Ironically, individual differences (ID) research in SLA often refers to differences within a sample, not an individual. Complex dynamic systems theory (CDST) re-imagines the meaning of individual differences in ways that complement, supplement, and challenge traditional approaches to ID variables. Specific empirical investigations in WTC, motivation, and emotion will serve as examples of intra-individual research.
Individual differences (ID) research in SLA often refers to differences across individuals with a sample. In general, the ID approach attempts to account for why some people score high and others low on a specific attribute, such as anxiety, enjoyment, motivation, or willingness to communicate. Often, ID research uses correlations to argue that theoretical explanations for IDs have (or lack) empirical support. However, the emergence of complex dynamic systems thinking in SLA offers an opportunity to re-imagine the meaning of individual differences, not only across people but also within person. SLA provides a rich context for studying dynamics with its focus on both change and stability in language development. However, it is not just language competences that are in a state of flux, but a range of related factors during these processes that are constantly interacting with learner and teacher psychologies. This makes the psychology of language learning an especially fertile ground for dynamic studies to take root. Within applied linguistics, theorizing complexity is well ahead of its empirical investigations. Adopting a dynamic approach to ID research requires new approaches not only to conceptualizing IDs, but also in methodology and data analysis/presentation. the possibilities for future research excite the imagination. The question now is how to proceed with research that will further our appreciation of the scope and potential of this theoretical framework to extend our understandings of the field of language learning and teaching. This presentation will focus on the ways in which intra-individual variability, conceptualized and empirically studied from a complex dynamic perspective complements, supplements, and challenges traditional approaches to ID variables. Specific empirical investigations of emotions, motivation and willingness to communicate will serve as illustrative examples.
