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ESRC-DTP Knowledge Exchange Studentship (ESL research combining corpus and behavioural data)

Linguistics, Faculty of Modern & Medieval Languages

Applications are invited for a 1+3-year PhD studentship (MPhil + PhD) as part of the ESRC Doctoral Training Partnership at the University of Cambridge. This step will be important to train the student in the multidisciplinary methodologies and skills required to conduct this study. The project will be based in the Psycholinguistics lab in Linguistics under the supervision of Prof. Ianthi Tsimpli ( and also in Cambridge Assessment under the supervision of Dr Nick Saville

Brief project description: The proposed PhD project aims to investigate the developmental trajectory of English as a second language in instructed contexts. The aim is to focus on oral and reading comprehension of English by speakers of different L1s in order to identify the domains of the language which appear to stagnate or fail to correlate with the overall advancement in proficiency levels across L1s as well as the domains which are problematic for speakers of particular L1s. Psycholinguistic data from eye-tracking during reading or listening studies will be designed to test a group of adult L2 learners of English on the areas of difficulty identified in the corpus data.

To date, most research on second language acquisition is based on limited datasets coming from small groups of speakers with the same first language. This limitation in data power is a serious drawback in identifying the learning trajectory and the particular domains of English which are most problematic for L2 learners as the results mostly pertain to the particular group of participants with one or a small set of native languages. Cambridge Assessment English examines English proficiency in over 130 countries with around 5.5 million people taking these tests per year. Moreover, this dataset is drawn from participants speaking a variety of L1s whose English proficiency ranges from basic to highly advanced.  Thus, the research questions concerning areas of difficulty across L1s or from specific L1s can be addressed through a corpus analysis of a selected dataset where L1 and proficiency level can be used as independent variables. The eye-tracking data will allow us to focus on the identified areas of difficulty by isolating the relative contribution of lexical, morphological, syntactic and semantic complexities of the problematic domains, and will support generalizations from the corpus data and lead to a comprehensive theory of learning English as a second language.

Expressions of interest should be addressed to Prof. Ianthi Tsimpli,

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