Blog 4 (Fall 2016) – Do we perceive technology as a male dominated space?, by Sooyeon Kang

In our modern Western, first world country context, do we perceive technology as something that is dominated by a certain gender? Or perhaps do we view it as a typical domain full of one gender? Is technology a space just like ‘math’ that’s considered more ‘masculine’ while as ‘textiles or home economics’ is more ‘feminine’?

Does this mean the way we communicate and interact with technology is impacted by gender?

Or does society need to shift the way it views technology?

(i)                            Introduction

Specifically I really enjoyed looking at the research done by Northern Arizona University (  Huffman et al, (2013) ‘Using Technology in higher education: The influence of gender roles on technology self-efficacy’, Computers in Human Behaviour, 29, 4, 1779-1786) about whether gender roles impacted on technology in higher education.

So, there are studies that have shown that many students do not learn the skills needed to master technology as quickly as others (McCoy, 2010.) This is something that is worrying as their ‘perceived ability’ has a direct correlation in whether the students frequent the use of technology or not. So, the research mentioned previously investigated what factors lead to differences, if any in computer self-efficacy between men and women.

They found in their research that ‘technology self-efficacy relies less on biological sex and more on societal based gender norms’ and that ‘educators and researchers need to look beyond biological sex and use gender as a factor to understand how students’ perceive their own ability and attitude in regards to the use of technology in the classroom’ (Huffman, 2013).

This is something I agree with – perceived notions of gender roles and what each sex is ‘good at’ or ‘should be good at’ is something that pervades every aspect of life and while this research argues that educators pay mind to the roles, I believe educators are in a position to eradicate negative arbitrary gender roles and set better models of beliefs. For example, an arbitrary, cliché belief that ‘boys’ are ‘better at coding’ and thus ‘should help out girls’. There should be a more of a move, whether it be in primary, secondary or tertiary education, for educators to change how they perceive gender norms and to effectively work towards gender equality in every aspect.

But, specifically in technology self-efficacy, this is how gender norms came into play.

(iii)                        Research Methods and Findings

A.          (A) Participants

Participants for this study were 750 undergraduate students (58.2% female, Mage = 19.3, SD = 3.1) from a medium- sized public university in the southwestern region of the US. Prior to this study, only 22.1% of participants had taken an online course.

B.         (B) Questions Asked

·             Participants were asked the question: ‘‘What is your sex?’’ Their response choices were either ‘‘male’’ or ‘‘female.’’

·             No non ‘genders’ or others were included

·             Used the masculine factor of the Personal Attributes Questionnaire (Spence & Helmreich, 1978 to assess masculinity traits in men and women

·             Respondents described themselves by choosing from a five-point scale with an extreme descriptor on each end (e.g., 1 = not at all extreme to 5 = very independent; 1 = not at all competitive to 5 = very competitive). Sample descriptors include: ‘‘Not at all competitive” to “very Competitive” and “Very Passive” to “Very Active”

·             Then, ‘ Technology Self- Efficacy’  was measured using a 9-item scale adapted from Compeau and Higgin’s (1995) computer self-efficacy scale (current sample: a = .86). The root of the questions stated, ‘‘I could successfully use new technology.’’ This scale has shown that it is highly reliable (r = .81) and valid (positively related to technology use, r = .45; negatively related to anxiety r = .50; Compeau & Higgins). A sample item was ‘‘If there was no one around to tell me what to do as I go.’’ The five-point response item ranged from “strongly disagree” to “strongly agree”

C.        (C) Findings

·             Males self reported higher levels of perceived technological ability than females.

·             “Although many students in today’s universities come prepared with previous experience in the use of technology from home or previous schooling (Goode, 2010), masculinity continues to be a stronger predictive factor of technology self-efficacy than previous preparation or university support.” (Huffman, 2013).

So basically it’s unsurprising that the research found that the way people interact with technology and their efficiency has everything to do with gender norms and less to do with actual biological ‘sex’.

(iv)                       Conclusion

Gender norms are internalized by society to the extent that it’s harmful. It impacts on how we interact with technology especially in an educational context. This is why educators should take great care to dismantle harmful stereotypes to encourage everyone to be comfortable in how they’re formed and to have respectful opinions of everyone. Gendered social constructs are pervasive and destructive to women and minorities in a developed, liberal context. There really needs to be an overhaul of how we think of gender.


Huffman et al, (2013) ‘Using Technology in higher education: The influence of gender roles on technology self-efficacy’, Computers in Human Behaviour, 29, 4, 1779-1786.

·             McCoy, C. (2010). Perceived self-efficacy and technology proficiency in undergraduate college students. Computers and Education, 4, 1614–1617.

·             Coffin, R. J., & MacIntyre, P. D. (1999). Motivational influences on computer-related affective states. Computer in Human Behavior, 15 , 549–569. 10.1016/S0747-5632(99)00036-9.

·             Cooper, J. (2006). The digital divide: The special case of gender. Journal of Computer Assisted Learning, 22, 320–334. 2729.2006.00185.

·             Young, B. J. (2000). Gender differences in student attitudes toward computers. Journal of Research on Computing in Education, 33, 204–216.

·             Havelka, D. (2003). Predicting software self-efficacy among business students: A preliminary assessment. Journal of Information Systems Education, 14 , 145–152.

·             Colley, A. M., Gale, M. T., & Harris, T. A. (1994). Effects on gender role identity and experience on computer related attitude components. Journal of Educational Computing Research, 10 , 129–137.

·             Steele, C. M., & Aronson, J. (1995). Stereotype threat and intellectual test performance of African Americans. Journal of Personality and Social Psychology, 69, 797–811.

·             Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19 , 189–211. 249688.

·             Goode, J. (2010). The digital identity divide: How technology knowledge impacts college students. New Media Society, 12 , 497–513. 1461444809343560.

·             Peterson, H. (2010). The gendered construction of technical self-confidence: Women’s negotiated positions in male dominate, technical work settings. International Journal of Gender, Science and Technology, 2, 66–88.

·             Plumm, K. M. (2008). Technology in the classroom: Burning the bridges to the gaps in gender-based education. Computers and Education, 50 , 1052–1068. doi:0.1016/j.compedu.2006.10.005.


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