Interaction, as the central tenet in Human-Computer Interaction phenomenon, lends itself to considering those characteristics of technologies that humans can perceive and/or interact with directly. However, Griffith (1999) noted that deciphering technology features is ambiguous with multiple levels of granularity that can be further deconstructed. Deciding which granularity levels technological features should be considered at can be challenging to HCI scholars. This paper demonstrates how to apply extended Adaptive Structuration Theory (eAST) (Markus & Silver, 2008) to data collection and analysis in a way that can address phenomena at an appropriate level of technological abstraction. Our approach helps to provide researchers with clear guidance as to how to understand human interaction with technologies in such a way as to provide insight on information technology design. Such an illustration can be beneficial to HCI scholars because despite the popularity and wide application of AST and eAST, little research has demonstrated the direct application of these theories in guiding qualitative HCI work. This paper first establishes the importance of identifying the appropriate technological features when studying HCI. Then foundations of the extended AST (technical objects, functional affordances, and symbolic expressions) are explained with attention to how they can guide the identification of technological features at the appropriate granularity level. An example multi-case study is used to illustrate the applicability of eAST. Finally, some considerations for applying AST are summarized.



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