1. Introduction: Applying Complex Dynamic Systems Principles to Empirical Research on L2 Motivation

Abstract

When nonlinear system dynamics was introduced into second language acquisition (SLA) research – under various rubrics such as chaos theory (Larsen-Freeman, 1997), emergentism (Ellis & Larsen-Freeman, 2006), dynamic systems theory (de Bot et al., 2007) and complexity theory (Larsen-Freeman & Cameron, 2008) – the new approach, which may be seen as the ‘dynamic turn ’ in SLA, resonated with many scholars because nonlinear system dynamics appeared to nicely describe several puzzling language learning phenomena. To offer but one illustration, the so-called ‘butterfly effect ’ explained why language teaching input sometimes had considerable impact on the learners ’ progress, whereas at other times it led only to mini-mal, if any, uptake. The dynamic principles introduced also made intuitive sense research-wise. We have long known that the manifold issues and fac-tors affecting SLA are interrelated, and the new paradigm represented a holis-tic approach that took into account the combined and interactive operation of a number of different elements/conditions relevant to specific situations, rather than following the more traditional practice of examining the rela-tionship between well-defined variables in relative isolation. Thus, proposals for a dynamic paradigm shift in the research community during the first decade of the new millennium were generally well received. However, by the end of the 2010s it had become noticeable that while there was a growing body of literature on complex dynamic systems within SLA contexts, very little of this work was empirical in nature. In other words, scholars spent much more time talking about research in a dynamic systems vein than actually doing it. Furthermore, even when dynamic principles were 1 2822_Ch01.indd 1 20-08-2014 13:55:14 referred to in data-based studies, this was often to explain away difficult-to-interpret results, stating in effect that such results occurred because of the unpredictable or ‘emergentist ’ nature of the system. At the same time, in informal conversations at conferences, it was not at all uncommon to hear scholars privately express the sense of being at a loss as to how exactly to go about researching dynamic systems.

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