On influences on women choosing technology careers

Report: Women Who Choose Computer Science – What Really Matters (Google, 2014)

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 (and where schools a lot of their student cohort).

On ICT Literacy in Australia (National Assessment Program)

Australia has an information and communication technology literacy assessment. Started in 2005 (run again in 2008 and 2011), the assessment looks at a student’s capabilities in Year 6 and Year 10 (approx age 12 and 16). In 2011 5,500 students per age category were chosen at random, representing 649 schools. The 2014 assessment will take place between October and November this year. The 2011 report is available here.

Background:

The assessment defines ICT literacy as: “the ability of individuals to use ICT appropriately to access, manage, integrate and evaluate information, develop new understandings, and communicate with others in order to participate effectively in society” – the 2011 report pointedly notes “ICT literacy has not focused on programming but on computer use”. The assessment included seven main activities covering topics such as installing software, managing an anti virus, web based research on topics, creating a video about a topic, updating a wiki entry, working with collaborative software,  using email and organising an event using online tools.

The Ministerial Council on Education, Employment, Training and Youth Affairs (MCEETYA) has released a couple of statements over the years that give insight into their acceptable levels of ICT literacy (my emphasis and underlining):

When students leave school they should be “confident, creative and productive users of new technologies, particularly information and communication technologies, and understand the impact of those technologies on society”. – Adelaide Declaration on Australia’s National Goals for Schooling, 1999

Successful learners “have the essential skills in literacy and numeracy and are creative and productive users of technology, especially ICT, as a foundation for success in all learning areas”. – Goal 2, Melbourne Declaration on Educational Goals for Young Australians, 2008

Assessment outcomes (2011): 

• 62% of Year 6 students reached or exceeded “proficient standard” (49% in 2005 and 57% in 2008)
• 65% of Year 10 students reached or exceeded “proficient standard” (61% in 2005)
• Children of parents working in “unskilled, manual and sales jobs” were less proficient than those in “senior manager and professional” jobs – Year 6 (50% v 79%) and Year 10 (57% v 78%) students
• Children of Indigenous parents were less proficient than those of non-Indigenous – Year 6 (31% v 64%) and Year 10 (36% v 66%)
• Regionally ACT is streaks ahead of the other states/territories in terms of student proficiency
• ACT, Victoria and NSW were generally more proficient than WA, Qld, Tasmania and NT
• Tasmania and Northern Territory were the only two regions to NOT show an increase in proficiency from 2005 to 2011
• Queensland showed the greatest proficiency difference between Year 6 (55%) and Year 10 (63%) students

Student perceptions of Using ICT:

Students indicated a high level of interest and enjoyment in using computers. Males recorded higher levels of interest than females and Year 6 students expressed greater interest in using ICT than Year 10 students. Year 6 and Year 10 students showed themselves confident that they could easily download music from the internet, upload files to a website and create a multi-media presentation (with sound, pictures, video). They were less confident about their ability to construct a web page or create a database. There were no differences between males and females in terms of confidence in using ICT, but there were significant differences between Year 6 and Year 10: Year 10 students expressed higher levels of confidence in using ICT than Year 6 students. [Excerpt]

Gender in ICT:

Females recorded higher levels of ICT Literacy than males. Even though female students expressed lower levels of interest and enjoyment than males in computing, they expressed similar levels of confidence in their ability to carry out ICT-based tasks without assistance. [Excerpt]

My thoughts:

You can see I have underlined the assessment’s emphasis on “using technology”. So much of what I do and what I read is about the need to shift mentalities away from ‘using’ and into ‘creating/making’. I see the purpose of measuring base level proficiency – particularly when there are circumstances where children of some families (unskilled labour) score between 20-30% less than those of whose parents are managers and professionals. In that context, it sounds like there are some base level needs that should be addressed before we start concentrating on  training up armies of computer scientists capable of creating a generation of high growth tech jobs for Australia’s future economy.

I wrote this post to raise a couple of points:

• Australia does have a digital literacy assessment that is tracking proficiency over time
• There are wide variations in proficiency based on geography, parental backgrounds and whether you are from a minority or marginalised group
• The current assessment focuses on basic use of technology to perform everyday tasks – not coding or more advanced computer science concepts
• … in the future, hopefully after the uptake of the new Digital Technologies Curriculum, it should start addressing these areas

On Cracking the Girl Code: How to End the Tech Gender Gap

Girls Who Code is a fantastic US based not-for-profit that addresses the tech gender gap by offering activities that specifically support young girls with an interest in computer science. At its most practical – the NFP runs summer courses (seven weeks) for groups of girls around the country. The courses are facilitated by a trainer with financial support from a major tech companies.

Some background stats (US centric): only 12% of computer science graduates are female. Code.org estimates that by 2020 US universities will not be able to fill even a third of the country’s 1.4 million computing positions with qualified graduates. The industry needs to tap all areas of the economy to find skilled employees. Girls Who Code has gone from graduating 20 girls in 2012 to approx 3,000 in 2014. 95% of who go on to study computer science at university. Another insight is that girls place higher expectations on themselves – at a university level girls are likely to drop out if their marks hit a B+ while boys are happy with a B-.

The article outlines some strategies used by Harvey Mudd College in Claremont, California to raise the percentage of women graduating from computer science from 10% to 40% in seven years.

These include:

• Emphasise problem-solving real-world issues because girls tend to want to help their communities.
• Group projects: research shows that girls flourish when they collaborate with others.
• Role models: help girls build a network of like minded people – a challenge as there are so few high-profile female programmers as role models

 

On Reasons Why Women Should Work in Software Engineering

 

Alaina Percival, CEO of the nonprofit Women Who Code, recently posted her thoughts on reasons more women should work in software engineering. Her post comes in response to the recent diversity reports from Google, Facebook and LinkedIn that show women hold just 15%-17% of technical roles in those organisations.

Here are 10 reasons why more women should work in software engineering:

1. Employers want to hire you.
2. Job security.
3. The potential for flexible schedules, working from home or anywhere in the world.
4. IT jobs constantly claim the top spots on “Top Job Lists”.
5. Tech can require a lot of collaboration — a skill often valued in women.
6. The career can be fulfilling for those who like to constantly learn new things.
7. You often need to think creatively and solve problems.
8. It is considered prestigious and this will likely increase over time.
9. There are many different career paths as you move up in your career.
10. In the future, all companies will be involved in technology, so no matter what sector you are interested in you could find an engineering role.

This list could really apply to anyone but its a great the diversity is being championed.

Promoting computer science careers to high school students

Article: New Image for Computing, Report on Market Research (April 2009) (Association for Computing Machinery)

This 2009 report outlines market research and initial message testing conducted by two New York marketing and communications firms (BBMG and Global Strategy Group). In 2008 the project surveyed some 1,400 college bound high school students (age 13-17) to:

• assess the current attitudes toward computer science as a college major and future career choice
• assess the same attitudes along different lines (gender, Hispanic, African American)
• develop messages that portray computer science in a variety of ways and then test the messages among teens

A couple of scene setting points to start:

• the number of students choosing computer science as a major had dropped 70% since 2000 (UCLA, 2007)
• more than 80% of first year university students did not know what a computer science major actually did
• a different survey (Taulbee, 2007) says computer science enrolments had risen 6.2% from 2006 to 2007 – however diversity is still an issue with only 10% of those awarded to women

The report begins with high school student attitudes towards computer science as a career. For the most part they are positive.

• CS ranked third (behind music and business) as ‘a good major to choose’ – however this is split on gender lines. 74% positive for boys vs 38% for girls.
• As a career choice CS ranks fourth (behind musician (?!), doctor and entrepreneur (?!)) – but notably above lawyer, financial analyst and accountant. Once again – split on gender lines leads to 67% positive for boys vs 26% positive for girls.

The report is most useful when it moves to messaging. When choosing careers high school students focused on:

• Doing work that they find interesting (78%)
• Being passionate about their jobs (71%)
• Being able to spend time with their families (54%)
• Having the power to do good and doing work that makes a difference (52%)

The research provides a gender split for the above responses – it finds that girls are more responsive when it comes to ‘being more passionate about your work’ and ‘having the power to do good and doing work that makes a difference‘. These gender gaps were quite wide (14% and 9% respectively) suggesting that people speaking with young girls about career choices should focus on these elements in their primary messaging.

The next section of the report I found interesting was when they looked at university and career choices based on familiarity with technology. The report creates three segments i) communicators (think teenagers with mobiles/social media), ii) techies (kids fixing modems and assembling computers), and iii) creators (digital media content). Not surprisingly, all teens ranked high on the first, boys on the second and girls on the third.

From here the report identified that a reasonably high number of students in the creators space (which is 44% female) were thinking of taking up computer science majors (74%) and careers (68%). This insight suggests that it is possible to translate a young girl’s enthusiasm for digital media (photography mainly) – into future digital careers. [nb a point of note – while about 70-80% of students thought computer science was a good idea – only 6%-14% considered it as a future career path. The review team proposed a separate report to address this issue]

My take away:

When talking to girls about tech careers I suggest focusing on the outcome/result of the technology. They know that apps, websites and systems are built with ‘code’ but it helps to explain that they are built by people that work with humans, that understand design, that have the ability to make things beautiful and work seamlessly. User experience, app development, business analyst roles are strong points for discussions on careers. Talking through how different organisations use technology to improve lives (ie local councils using apps to fix infrastructure or banks helping retailers conduct transactions quickly) is a good approach. Another point of conversation is that having the skills to design software (or work in tech) empowers the girls to effect this change – to ‘be in the drivers seat’.

Conclusion:

The strongest positive driver towards computer science or an openness to a career in computing, regardless of gender, is “having the power to create and discover new things”.

How to present STEM career choices to girls

The New Digital Learning Playbook: Understanding the Spectrum of Students’ Activities and Aspirations (2014, link)

This article discusses digital learning trends, use of technology in the classroom and confidence levels for boys/girls from K-12. Interesting information if that’s what you are after however the part that interested me the most was a review of students’ interests, differentiated by gender, in making STEM career choices.

The review begins with a table demonstrating that by Y9-12 the number of girls that assessed themselves as advanced tech users had dropped to almost half that of boys (17% v 32%). The conclusion from this is that if female students are not confident in their own tech abilities then they will be less likely to pursue tech careers.

It’s not all over though. A further chart says that 67% of female students are either somewhat interested or very interested in STEM related careers (79% in boys). The article then highlights that girls in particular are interested in socially based and digital career exploration opportunities that can be highly individualised to their interest levels.

A new approach to engaging girls in STEM fields may therefore include:

• Providing an online self-assessment of skills and interests (34%)
• Working with mentors who can guide college choices (32%)
• Access to websites and day-in-the-life videos for self-directed career exploration (28%)

Students were also interested in these general STEM career engagement ideas:

• Visiting companies to learn about careers (58%)
• Participating in school based career exploration programs (47%)
• Having teachers with a background in a STEM profession (43%)

It’s an interesting idea – reviewing how girls go about learning and then making sure that information is delivered in a similar fashion. Page 6 has a chart that shows that girls are more advanced tech users than boys in all aspects of digital writing (except texting conversations on gaming and HTML coding). The main broad categories that girls are strong in are digital media and writing (photography, creative writing, and journalism) and social media and online interactivity (blogging, tweets, instant messaging).

My general perception is that when talking tech with girls it is best to focus on results and outcomes. The idea that tech is a way of doing something, achieving a social outcome or helping overcome challenges.

A summary of “Is Coding the New Literacy?”

This post is a summery of the reasonably detailed article by Tasneem Raja, ‘Why Computer Literacy is Key to Winning the 21st Century‘ (Motherjones, June 2014). This 6,000 word piece touches on the role technology can play in driving productivity, the decline of both student and teacher numbers, the difference between using tech and being fluent in it as well as gender and race divides. Its long but bang on.

Computational Thinking vs Coding:

What I like about this article is that pulls back from the argument that everyone should learn to code and refines the challenge as everyone should have capacity to think logically and engage computational thinking methodologies to solve challenges. The article suggests that the biggest issue we are facing is that “Unless you can think about the ways computers can solve problems, you can’t even know how to ask the questions that need to be answered” (Annette Vees, University of Pittsburgh). Computational thinking involves solving problems, designing systems, and understanding human behavior,” she writes in a publication of the Association for Computing Machinery. Those are handy skills for everybody, not just computer scientists.

Why you need computational literacy for future jobs:

The article proposes that computational fluency is fast becoming a divide in the same way that numeracy/literacy used to keep a stable of scribes employed to write on behalf of citizens. While not everyone will go on to become a programmer, at some point, everyone will need to work with programmers to solve problems. Knowing how to talk in technical terms will make this process easier. The article also draws a clear line between knowing how to use technology and knowing how to make it. It raises the idea that knowing how to make a powerpoint or edit in iMovie is not the same as being technologically literate.

US Computer Science Study Trends:

Between 1989 and 2009, while almost all other STEM subjects grew in the US, computer science dropped from 25% of high school students enrolled to 19% (USA, National Centre for Education Statistics). In 2014, only 20 states allowed computer science to count as part of a core graduation requirement. Part of this is the lack of qualified teachers. In the US, states manage teacher accreditation and there is no clear path for tech teachers as they move from university into the education system.

Gender, messaging and tech studies:

The New Image for Computing survey (2009, link) tested various messages about computer science with college-bound teens. It found that explaining how programming skills can be used to “do good”—connect with one’s community, make a difference on big social problems like pollution and health care—reverberated strongly with girls. Far less successful were messages about getting a good job or being “in the driver’s seat” of technological innovation—i.e., the dominant cultural narratives about why anyone would learn to code.

In the US, women currently make up only 20% of the tech workforce. This is a drop from 37% in 1987. Excluding huge swaths of the population also means prematurely killing off untold ideas and innovations that could make everyone’s lives better. There is evidence that girls exposed to very basic programming concepts early in life are more likely to major in computer science in college (Increasing Student Interest and Attitudes in STEM: Professional Development and Activities to Engage and Inspire Learners, 2011, link).