSE will offer open-access electronic resources (including a multi-modal subcorpus) available for researchers and practitioners who are interested in a wide range of topics, including for example Second Language Acquisition (SLA), English for Academic Purposes (EAP), English as a Lingual Franca (ELF)/World Englishes, and many other aspects of the Written and Spoken English unique to this new corpus.

This talk will first introduce this unique UNNC CAWSE corpus including its design and construction process. Then various challenges and issues arising from using innovative approaches in constructing an L2 multimodal corpus will be described and discussed. Based on our current data transcription and annotation, some preliminary findings which share certain characteristics with ELF will also be presented.

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