Development of different dimensions of L2 performance has been well-documented in the literature (Housen et al., 2012). Among these, L2 learners' performance considering lexical complexity, word choice and formulaicity might hugely differ in terms of the amount and type of exposure in a certain context. Operationalizing formulaicity as conventionalized ways of saying things, this study assumes that learning contexts are a crucial part of the picture as only some could provide a wealth of examples, such as the study abroad context.
The current study draws on the tenets of a dynamic usage-based approached to L2 development (Verspoor et al., 2021) in an attempt to understand the interplay between the study abroad context and lexical development. It aims to investigate the learning trajectories of a group of sojourners with regard to written lexical diversity, variation, sophistication, and formulaicity. A subgroup of (n = 26) Catalan/Spanish bilingual participants from the Study Abroad and Language Acquisition (SALA) project (Pérez-Vidal, 2014) volunteered to provide a weekly diary entry about their experiences related to language use, interaction, and host culture over the course of their semester abroad (12-17 weeks). The authors compiled the SALA diary corpus (a total of 383 weekly entries including around ~250K words) and analyzed this dataset in terms of lexical complexity via CLAN (MacWhinney, 2000) and TAALES (Kyle et al., 2018). To determine how formulaic each weekly entry is, the dataset is also analyzed through IdiomSearch (Colson, 2016). In response to the recent discussion around using indices that are not sensitive towards text length (Zenker & Kyle, 2021), the authors also coded and analyzed the written samples using indices sensitive to text length, such as like moving average TTR, hypergeometric distribution diversity index and the measure of textual lexical diversity (Zenker & Kyle, 2021). Following Verspoor et al. (2020), a series of generalized additive mixed modes was developed to examine the relationship between time, formulaicity, and lexical indices. The first results yielded a significant effect for random (participant behavior) and fixed factors (time) confirming the DUB argument for nonlinear and highly variable individual trajectories for lexical development, as well, significantly informing language classroom pedagogy.
Colson, J.-P. (2016). IDIOM search. http://idiomsearch.lsti.ucl.ac.be/index.html.
Housen, A., Kuiken, F., & Vedder, I. (Eds.). (2012). Dimensions of L2 performance and proficiency: Complexity, accuracy and fluency in SLA (Vol. 32). Amsterdam: John Benjamins Publishing.
Kyle, K., Crossley, S., & Berger, C. (2018). The tool for the automatic analysis of lexical sophistication (TAALES): version 2.0. Behavior research methods, 50(3), 1030-1046.
MacWhinney, B. (2000). The CHILDES project: Tools for analyzing talk. Mahwah, NJ: Lawrence Erlbaum Associates.
Pérez-Vidal, C. (2014). Language acquisition in study abroad and formal instruction contexts. Amsterdam: John Benjamins.
Verspoor, M., Lowie, W., & Wieling, M. (2021). L2 Developmental Measures from a Dynamic Perspective. In B. Le Bruyn & M. Paquot (Eds.), Learner Corpus Research Meets Second Language Acquisition (Cambridge Applied Linguistics, pp. 172-190). Cambridge: CUP. doi:10.1017/9781108674577.009
Zenker, F., & Kyle, K. (2021). Investigating minimum text lengths for lexical diversity indices. Assessing Writing, 47, 100505. https://doi.org/10.1016/j.asw.2020.100505
