Identifying Categories of End Users Based on the Abstractions That They Create
Technical Report CMU-ISRI-05-110/CMU-HCII-05-101, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, 2005
KeyWords:end user programming,adoption,end users,end user software engineering,abstraction
Software created by end users often lacks key quality attributes that professional programmers try to ensure
through the use of abstraction. Yet to date, large-scale studies of end users have not examined end
user software usage at a level which is sufficiently fine-grained to determine the extent to which they create
To address this, we deployed an online survey to Information Week subscribers to ask about not only software
usage but also feature usage related to abstraction creation. Most respondents did create
abstractions. Moreover, through factor analysis, we found that features fell into three clusters?when users
had a propensity to use one feature, then they also had a propensity to use other features in the same cluster.
These clusters corresponded to macro features, linked data structure features, and imperative features.
For each of the three factors, we created a scale and used it to categorize users into two bins?those with a
high propensity to use features associated with that scale, and those with a low propensity. Compared to
users with a low propensity to use imperative features, users with a high propensity to use imperative features
were more likely to report testing and documenting. Propensity to use linked structure features was
less strongly related to these practices. These findings represent a step toward a more complete map of
end users? skills.
Preferred citation: C. Scaffidi, A. Ko, B. Myers, M. Shaw. Identifying Categories of End Users Based on the Abstractions That They Create, Technical Report CMU-ISRI-05-110/CMU-HCII-05-101, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, 2005
Entry last Updated 2006-06-26.
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