In our research, we investigate open-structured and narrative interview approaches for specifically accessing UX. These open-structured interview techniques are characterized by giving the interviewees the opportunity to extensively express their personal reflections and thoughts, providing valuable insights into the specific situation where an experience is encountered.

HCI and user experience (UX) research can rely on various techniques and methods from human and social sciences to collect interview data regarding peoples’ experiences of human-computer interactions. However, the knowledge about specific characteristics and the systematic use of these techniques for UX research is limited. Based on our approach on open-structured and narrative interview techniques, we conducted interview studies in different context like the automotive context and in production environments. Based on an initial theoretical framework, a classification of textual data specifically developed for accessing user experience (Meneweger et al., 2014), we recently set up an open-structured interview study in the factory context investigating operators’ experiences with industrial robots and the transition of working together with these robots. This provides us with knowledge to develop a framework for guiding the process of gathering appropriate qualitative interview data for accessing everyday experiences with technology.

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