This presentation describes the first stages of a 3-year collaborative research project aimed at integrating eye-tracking and corpus-based data in the development of phraseological complexity measures in the context of Italian L2 teaching.
The centrality of the phraseological dimension in second language learning has progressively gained recognition as a result of the increasingly numerous studies providing evidence in this respect. The two corpus-based measures of diversity (i.e. the range of phraseological units used in a text) and sophistication (i.e. how common a phraseological unit is) have been used to demonstrate how the phraseological dimension in produced language can be observed (Paquot, 2019). However, not only are corpus-based measures still too simple to account for phraseological complexity as a whole, but these seem to have been hardly ever integrated with other data sources in a systematic way (Durrant & Siyanova, 2015). In this presentation, we show how we hope to take this one step further. Our project aims to shed light on how different kinds of data are related in informing us on the dimension of phraseological complexity in second language learning. In particular, it aims to define a measure of phraseological complexity by integrating online (eye-tracking) and offline (corpus-based) data, and provide a computational validation for the measure. Furthermore, it wishes to apply the findings to the fields of syllabus and test design, with specific reference to Italian L2 teaching contexts. References Durrant, P., & Siyanova-Chanturia, A. (2015). Learner corpora and psycholinguistics. In S. Granger, G. Gilquin, & F. Meunier (Eds.), The Cambridge Handbook of Learner Corpus Research (pp. 57–78). Paquot, M. (2019). The phraseological dimension in interlanguage complexity research. Second Language Research, 35(1), 121–145.
