Though benefits of Experience Sampling (ES) for experience design and research are apparent, the method has not been widely used in the field. As for the reasons, the following are prominent: 1) methodological issues as conventional ES obtains contextual experience information from the participants’ description of the context), and 2) a lack of theoretical framework enabling researchers to carry systematical analysis and extraction of meaningful experiences. In order to deal with these issues, the researchers have created an adapted ES model, named ‘Context-Specific Experience Sampling’, by which integration of a rigorous data collection and analysis processes is made possible. The model provides explanations of how to gather context-specific user experience information and extract key themes and attributes from the data pool. This approach, manifesting divergent-to-convergent features, is described as ‘experience pooling, sorting, and extracting’ which fall under the concept of ‘experience processing’. This paper details the structure and procedure of the model illustrating it with examples from a small scale lighting ambiance study of fashion stores.

This content is only available via PDF.
You do not currently have access to this content.