Gender pluralism in problem-solving software

  • Authors:

  • Margaret M. Burnett;Laura Beckwith;Susan Wiedenbeck;Scott D. Fleming;Jill Cao;Thomas H. Park;Valentina Grigoreanu;Kyle Rector

  • Affiliations:

  • Oregon State University, 1148 Kelley Engineering Center, Corvallis, OR 97331, USA;Oregon State University, 1148 Kelley Engineering Center, Corvallis, OR 97331, USA and HCI Researcher, Sønder Boulevard 63, 4.th, 1720 Copenhagen, Denmark;Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USA;Oregon State University, 1148 Kelley Engineering Center, Corvallis, OR 97331, USA;Oregon State University, 1148 Kelley Engineering Center, Corvallis, OR 97331, USA;Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USA;Oregon State University, 1148 Kelley Engineering Center, Corvallis, OR 97331, USA and Microsoft, One Microsoft Way, Redmond, WA 98052, USA;Oregon State University, 1148 Kelley Engineering Center, Corvallis, OR 97331, USA and University of Washington, AC101 Paul G. Allen Center, Box 352350, 185 Stevens Way, Seattle, WA 98195, USA

  • Venue:
  • Interacting with Computers
  • Year:
  • 2011

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Abstract

Although there has been significant research into gender regarding educational and workplace practices, there has been little awareness of gender differences as they pertain to software tools, such as spreadsheet applications, that try to support end users in problem-solving tasks. Although such software tools are intended to be gender agnostic, we believe that closer examination of this premise is warranted. Therefore, in this paper, we report an end-to-end investigation into gender differences with spreadsheet software. Our results showed gender differences in feature usage, feature-related confidence, and tinkering (playful exploration) with features. Then, drawing implications from these results, we designed and implemented features for our spreadsheet prototype that took the gender differences into account. The results of an evaluation on this prototype showed improvements for both males and females, and also decreased gender differences in some outcome measures, such as confidence. These results are encouraging, but also open new questions for investigation. We also discuss how our results compare to generalization studies performed with a variety of other software platforms and populations.