New Experimental Findings in Chinese Linguistics
9:00 am (HKT)

Abstract:

We may be entering a new, golden age of Chinese linguistics research. Innovative technology, internet-based recruiting and testing, and a new generation of talented and rigorously trained researchers are changing the field for the better. Research in my lab aims to contribute to this ongoing paradigm shift by understanding the mechanisms and architecture underlying Chinese language acquisition and processing, and then applying this knowledge to develop real-world pedagogical innovations. In the first part of this talk, I will provide an overview of the lab’s recent work investigating adult second language acquisition of Mandarin Chinese. In the second part, I will describe an emerging line of research from the lab which explores how findings from cognitive science can be applied to language acquisition research. I will close by discussing future directions for the lab, as well as broader implications and best practices for the field.

 

Biography:

Seth Wiener is an Associate Professor of Second Language Acquisition and Chinese Studies and the Director of Graduate Studies in the Department of Modern Languages at Carnegie Mellon University. He is the Principal Investigator and director of the Language Acquisition, Processing, and Pedagogy Lab or LAPP Lab. LAPP Lab, which carries out experimental linguistics research, has been funded by the National Science Foundation, the National Institutes of Health, and the journal, Language Learning. Dr. Wiener received his BA from Boston University and his MA and PhD from The Ohio State University where he trained with Professors Marjorie Chan, Shari Speer, and Kiwako Ito. He is currently an Associate Editor for the journal, Applied Psycholinguistics, and an editorial board member for the journals Chinese as a Second Language, and Studies in Chinese Learning and Teaching.

 

When
Language
English
Speakers / Performers:
Dr. Seth WIENERS
Carnegie Mellon University
Organizer
Center for Chinese Linguistics
Contact

Meeting ID: 977 9745 3299

Passcode: 818134