CONTEXT-SPECIFIC EXPERIENCE SAMPLING FOR EXPERIENCE DESIGN RESEARCH

Despite apparent benefits of Experience Sampling (ES) for experience design and research, it has been scarcely used in the field. Among the reasons for that are some methodological issues such as the way in which conventional ES gathers contextual experience information directly from the participants’ description of the context and the lack of theoretical framework enabling researchers to systematically explore and extract meaningful experiences. To address these issues, the researchers have developed an adapted ES model, entitled ‘Context-Specific Experience Sampling’ which integrates a rigorous data collection and analysis processes. The model explains how to gather context-specific user experience information and then extract key experience attributes from the data pool through. This divergent-to-convergent approach is described ‘experience pooling, sorting, and extracting’ under the theme of experience processing. This paper explains in detail the structure and procedure of the model with examples obtained from a small scale office environment research.