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Dimensions Characterizing Programming Feature Usage by Information Workers

Chris Scaffidi, Andrew Ko, Brad Myers, and Mary Shaw
VL/HCC"06: Proceedings of the 2006 IEEE Symposium on Visual Languages and Human-Centric Computing, pp. 59-62, 2006.

KeyWords:adoption,end user programming,end user software engineering,end users,abstraction

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Abstract:

Information workers such as administrative staff, consultants, and their managers constitute one of the largest groups of end users, yet little research about their usage of programming features is available to guide development of end user programming tools. In this paper, we describe our survey of over 800 information workers and our analysis of their feature usage in applications such as spreadsheets, browsers, and databases. Our factor analysis reveals three clusters of features?macro features, linked structure features, and imperative features?such that information workers with an inclination to use a feature in each cluster also were inclined to use other features in that cluster, even though each cluster spans several applications. We discuss the implications for research aimed at providing end user programming tools for information workers.

Preferred citation: C. Scaffidi, A. Ko, B. Myers, M. Shaw. Dimensions Characterizing Programming Feature Usage by Information Workers. VL/HCC"06: Proceedings of the 2006 IEEE Symposium on Visual Languages and Human-Centric Computing, pp. 59-62, 2006.

Entry last Updated 2006-10-11.
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