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ceases to be relevant over prolonged use. Last, such approaches provide rather lim-
ited insight into the exact reasons for changes in users' experiences. They may, for
instance, reveal a shift in the dominance of perceived ease-of-use and perceived use-
fulness on intention to use a product (e.g. Venkatesh and Davis, 2000), but provide
limited insight to the exact experiences that contributed to such changes.
An alternative approach for the measurement of the dynamics of experience over
time relies on the elicitation of idiosyncratic self-reports of one's experiences with
a product, i.e. experience narratives . Each narrative provides rich insights into a
given experience and the context in which it takes place. Moreover, generalized
knowledge may also be gained from these experience narratives. Such generalized
knowledge may be reflected in questions like: how frequent is a certain kind of
experience, what is the ratio of positive versus negative experiences and how does
this compare to competitive products, how does the dominance of different product
qualities fluctuate over time and what should be improved to motivate prolonged
use?
This manuscript makes two methodological contributions in this research prob-
lem. First, it highlights the labor-intensive nature of longitudinal studies, and pro-
poses an alternative approach that relies on the elicitation of one's experiences with
a product from memory. iScale, a tool designed with the aim of increasing users'
effectiveness and reliability in recalling their experiences is theoretically grounded
and empirically validated. Second, it proposes a computational approach that aims
at supporting the researcher in the qualitative analysis of experience narratives.
The proposed approach addresses two limitations of traditional qualitative analy-
sis practices. First, qualitative analysis is a labor intensive activity which becomes
increasingly a concern when qualitative data may be elicited from a large num-
ber of participants as in the case of iScale. Second, qualitative analysis has been
shown to be prone to researcher bias as humans often rely on heuristics in forming
judgments about the relevance or similarity of two or more data instances (Kahne-
man et al., 1982). The proposed approach aims at supporting the researcher through
semi-automating the process of qualitative coding, but also minimizes the risks of
overemphasizing interesting, but rare experiences that do not represent users' typi-
cal reactions to a product.
1.5
Manuscript Outline
We argue for a hybrid paradigm between reductionist and holistic approaches to
evaluation. We propose two techniques, one grounded in personal attribute judg-
ments and one in experience narratives . Both developed techniques aim at increas-
ing the richness and diversity in obtained information while trying to create different
levels of granularity of insight, thus enabling the researcher to move between ab-
stracted, generalized insight and concrete, idiosyncratic and insightful information.
 
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