A Complex Dynamic Systems Theory perspective on speaking in second language development

L2 speaking is a challenging area of research due to the wide variety of relevant factors that shape the process in different ways and at different timescales. This chapter provides insights into the development of second language speaking from a Complex Dynamic Systems Theory perspective. This chapter sketches the dynamic nature of the developmental process and discusses methodological issues in analyzing data from this perspective leading to several recommendations about doing research into L2 speaking. One of the most important conclusions is that the process of L2 speaking is essentially individually owned and that most insight into this process can be expected from longitudinal case studies with dense data collected at a high frequency

L2 developmental measures from a dynamic perspective

An important objective of research in Second Language Acquisition has been to find a simple and reliable way to quantify second language use. Corpora have provided a crucial source of information for these studies. In spite of many attempts to determine an optimal “yardstick” to measure the quality of second language use, particularly lexical complexity and syntactic complexity, a reliable and widely applicable instrument has not yet been determined. The difficulty in finding a suitable instrument can be accounted for in a complex dynamic systems theory (CDST) approach to second language development. An important starting point of this approach is that every next step in time “is the emergent product of context and history, and no component has causal priority” (Thelen 2005, p. 271). In this paper we illustrate this by using a dense longitudinal corpus of the development of 22 highly similar L2 learners, consisting of 23 weekly measurements. The analysis of these data show convincingly that L2 development is a highly individually owned and nonlinear process. While complexity yardsticks (like MLTU and Guiraud) may seem functional from a group perspective, their application to individual learners is very limited

Variability as predictor in L2 writing proficiency

Lowie and Verspoor (2019) had an unexpected finding in their work Individual Differences and the Ergodicity Problem: The main predictor for proficiency gains in 22 beginning Dutch learners of English over one year was not traditional individual difference (ID) factors, but the degree of variability that occurred over time. We speculate that variability might stand for “investment” as students might strive for an excellent product at one time, but are not able to reach quite the same level the next time. The current paper sets out to see whether the findings can be replicated with a different population and finer-tuned measures. The English writing proficiency of 22 L1 Chinese adults at the university level was measured with 12 texts scored holistically over one academic year. The degree of variability in L2 writing was operationalized as the coefficient of variation (CoV), which was calculated as the standard deviation divided by the mean of the L2 writing holistic scores. ID factors measured were motivation, language aptitude, and working memory. The findings were as follows: None of the ID factors predicted the final L2 writing proficiency nor the L2 writing proficiency gains, but the CoV did. The implications of these findings are discussed