This is one of a series of mini-essays I set myself in response to the question ‘is educational technology a feminist space?’
Pragmatically, learning tech is a place of work and so where struggles over equal value, equal pay and working conditions take place. Martin Hawksey recently analysed the gender of respondents to the (UK-based) Association for Learning Technology’s annual survey. He found the M/F split to be roughly equal (you can read his blog post about this data, or see how he and Maren used it in a keynote for IWD19). I was interested, though, in this slide showing how men and women tend to occupy different learning technology roles.
I’ve written in the past about learning technology workas a contested or ‘hybrid’ profession. For example, it’s central to the project of the neo-liberal university (centrally located, invested in institutional agendas, associated with technical systems and solutions) but marginalised within it (youthful, precarious, constantly vulnerable to realignment). Perhaps another sign of its hybrid and contested nature is here, in the inclusion of work roles identified with both genders. The gendering of IT as a masculine interest begins in school. So does the less strident gendering of ‘teaching’ as feminine, especially the student-centred or ‘learning support’ end of the teaching spectrum: the tutorial or development workshop, rather than the set-piece lecture or curriculum committee. The work of helping people to learn rather than defining and performing powerful knowledge. Of course men and women do both roles equally competently – but it does look as though a traditional gendering of roles is being played out here in the work being performed by actual male and female bodies.
It shouldn’t be news that tech companies have a gender equity problem . The proportion of women in the IT workforce is actually lower than it was 30 years ago,and while the pay gap is narrowing for equivalent work, women are found in lower-paid roles. A recent Kaggle survey of workers in data sciencefound that men and women doing the same data-related tasks were given different job titles and differential pay. Even more troubling, with data skills required for high-value roles in all industries, only 16% of Kaggle’s data scientists were women. UNESCO’s women in science database shows that women make up only 12% of AI researchers and 6% of software developers. Across the world less than 30% of researchers are women, and men are 13 times more likely than women to file ICT-related patents.
Marie Hicks has recently written a wonderful short historyof how women – the original ‘computers’– were systematically excluded from programming jobs as the power of the industry grew. (A longer readcan be found here). The first interfaces looked like typewriters, and typing was women’s work. But as software ate the world, and data digested it, the power and prestige of programming were more than women could handle.
Rushkoff’s famous ‘choice’ – to ‘programme or be programmed’– defines what kind of agency we can have in a data-driven, programmable world. But the choice is not the same for everyone. It may not even be a choice at all. It may be just a further twist in the gendering and racial profiling of powerful forms of knowledge work.
Schools and universities aren’t meant to be like this. They are meant to offer a more secure, egalitarian environment than a digital start-up or IT department, which may be one reason so many tech-literate women are attracted to work in learning tech. Education is in the business – isthe business – of levelling playing fields. But things aren’t so great here either. The proportion of women working in HE drops off at every level above postgraduate study. Among academics the gender pay gap is 12% and the gap widens if you look at other roles: only 27.5% of those in management are women, compared with of 56.5% of the student body. Globally, around 18% of ‘top’ universities (those best positioned to import students and export knowledge) are led by women. In secondary education 62% of the workforce are female but only 36% are heads. And the latest gender equity figures find some schools and colleges among the worst offenders.
Flexible working arrangements are good news for women juggling responsibilities (why is it always women who are juggling?). Online teaching work often appeals to women for similar reasons. But casualisation is one of the forces that has made the equity gap worse, and technology is complicit in casualisation.
I’m drawing here on articles from UCUWonkHE, the UCU writing on WonkHE, Guardian Educationand a couple of great academic reviews from Australia, hereand here. These show that women, people of colour and disabled teaching staff are more likely to be on casual contracts, for longer, with knock-on effects on lifelong earnings and pensions. That staff in non-academic professional roles like LT – roles that have exploded in number as expensive, full time academic staff have been cut – are also more likely to be on fixed-term contracts. These staff are also more likely to be women.
Casualisation has grown alongside other forces: the new managerialism and corporatism, quality assurance metrics, and an unbundling of research and teaching roles. Who would have guessed that women would lose out in these brutally reductive, career-defining metrics, or that more women would end up on the less brutal, less rewarded (but financially more valuable) ‘teaching’ side of the academic divide?Karen Cardazo (2016) regards casualised teaching and other precarious support roles as the equivalent to ‘care work’, inherently ‘feminised’ (even when carried out by men): underpaid, undervalued, and dependent on the personal commitment of its participants – their ‘care’ for the student body.
‘The complex work of ‘professing’ has been unbundled into a two-tiered system of academic labour that also devalues caring activities’Kardazo
Alongside tech companies, educational organisations are among the most powerful forces shaping the future – our technologies, knowledge practices, values and work. So it matters that both kinds of organisation (ed and tech) are deeply, institutionally discriminating in their employment practices, in crude economic terms, and culturally in terms of how different kinds of work are gendered. Learning technology work is feminist work. Many learning technologists are also feminists at work and we are going to keep talking about these issues.