Article

Effectiveness of end-user debugging software features: are there gender issues?

Authors:

Laura Beckwith,

Margaret Burnett,

Susan Wiedenbeck,

Shraddha Sorte,

Michelle HastingsAuthors Info & Claims

CHI '05: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 869 - 878

https://doi.org/10.1145/1054972.1055094

Published: 02 April 2005 Publication History

Abstract

Although gender differences in a technological world are receiving significant research attention, much of the research and practice has aimed at how society and education can impact the successes and retention of female computer science professionals-but the possibility of gender issues within software has received almost no attention. If gender issues exist with some types of software features, it is possible that accommodating them by changing these features can increase effectiveness, but only if we know what these issues are. In this paper, we empirically investigate gender differences for end users in the context of debugging spreadsheets. Our results uncover significant gender differences in self-efficacy and feature acceptance, with females exhibiting lower self-efficacy and lower feature acceptance. The results also show that these differences can significantly reduce females' effectiveness.

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Effectiveness of end-user debugging software features: are there gender issues?

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cover image ACM Conferences

CHI '05: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

April 2005

928 pages

ISBN:1581139985

DOI:10.1145/1054972

Conference Chairs:
Wendy Kellogg
IBM T. J. Watson Research Center
,
Shumin Zhai
IBM Almaden Research Center
,
General Chair:
Gerrit van der Veer
Vrije Universiteit, The Netherlands
,
Program Chair:
Carolyn Gale
Stanford University, USA

Copyright © 2005 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 02 April 2005

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CHI '05 Paper Acceptance Rate 93 of 372 submissions, 25%;

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https://doi.org/10.1016/j.datak.2022.102108
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