Gender HCI

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Gender HCI is a branch of human-computer interaction that focuses on the design and evaluation of interactive systems for people. The particular focus of Gender HCI is on variations in the way people of different sexes interact with computers .

example

Gender HCI research was carried out in the following areas, among others

  • Prejudices in the perception of gender-specific computerized partners
  • The effects of trust and self-efficacy on interactions of both sexes with software.
  • The design of gender-specific software, such as video games designed for women.

Overview

Gender HCI examines how properties of software (or hardware) can interact with gender differences. As with all HCIs, Gender HCI is a strongly interdisciplinary area. Findings from areas such as psychology , computer science , marketing , neuroscience , education and economics suggest that men and women solve problems, communicate and process information differently. Gender HCI examines whether these differences need to be taken into account when designing software and hardware.

history

The term Gender HCI was coined in 2004 by Laura Beckwith, a PhD student at Oregon State University , and her advisor Margaret Burnett. They found that while there were some activities that could be characterized as gender HCI work, people were unaware of the work of the others. The relevant research reports were isolated and scattered across different areas. Since then, she and others have worked to help researchers know about each other's work and to help practitioners become aware of the results so that this area could mature as a part of the HCI.

A short series of milestones follows in the history of this emerging branch.

  • 1987: Games designed to be "gender neutral" look like games designed for boys. (Chuck Huff).
  • 1989: Ethnographic research on women, programming and computers ( Sherry Turkle ).
  • 1995: Gender-specific differences in self-efficacy and attitudes towards computers (Tor Busch).
  • 1998: Gender Factors in Video Game Design (Justine Cassell).
  • 2002: Wider screens are more beneficial for all users, especially women (Mary Czerwinski, Desney S. Tan, George G. Robertson).
  • 2004: The gender HCI concept made explicit (Laura Beckwith, Margaret Burnett).
  • 2006: A research workshop on Gender HCI.

Selected findings

Here are some results from previous Gender HCI research - sorted by newest to least recent, by category:

  1. "Reward Expectations in Gender-Based Computers" - In one experiment, subjects worked on a task with a computerized partner named James or Julie. The task was gender neutral, meaning it was not directly relevant to being a man or a woman. The results showed that the test subjects behaved the same way towards a computer named James or Julie. Despite these similarities in behavior, the test subjects estimated that a computer named James would cost them significantly more than a computer named Julie. The results show that users' perception of computers is gender-specific and that they lack the human characteristics that define gender.
  2. Trust related results. - For spreadsheet problem-solving tasks , (1) female end-users had significantly less self-efficacy than males, and (2) women with low self-efficacy were significantly less likely to work effectively with the problem-solving features available in the software. In contrast, men's self-efficacy did not affect their effectiveness with these functions. - In a study of computer settings and self-efficacy in 147 college students, there were gender differences in self-efficacy for complex tasks (such as word processing and spreadsheet software) but not for simpler tasks. The male students were also more experienced in using computers and reported more encouragement from parents and friends.
  3. Results related to software features. - For spreadsheet problem-solving tasks, female end-users were significantly slower at trying unknown functions. Women were significantly more likely to agree with the statement: "I was afraid that it would take me too long to learn the [unskilled function]". Even when they tried it once, women were significantly less likely to take on new functions for repeated use. In contrast to men, self-efficacy in women predicted the extent of the effective use of traits. There was no significant difference in the success of either sex or in learning how the traits worked, implying that women's low self-efficacy in using new traits was not an accurate assessment of their problem-solving potential, but rather became a self-fulfilling prophecy.
  4. Behavioral findings. - For problem-solving spreadsheets, tinkering (playful experimentation) with characteristics was more often done by men than women. While the men were comfortable with this behavior, some did it too much. For women, the amount of crafting predicted success. Pauses after each action were a sign of better understanding for both sexes. - Men saw machines as a challenge, something to be mastered, overcome and measured against. They were willing to take risks, and they demonstrated it by eagerly trying new techniques and approaches. The women rejected the image of the male hacker as alienating and depersonalizing. Her handling of computers was "soft", tactile, artistic and communicative.
  5. Hardware interface results. - Larger displays helped narrow the gender gap when navigating virtual environments. On smaller screens, men performed better than women. With larger screens, women's performance improved, while men's performance was not adversely affected.
  6. Video game results. - Several findings on girls' interests in video games have been reported, with interpretations for the video game software industry. - Several researchers looked at what girls look for in video games and what impact this has on video game designers. The implications included collaboration vs. Competitive Preferences and the Use of Nonviolent Rewards vs. Death and destruction as a reward. These papers discuss both sides of the question of whether or not games should be designed specifically for girls.
  7. Other related findings on gender and computers. - In a study of the way people interacted with conversational software agents in terms of the agent's gender, the female virtual agent received much more violent and sexual advances than the male or the sexless (a robot). - In the household, where many devices are programmable to a certain extent, it was found that different device categories are more likely to be programmed by men (e.g. entertainment devices) and women (e.g. kitchen devices). Often a member of a household takes responsibility for programming a particular device, with housekeeping doing this job. - Men and women had different views on whether a website would be suitable for their home country, and women were more likely than men to prefer more information on all websites viewed during a study. - Women who embarked on a career in mathematics, science, and technology had high academic and social self-efficacy. Their self-efficacy was based on vicarious experiences and the verbal persuasiveness of significant people around them. - Factors affecting women's low loyalty to college computer science programs included women's lower level of computer science experience than men, low self-perception, discouragement from the prevailing male peer culture and the Lack of faculty encouragement.

Related Links

Individual evidence

  1. ↑ a b Posard, Marek (August 2014). "Status processes in human-computer interactions: Does gender matter?". Computers in Human Behavior . 37 : 189-195. doi : 10.1016 / j.chb.2014.04.025.
  2. ↑ a b Beckwith, L. and Burnett, M. Gender: An important factor in end-user programming environments? , In Proc. Visual Languages ​​and Human-Centric Computing Languages , IEEE (2004), 107-114.
  3. ↑ De Angeli, A. and Bianchi-Berthouze, N. Proceedings of Gender and Interaction, Real and Virtual Women in a Male World Workshop , Venice, May 23, (2006).
  4. ↑ a b c Beckwith, L. Burnett, M., Wiedenbeck, S., Cook, C., Sorte, S., and Hastings, M. Effectiveness of end-user debugging software features: Are there gender issues? ACM Conference on Human Factors in Computing Systems (2005), 869-878.
  5. ↑ Busch, T. Gender differences in self efficacy and attitudes towards computer , Journal of Educational Computing Research 12 , (1995) 147-158.
  6. ↑ Beckwith, L. Kissinger, C., Burnett, M., Wiedenbeck, S., Lawrance, J., Blackwell, A. , and Cook, C. Tinkering and gender in end-user programmers' debugging , ACM Conference on Human Factors in Computing Systems , (2006), 231-240.
  7. ↑ Turkle, S. Computational reticence: Why women fear the intimate machine. In Technology and Women's Voices , Cheris Kramerae (ed.), (1988), 41-61.
  8. ↑ Czerwinski, M., Tan, D., and Robertson, G., Women take a wider view , In Proc. CHI 2002 , ACM Press (2002), 195-202.
  9. ↑ Tan, S., Czerwinski, M., and Robertson, G.,   Women go with the (optical) flow , In Proc. of CHI 2003, Human Factors in Computing Systems , (2003), 209-215.
  10. ↑ Gorriz, C. and Medina, C. Engaging girls with computers through software games . Communications of the ACM , (2000), 42-49.
  11. ↑ Cassell, J. Genderizing HCI Archived October 7, 2007 at the Wayback Machine , MIT Media Lab , (1998).
  12. ^ Cassell, J. and Jenkins, H. (Eds.), From Barbie to Mortal Kombat: Gender and Computer Games Archived 2009-01-25 at the Wayback Machine , Cambridge, MA: MIT Press, (1998).
  13. ↑ De Angeli, A. and Brahnam, S. Sex stereotypes and conversational agents . In Proc. of Gender and Interaction , Real and Virtual Women in a Male World Workshop, (2006).
  14. ↑ Rode, JA, Toye, EF and Blackwell, AF , The Fuzzy Felt Ethnography - understanding the programming patterns of domestic appliances. Personal and Ubiquitous Computing 8 , (2004), 161-176.
  15. ↑ 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.
  16. ↑ Zeldin, A. and Pajares, F., Against the odds: Self-efficacy beliefs of women in mathematical, scientific, and technological careers . American Educational Research Journal , 37, (2000), 215-246.
  17. ^ Margolis, J., and Fisher, A. Unlocking the Clubhouse: Women and Computing . Cambridge, MA, MIT Press, (2001).