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Gender differences and programming environments: across programming populations

Authors:

Margaret Burnett,

Scott D. Fleming,

Valentina Grigoreanu,

Mary CzerwinskiAuthors Info & Claims

ESEM '10: Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement

Article No.: 28, Pages 1 - 10

https://doi.org/10.1145/1852786.1852824

Published: 16 September 2010 Publication History

Abstract

Although there has been significant research into gender regarding educational and workplace practices, there has been little investigation of gender differences pertaining to problem solving with programming tools and environments. As a result, there is little evidence as to what role gender plays in programming tools---and what little evidence there is has involved mainly novice and end-user programmers in academic studies. This paper therefore investigates how widespread such phenomena are in industrial programming situations, considering three disparate programming populations involving almost 3000 people and three different programming platforms in industry. To accomplish this, we analyzed four industry "legacy" studies from a gender perspective, triangulating results against each other and against a new fifth study, also in industry. We investigated gender differences in software feature usage and in tinkering/exploring software features. Furthermore, we examined how such differences tied to confidence. Our results showed significant gender differences in all three factors---across all populations and platforms.

References

[1]

Bandura, A. Social Foundations of Thought and Action. Prentice Hall, Englewood Cliffs, NJ, USA, 1986.

[2]

Bardzell, S. Feminist HCI: Taking stock and outlining an agenda for design, In Proc. ACM Conference on Human Factors in Computing Systems, ACM (2010), 1301--1310.

Digital Library

[3]

Beckwith, L. and Burnett, M., Gender: An important factor in end-user programming environments? In Proc. IEEE Symposium on Visual Languages and Human-Centric Computing, IEEE (2004), 107--114.

Digital Library

[4]

Beckwith, L., Burnett, M., Wiedenbeck, S., Cook, C., Sorte, S., and Hastings, M. Effectiveness of end-user debugging software features: Are there gender issues? In Proc. ACM Conference on Human Factors in Computing Systems, ACM (2005). 869--878.

Digital Library

[5]

Beckwith, L., Kissinger, C., Burnett, M., Wiedenbeck, S., Lawrance, J., Blackwell, A., and Cook, C., Tinkering and gender in end-user programmers' debugging, In Proc. ACM Conference on Human Factors in Computing Systems, ACM (2006), 231--240.

Digital Library

[6]

Beckwith, L., Inman, D., Rector, K., and Burnett, M. On to the real world: Gender and self-efficacy in Excel, In Proc. IEEE Symposium on Visual Languages and Human-Centric Computing, IEEE (2007), 119--126.

Digital Library

[7]

Berenson, S., Slaten, K., Williams, L., and Ho, C.-W. Voices of women in a software engineering course: Reflections on collaboration. J. Educ. Resour. Comput. 4, 1 (2004).

Digital Library

[8]

Busch, T. Gender differences in self-efficacy and attitudes toward computers. J. Educ. Comput. Research 12, (1995).

[9]

Compeau, D., Higgins, C. Computer self-efficacy: Development of a measure and initial test. MIS Quarterly 19, 2 (1995).

Digital Library

[10]

Conover, W. J. and Iman, R. L. Rank transformations as a bridge between parametric and nonparametric statistics. The American Statistician 35, 3 (1981), 124--129.

[11]

Fennema, E., Carpenter, T., Jacobs, V., Franke, L., Levi. L. A longitudinal study of gender differences in young children's mathematical thinking. Educational Researcher 27, 5 (1998).

[12]

Gallagher, A. M., De Lisi, R. Gender differences in scholastic aptitude-test mathematics problem-solving among high-ability students. J. Educational Psychology 8, 2 (1994), 204--211.

[13]

Grigoreanu, V., Cao, J., Kulesza, T., Bogart, C., Rector, K., Burnett, M., and Wiedenbeck, S. Can feature design reduce the gender gap in end-user software development environments? In Proc. IEEE Symposium on Visual Languages and Human-Centric Computing, IEEE (2008), 149--156.

Digital Library

[14]

Hartzel, K. How self-efficacy and gender issues affect software adoption and use. Comm. ACM 46, 9 (2003), 167--171.

Digital Library

[15]

Kaye, J. Some statistical analyses of CHI. In Proc. ACM Conference on Human Factors in Computing Systems, Extended Abstracts, ACM (2009), 2585--2594.

Digital Library

[16]

Kelleher, C., Pausch. R., and Kiesler, S. Storytelling Alice motivates middle school girls to learn computer programming, In Proc. ACM Conference on Human Factors in Computing Systems, ACM (2007), 1455--1464.

Digital Library

[17]

Lawton, C. Gender differences in way-finding strategies: Relationship to spatial ability and spatial anxiety. Sex Roles Journal 30, 11--12 (1994), 765--779.

[18]

Ljungblad, S. and Holmquist, L. Transfer scenarios: Grounding innovation with marginal practices, In Proc. ACM Conference on Human Factors in Computing Systems, ACM (2007), 737--746.

Digital Library

[19]

Margolis, J. and Fisher, A. Unlocking the Clubhouse, MIT Press, Cambridge, MA, USA, 2003.

[20]

McDowell, C., Werner, L., Bullock, H. E., Fernald, J. The impact of pair programming on student performance, perception and persistence, In Proc. International Conference on Software Engineering, ACM (2003), 602--607.

Digital Library

[21]

Meyers-Levy, J. Gender differences in information processing: A selectivity interpretation. In P. Cafferata & A. Tybout (Eds) Cognitive and Affective Responses to Advertising. Lexington Books, Lexington, MA, USA, 1989.

[22]

O'Donnell, E., Johnson, E. Gender effects on processing effort during analytical procedures. Int. J. Auditing 5, 2001, 91--105.

[23]

Powell M. and Ansic D. Gender differences in risk behavior in financial decision-making: An experimental analysis, J. Economic Psychology 18, 6 (1997), 605--628.

[24]

Rode, J. An ethnographic examination of the relationship of gender & end-user programming, Ph.D. Thesis, Univ. Calif., 2008.

Digital Library

[25]

Rosson, M. B., Sinha, H., Bhattacharya, M., and Zhao, D. Design planning in end-user web development, In Proc. IEEE Symposium on Visual Languages and Human-Centric Computing, IEEE (2007), 189--196.

Digital Library

[26]

Sheskin, D. J. Handbook of Parametric and Nonparametric Statistical Procedures. Chapman & Hall/CRC, 2007.

Digital Library

[27]

Simon, S. The impact of culture and gender on web sites: An empirical study. The Data Base for Advances in Information Systems 32, 1 (2001), 18--37.

Digital Library

[28]

Subrahmaniyan, N., Beckwith, L., Grigoreanu, V., Burnett, M., Wiedenbeck, S., Narayanan, V., Bucht, K., Drummond, R., and Fern, X. Testing vs. code inspection vs. what else? Male and female end users' debugging strategies. In Proc. ACM Conference on Human Factors in Computing Systems, ACM (2008), 617--626.

Digital Library

[29]

Tan, D., Czerwinski, M. and Robertson, G. Women go with the (optical) flow, In Proc. ACM Conference on Human Factors in Computing Systems, ACM (2003), 209--215.

Digital Library

[30]

Torkzadeh, G. and X. Koufteros. Factorial validity of a computer self-efficacy scale and the impact of computer training. Educational and Psychological Measurement 54, 3 (1994).

[31]

Wohlin, C., Runeson, P., Höst, M., Ohlsson, M. C., Regnell, B., and Wesslén, A. Experimentation in Software Engineering: An Introduction. Kluwer, 2000.

Digital Library

[32]

Yin, R. Case Study Methodology (3rd edition), Sage, 2003.

Cited By

Santos IFelizardo KSteinmacher IGerosa M(2025)Software solutions for newcomers’ onboarding in software projects: A systematic literature reviewInformation and Software Technology10.1016/j.infsof.2024.107568177(107568)Online publication date: Jan-2025
https://doi.org/10.1016/j.infsof.2024.107568
Newendorp AGilbert S(2024)Gender-Related Preferences for Learning by Tinkering: Updated Research is NeededProceedings of the Human Factors and Ergonomics Society Annual Meeting10.1177/10711813241272118Online publication date: 24-Oct-2024
https://doi.org/10.1177/10711813241272118
Anderson AGuevara JMoussaoui FLi TVorvoreanu MBurnett M(2024)Measuring User Experience Inclusivity in Human-AI Interaction via Five User Problem-Solving StylesACM Transactions on Interactive Intelligent Systems10.1145/366374014:3(1-90)Online publication date: 24-Sep-2024
https://dl.acm.org/doi/10.1145/3663740
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Index Terms

Gender differences and programming environments: across programming populations
1. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Conferences

ESEM '10: Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement

September 2010

423 pages

ISBN:9781450300391

DOI:10.1145/1852786

General Chair:
Giancarlo Succi
Free University of Bolzano, Italy
,
Program Chairs:
Maurizio Morisio
Politecnico di Torino, Italy
,
Nachi Nagappan
Microsoft Research

Copyright © 2010 ACM.

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Published: 16 September 2010

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National Science Foundation

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ESEM '10

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SIGSOFT

ESEM '10: 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement

September 16 - 17, 2010

Bolzano-Bozen, Italy

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ESEM '10 Paper Acceptance Rate 30 of 102 submissions, 29%;

Overall Acceptance Rate 130 of 594 submissions, 22%

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https://doi.org/10.1016/j.infsof.2024.107568
Newendorp AGilbert S(2024)Gender-Related Preferences for Learning by Tinkering: Updated Research is NeededProceedings of the Human Factors and Ergonomics Society Annual Meeting10.1177/10711813241272118Online publication date: 24-Oct-2024
https://doi.org/10.1177/10711813241272118
Anderson AGuevara JMoussaoui FLi TVorvoreanu MBurnett M(2024)Measuring User Experience Inclusivity in Human-AI Interaction via Five User Problem-Solving StylesACM Transactions on Interactive Intelligent Systems10.1145/366374014:3(1-90)Online publication date: 24-Sep-2024
https://dl.acm.org/doi/10.1145/3663740
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