Asynchronous multiple interpretation (AMI): Expanding temporal dimensions in qualitative data analysis

Abstract

This article introduces an analytical framework called ‘asynchronous multiple interpretation’ (AMI) that expands our understanding of temporal dimensions in qualitative data analysis. Inspired by Fanselow and Barnard’s ‘Take 1, Take 2, Take 3’ method, this approach involves multiple researchers examining the same dataset at different times, presenting their interpretations from their unique perspectives. The framework acknowledges and leverages the temporal aspects of research, including researchers’ distinct temporal-spatial circumstances, lived experiences, and data analysis engagement. This approach nurtures a more nuanced apprehension of qualitative data for both researchers and readers by underscoring the inherent variables and fluctuations in data interpretation over time. We applied this methodology to a case study in a ‘discussion and debate’ course at a Japanese university. Three researchers rendered individual interpretations of the data, resulting in more comprehensive discernment of the temporal layers influencing data interpretation. The findings accentuated the significance of temporal dimensions in research methodology and demonstrated the ways in which this approach can draw attention to the idiosyncratic nature of research findings. This study serves as an example of implementing AMI within language education research.