Quantifying diversity in user experience

E. Karapanos

    Research output: ThesisPhd Thesis 1 (Research TU/e / Graduation TU/e)

    534 Downloads (Pure)

    Abstract

    Evaluation should be integral to any design activity. Evaluation in innovative product development practices however is highly complicated. It often needs to be applied to immature prototypes, while at the same time users’ responses may greatly vary across different individuals and situations. This thesis has focused on methods and tools for inquiring into users’ experiences with interactive products. More specifically, it had three objectives: a) to conceptualize the notion of diversity in subjective judgments of users’ experiences with interactive products, b) to establish empirical evidence for the prevalence of diversity, and c) to provide a number of methodological tools for the study of diversity in the context of product development. Two critical sources of diversity in the context of users’ experiences with interactive products were identified and respective methodological solutions were proposed: a) understanding interpersonal diversity through personal attribute judgments, and b) understanding the dynamics of experience through experience narratives. Personal Attribute Judgments, and in particular, the Repertory Grid Technique, is proposed as an alternative to standardized psychometric scales, in measuring users’ responses to artifacts in the context of parallel design. It is argued that traditional approaches that rely on the a-priori definition of the measures by the researchers have at least two limitations. First, such approaches are inherently limited as researchers might fail to consider a given dimension as relevant for the given product and context, or they might simply lack validated measurement scales for a relevant dimension. Secondly, such approaches assume that participants are able to interpret and position a given statement that is defined by the researcher to their own context. Recent literature has challenged this assumption, suggesting that in certain cases participants are unable to interpret the personal relevance of the statement in their own context, and might instead employ shallow processing, that is respond to surface features of the language rather than attaching personal relevance to the question. In contrast, personal attributes are elicited from each individual respondent, instead of being a-priori imposed by the experimenter, and thus are supposed to be highly relevant to the individual. However, personal attributes require substantially more complex quantitative analysis procedures. It is illustrated that traditional analysis procedures fail to bring out the richness of the personal attribute judgments and two new Multi-Dimensional Scaling procedures that extract multiple complementary views from such datasets are proposed. An alternative approach for the measurement of the dynamics of experience over time is proposed that relies on a) the retrospective elicitation of idiosyncratic selfreports of one’s experiences with a product, the so-called experience narratives, and b) the extraction of generalized knowledge from these narratives through computational content analysis techniques. iScale, a tool that aims at increasing users’ accuracy and effectiveness in recalling their experiences with a product is proposed. iScale uses sketching in imposing a structured process in the reconstruction of one’s experiences from memory. Two different versions of iScale, each grounded in a distinct theory of how people reconstruct emotional experiences from memory, were developed and empirically tested. A computational approach for the extraction of generalized knowledge from experience narratives, that combines traditional coding procedures with computational approaches for assessing the semantic similarity between documents, is proposed and compared with traditional content analysis. Through these two methodological contributions, this thesis argues against averaging in the subjective evaluation of interactive products. It proposes the development of interactive tools that can assist designers in moving across multiple levels of abstractions of empirical data, as design-relevant knowledge might be found on all these levels.
    Original languageEnglish
    QualificationDoctor of Philosophy
    Awarding Institution
    • Industrial Design
    Supervisors/Advisors
    • Martens, J.B.O.S. (Jean-Bernard), Promotor
    • Brombacher, Aarnout C., Promotor
    Award date23 Mar 2010
    Place of PublicationEindhoven
    Publisher
    Print ISBNs978-90-386-2183-8
    DOIs
    Publication statusPublished - 2010

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