Influences on women choosing technology careers

google influencesToday’s guest post is from the redoubtable John Westgarth, who has been reading Google’s report Women Who Choose Computer Science – What Really Matters and nicely covers what I would have wanted to say.

Today I had a read of this Google backed report into women in technology. In the face of so many reports commenting about negative perceptions of women and tech, this one stood apart due to its positivity. The report identified the two main drivers that can have the most impact on increased female participation as ENCOURAGEMENT (social/family/peers and self belief) and EXPOSURE (availability of academic subjects and perceptions of the tech sector). The report also highlighted that some commonly held beliefs about what influences students may not be as important as we credit them.

Top four influencing factors are:

  • Social encouragement: positive reinforcement of computer science from family and peers. Family support influenced 17% of people surveyed, peers 11%. It also noted that girls are half as likely to receive encouragement as girls.
  • Self perception: having an interest in puzzles and problem solving – and a belief that those skills can translate to a successful career. Self perception of maths ability and problem solving influenced 17% but the ultimate influencer was a passion for solving problems and tinkering.
  • Academic exposure: availability of both structured (formal/graded studies) and informal (after school programs). This accounted for 22.4% of explainable factors – the study went on to say that regardless of how they were exposed – young women that had been exposed were more likely than those that weren’t (eg. Anything is better than nothing).
  • Career perception: familiarity and perception that tech careers can be diverse and be positive. Accounts for 27.5% of explainable factors on why a young woman would pursue an career in technology. The main problem here is that a flawed perception of tech (ie nerdy, boring, hard, technical) actively dissuades young woman from pursuing an interest, and ultimately correcting the perception.

Things that have less influence include: ethnicity, family income, parental occupation and perceptions of natural ability. Other factors that had limited influence include: having a family member in the tech sector, early exposure to tech, age of first computer exposure, access to mobile devices, natural aptitude, pre-college computer science education.

The conclusion is overwhelmingly positive. Mainly because the report believes that the four core influencers can be addressed. It believes that outreach programs should:

  • contain a parent education component,
  • provide young woman an opportunity to practice problem solving skills,
  • support organisations adding informal or formal computer science education to more schools,
  • focus on the visibility of female role models and story telling of positive impact careers.

My thoughts:

I liked the simplicity of this arrangement – exposure and encouragement. It makes sense. I liked the positivity that these are actionable areas and the suggestions for how to act. I like that the report makes an effort to identify things that are not critical influencers (but could be seen as distractions to outreach programs?). I would argue that those elements are things that need to be considered – e.g. parents and peers will still influence but, depending on background/situation, may influence in different ways.

One thing the report didn’t touch on was the age at which young women are most receptive to external influences. The report is categorised into ‘high school’ and ‘post college’ – but doesn’t mention primary education or the role of high school peers in subject selection. There is the common perception that early high school (age 13-14) is the subject choice cliff, the point at which female perceptions of technology is first revealed.

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