Indexicality, situated cognition, and heritage language socialisation: A linguistic ethnography
The growing segment of immigrant-origin children in contemporary societies has led to increased scholarly interest in heritage language (HL) learning. While existing research emphasises that HL and identity are mutually constitutive, such claims are mainly supported by macro-sociological studies focusing on motivation, ethnicity, and habitus. The challenge remains one of elucidating the HL-identity link from a micro-sociolinguistic and developmental perspective. We therefore have a relatively poor understanding of how HL learners are socialised into ways of speaking and acting, and how HL practices reflect the everyday experience and organisation of the HL community contextually.
My project will thus draw on the language socialisation framework to explore the socially situated nature of HL development and its symbiotic relationship with identity formation. Specifically, the project will look at how British Chinese adolescents from two differentially positioned Chinese community schools acquire, negotiate, and enact the indexical meanings of their HL both within and outside HL classrooms.
This presentation will provide an overview of the proposed study. I will first discuss the sociolinguistic dynamics within the Chinese diaspora community. I will then argue how indexicality can serve as an important lens for understanding HL socialisation, before outlining the preliminary research design of the study.
Linguistic complexity in second language learning
Dora Alexopoulou (joint work with Akira Murakami Tuebingen/Birmingham)
Linguistic complexity has long been considered a measure of development and proficiency in second language learning and shown to be directly influenced by the cognitive complexity of task prompts in instructed contexts. Recent advances in online language learning have opened new opportunities for the study of lingusitic complexity as they can provide SLA researchers with unprecedented amounts of data. The EF Cambridge Language Database (EFCAMDAT) built in Cambridge in collaboration with an international school of English, Education First, is an example in point. EFCAMDAT consists of writing submitted to the online school of EF. It stands out for its size (1.2 million scripts), the diversity of learner backgrounds as data are collected from around the globe, and the variety of its 128 distinct writing topics spreading across the proficiency spectrum.
Using EFCAMDAT as the empirical basis of our research, in this talk, we focus on the impact of the native language (L1) on L2 complexity. Our empirical goal is to investigate the impact of L1 on different measures of linguistic complexity and compare it with known L1 effects on accuracy. Our theoretical goal is to extend current notions of linguistic complexity within the framework of Complexity, Accuracy and Fluency (CAF) with a notion of L1-based representational complexity that stems from generative and formal approaches to linguistic knowledge. To evaluate the robustness of our empirical results we compare writings in two learner corpora, EFCAMDAT and the International Corpus of Learner English.