Last month I delivered a ‘grand challenge’ public lecture at Queensland University of Technology. The Institute for Future Environments hosts these lectures, which, as you’d expect, are all about the big challenges facing humanity, from feeding the world’s booming population to managing scarce natural resources and reducing our carbon footprint. Over the years they’ve hosted people like Professor Federico Rosei from the University of Quebec, who presented on new technologies for energy sustainability, and Professor Kevin Burrage from Oxford University, talking about personalised medicine.
My lecture was (of course!) about why, given disruptive changes to the world of work, society, and education, we all need to be future capable, what future capability means, and how we can all learn to be future capable.
Here’s the abstract:
This presentation asks what it means to be capable in the context of a world of work and society undergoing massive disruptive change under the influence of digital technologies. It engages with the key shifts that are occurring to the labour market, work and careers, and explores the 21st century capabilities and skills that research suggests will be important to graduates’ productive participation in the years to come, including capabilities for complex problem solving and innovation, enterprise and career self-management, social network capabilities, and digital making skills. It suggests some key ways that universities can foster 21st century capabilities, and some strategies for building agile and dynamic educational institutions that are as ‘future capable’ as the graduates they produce.
Recently, Australian universities have become highly concerned about graduate employability, and how to ensure that our graduates have positive career outcomes. It’s not that we didn’t care about this before — but recent graduate outcome statistics show that that chances of students gaining full-time employment after graduation are declining in all disciplines, and have been for a few years now. University education represents a signficant investment for students, both in terms of time and effort and course fees, and increasingly want to know that there will be a job for them at the end.
The chief metric that the higher education sector uses to demonstrate positive outcomes is full-time employment 4 months post course completion. This metric comes from graduate surveys known as the Graduate Destintation Surveys (GDS), until recently administered by Graduate Careers Australia.
Under the new QILT (Quality Indicators in Learning and Teaching) system, there are a range of other indicators as well — including a survey of graduate employers asking about graduate employees’ capabilities. There is also a ‘3-year out’ survey of graduate outcomes. The QILT website allows people to compare courses and universities using these indicators. However, the chief metric that is reported and used is still the short-term full-time employment metric, along with median graduate salary.
The short-term full-time employment metric can be useful as an indicator in some respects. For instance, Tom Karmel of the National Institute of Labour Studies, has recently used the GDS to show that more than 50% of the variance in declining graduate outcomes is due to a softening labour market and an oversupply of graduates, particularly in some fields. This has been exacerbated by the introduction of the ‘demand driven system’, and uncapping the number of university places that can be offered in Australia*. The sector is on track to meet its 40% university participation by 2020 target.
Another example of an interesting use of the graduate destination full-time employment metric comes from Denise Jackson from Edith Cowan University, who demonstrated the importance of social capital to initial graduate outcomes, also using statistical modelling of the GDS survey data (in her 2014 study, there was a 54% increase in the chances of full-time job attainment if social network strategies were used).
However, the full-time employment metric we use is problematic in important ways. I summarise these issues as: (i) full-time employment as an employee, (ii) employment is different from employability; and (iii) short-term, narrow outcomes.
1. Full-time employment as an employee. The metric has long been criticised by educators in the arts and creative industries, where the portfolio career (multiple job-holding, self-employment) is ubiquitous – as, of course, is underemployment. But in fields where self-employment and multiple job-holding are common, the ‘full-time employment as an employee’ metric does seem less relevant**. It also might be less relevant across the board in coming years as the traditional organisational career continues to decline, and more and more people are engaged in self-managed, portfolio careers. There is evidence that this is occurring already: while Australia’s overall unemployment rate is steady, the rate of part-time and short-term work overall, and casual jobs for young people 18-24, is increasing. Eighty-six per cent of the new jobs created in Australia last year were part-time. Across OECD nations, 20% of all jobs terminate within one year, and 33% terminate within 3 years. In the US, 40% of work is contingent.
There are also the phenomena of ‘uberisation’ of work, and the start-up economy. While self-employment is actually declining across Australia (according to ABS statistics), more and more people are engaged in informal, self-generated and distributed models of work and income earning through platforms such as Uber, Airtasker (Upwork in the US), and AirBnB. There is also much talk and policy about fostering a start-up economy, particularly in STEM fields, as a way to promote economic growth and social well-being in Australia. It seems that historically, an entrepreneurial career path has not often been chosen by recent graduates, and entrepreneurship is something that tends to be adopted with greater career experience – but it is something that is increasingly being encouraged.
My overall point is this: The national graduate outcomes data collection is the only one we have. If the survey doesn’t include measures of more complex job and career arrangements, we have no way of knowing exactly what’s going on for graduates across Australia. For disciplines where full-time employment is less relevant, and as full-time employment as an employee becomes less common across the economy, it seems less and less useful as a way of describing the outcomes of recent grads.
But of course the GDS (now the GOS in QILT) isn’t just used to describe outcomes — it’s used to benchmark universities and courses against one another. This brings me to my next reservation: employment is very different from employability.
2. Employment is different from employability.
In the last few years, graphs of our declining graduate outcomes like the one above have been used to argue that universities need to be doing more to enhance our students’ employability. However, there are actually a wide range of stronger influences on whether a graduate is employed or not, including (as Tom Karmel points out) the degree of competition for entry-level jobs, and the availability of roles. In 2005, McQuaid and Lindsay published a theoretical framework – one of many – of influences on employability and employment, which they summarise as ‘individual factors’, ‘personal factors’, and ‘external factors’. The traditional remit of universities has been just one element of these: skills and capabilities, and perhaps also some psycho-social factors that can be learned, such as confidence, proactiveness and resilience.
I’d argue that there are indeed things universities can do, and can do better, to enhance their students’ employability (and also, while we’re at it, their citizenship and sustainability capabilities). But using graduate outcomes as the benchmark is leading universities to do things that are outside the traditional capability remit, in seeking to compete for one another for students — such as direct interventions around graduate recruitment, and changing the range and types of courses that they deliver to choose those with better short-term full-time employment outcomes. Universities with regional campuses in areas where there is higher unemployment are at a disadvantage in the benchmarking– and I would hate to see them move out of regions and stop offering degrees to people from diverse backgrounds because the graduate employment outcomes might be lower in these regions.
3. Short term, narrow outcomes.
In a context where our KPI is short-term, full-time employment outcomes, universities are more and more ‘teaching to the test’ — which means we are paying close attention to employer surveys where desired graduate employabiliy skills are listed out (interpersonal skills, written communication etc), and we are paying close attention to the skills that professional accrediting and registering bodies say that they need. The idea is to make graduates as ‘oven ready’ as they can be – both in terms of specific technical and disciplinary skills for their professions, and their transferable / generic skills.
One problem here is that the world of work is in massive flux. In teaching to specific outcomes, the danger is that we start encouraging narrow, inflexible career identities, and overly specific, short-term skills. When students graduate in 3 or 4 years’ time, there may not be the demand for (for instance) print journalists, primary school teachers, or graphic designers, and we need our grads to be able to reinvent themselves and their skills to find and obtain other meaningful work. We don’t teach enough for disciplinary and professional agility.
The CEDA (2015) study into the automation of Australian work suggests that over the next decade, more than 40% of existing job roles will disappear anyway (goodbye taxi drivers and telemarketers!). Other entirely new roles will be created — and while it’s difficult to predict exactly what these roles will be, we’re seeing this already in statistics coming from the US around new jobs in information security, big data analytics, and social media. Further, the roles that will remain are changing, and will require different skill sets. Work roles will require more digital capabilities, emotional intelligence, creativity and complex problem solving, and complex manual dexterity (these kinds of skills are less likely to be automatable).
I also suggest that in this age of uncertainty and unprecedented social change and complexity, where we are confronted by more and more ‘super wicked problems’ — climate change, loss of biodiversity, antibiotic resistance, refugees and asylum seekers, widening gaps between the rich and the poor… and the list goes on — surely we need KPIs around capability development beyond employability skills. I read yet another article this morning about global catastrophic risk (nice reading to go with one’s cornflakes) that predicts our chances of destroying ourselves during the 21st century at about 50%. It’s hard to give exact probabilities on these kinds of things. However, the people who are graduating from our universities will lead our world in the coming decades — they need the capabilities to engage with and manage complex social, cultural, economic, and environmental challenges, as well as to find or create work and perform well in that work.
So, what should we be measuring?
Measurement and benchmarking is an inevitability in this space. It’s difficult to generate suitable, simple benchmarks for our graduate outcomes. I understand why full-time employment is used – it’s simple, and a good indicator of some things. However, we certainly need more nuanced, longer term outcome measures around employment, that embrace self-employment and the portfolio career as well as the metric of ‘short-term full-time work as an employee’.
We need to provide indicators around the actual capabilities that our graduates possess, and their behaviour (such as setting up their own enterprises, if that’s what we want). These indicators need to include capabilities beyond short-term employability skills, to encompass broader employment outcomes and the changing world of work. Finally, I think we need to include social, cultural, and environmental capability indicators, and those of critical thinking and learning, as well as employability skills.
In turn, we need the infrastructural, HR and policy supports in place so that our graduates are able to make the most of their capabilities. We need a labour market that can accommodate our skilled young people, and where they can make meaningful contributions.
*the solution doesn’t seem to be to re-cap the number of places offered. In fact, Andrew Norton offers some interesting commentary about how limiting the number of places in courses actually results in worse labour market mismtaches than we have at present. He provides the example of the 1990s Government restrictive caps on medical student places, and points out that this resulted in widespread shortages of doctors, something that was eventualy mitigated by inviting many more overseas-qualified doctors to practice in Australia.
** I should note here that the graduate outcomes survey does include a measure of ‘part-time employment – seeking full-time employment’ — but it isn’t detailed enough to describe employment patterns.
July was a busy month for me. I interviewed 43 people in different roles from a total of 26 Australian universities, to build a national picture of higher education engagement with learning and teaching for professional connectedness. The team have also profiled a number of humanities, arts and social sciences graduates and industry / community representatives across Australia to explore how professional connections and networks are important for success in 21st century work and life (more on these findings later).
Key findings of the higher education interviews
Australia wide, universities are stepping up to the challenge of fostering graduate employability through industry and community engagement. There is a national movement towards the development of university-wide employability strategies and infusion of employability skills and career development learning into all levels of the curriculum and elements of the university experience.
We are using a range of broad pedagogic approaches that support support the university-wide strategies, including: new models of WIL, alumni engagement, direct industry teaching, co-curricular facilitation and recognition, social media and professional identity building online, and connected learning.
We continue to struggle with the resource-intensiveness of effective industry engagement, and the scalability of our programs. The ad hoc approaches that used to work with a small number of students across a few programs and a few industry partners are proving less effective as we move into an era where 100% of our students will experience learning that is integrated with, related to, and/or otherwise connected with the world of work.
Some specific thoughts about students’ professional connectedness capabilities
learning for professional connectedness remains tacit and undervalued. Students are increasingly working with industry and community within and outside the curriculum, but often do not realise the importance of the connections they are making, or how to value, foster and extend those connections for future employability
we need to go beyond Linkedin profiles. Development of student professional identities online is key to employability, but employers are looking for more than simple Linkedin profiles and ePortfolios. How are students actively engaged with their online professional networks? Do they have industry authentic blogs, portfolios, social media presences? Are they interacting with the professional community in meaningful ways?
how are we supporting student networking? Many of our industry-engaged pedagogic strategies build a few strong professional connections. On average, students know only 1 employer when they graduate (often a WIL employer). How are we supporting our students to ‘network’ and grow their wider professional connections?
professionals use their social networks to learn, but universities tend not to promote this type of learning. There are substantial opportunities for students, universities and industry in ‘connected learning’, building learning communities and communities of enquiry around mutual areas of interest and practice. How can we start to build these broader communities and networks and learn from each other?
If you want to know more about what I’ve been finding in my interviews, head on over to the Graduate Employability 2.0 community of practice.
I promise that the third part of my series ‘the university of the future’ is still coming up! I got distracted… Over the weekend I read some documents about transferable skills, which reminded me that I had an idea for an article about them way back in 2007 around the time I was writing my ‘the graduate attributes we’ve overlooked’ paper. Here are some of the thoughts I was going to put into the paper I never managed to write.
For the last 20 or so years, the dominant way that universities have demonstrated their engagement with the graduate
employability agenda is through the notion of development of generic (aka transferable aka soft aka key) skills. By definition, these skills are non-task and non-context specific, and they are argued to enhance graduate employability by appealing to all employers. The argument is that once learned, these skills can be transferred from context to context – they can be applied across different subject domains. A few examples of generic skills include (there is no universally agreed list): written communication, teamwork, digital literacy, problem solving, and information literacy.
The generic skills approach is a simple one, and it has a lot of appeal. We teachers can map our curricula to demonstrate that we are teaching these skills through our programs; students can cite that they possess these skills when they develop their resumes; recruiters can easily find skills matches between job advertisements and applications; employers can be happy that they are employing graduates with the right kinds of skills.
The problem with all of this is that generic skills don’t actually exist. There is no such thing as a non-task, non-context specific skill.
Skills are learned in specific contexts and through specific tasks, and they are deployed in specific contexts through specific tasks. These specific skills that are acquired and deployed in specific contexts and tasks may have features in common, and this is what the generic skills approach does. However, to point to the presumed features in common to the exclusion of the specificities is what I would describe in an academic paper as ‘highly problematic’, and what I will describe here as superficial and dangerous. It lulls educators into a false sense that we’re covering off on the capabilities that are important, when in fact this is not necessarily the case.
It leads to the practice of context / domain / discipline ‘free’ skill development, which rather than being without domain/discipline/context (impossible!) asks students to learn generic skills in domains/disciplines and contexts completely alien to those in which they will be applying those skills in the future. Examples of this include generic written communication and information literacy courses one sometimes sees in foundational university programs. The challenges here are first that students can’t see the immediate relevance of, or have interest in, what they’re studying, so engagement tends to be lower. Second, they have trouble translating the skills they’ve learned into other contexts and applications later on. This translation is not a simple ‘transfer’ – it is a complex process involving assessment of which previous learning can simply be applied, what needs to be changed for the new context and how, and which entirely new things need to be learned and how. The process of translation is made much more difficult by greater differences between the specificities of the first context and the second.
The easiest way to build skills that employers are going to find appealing is to make the skill acquisition specificities as close as possible to the application and deployment specificities – or, put another way, make the learning activities as authentic as possible. This means that less translation is required between learning experience and work experience. However, students continually encounter new situations and tasks and will therefore need to engage in skills translation throughout their lives. No two learning/skill application contexts are the same. Therefore we must scaffold and support students to build what I’m calling skills translation bridges for themselves — that is, we must teach how the specific skills learned in one context can be translated for the specificities of a new context.
To what extent and how do you build skills translation bridges in your teaching?
The ‘T-shaped person’ metaphor has been floating around talent management and education circles for nearly 25 years now. The basic idea is that professionals need to possess both depth of disciplinary knowledge and breadth of capability for collaboration across multiple disciplines – hence the vertical and horizontal strokes of the ‘T’. According to T proponents, traditional higher education programs tend to produce ‘I-shaped’ graduates – students who possess disciplinary capabilities, but lack collaborative, communication and boundary-crossing capabilities. The notion of the ‘T-shaped’ professional has grown in popularity over the last five years, with IDEO’s CEO Tim Brown coming out as a strong advocate for the idea, and T-Summit Conferences being held annually in the US higher education sector.
I know, I sound skeptical. Actually, those of you who have read my work would know that I’m all for capabilities that support transdisciplinary work (e.g., Bridgstock, Dawson & Hean, 2012; Bridgstock, 2013), which the ‘T-shaped’ movement is all about. There is also quite a lot of academic literature out there that suggests that increasingly, professionals need to collaborate effectively with people who have quite dissimilar backgrounds to themselves. In fact, these kinds of collaborations are more likely to produce innovative ideas and effective solutions to difficult problems than unidisciplinary approaches. When I’m teaching my first years about transdisciplinarity I often use the example of the groundbreaking 2010 article in Nature, where gamers using the ‘Foldit’ platform were able to identify the molecular structure of complex proteins in just a few weeks, when scientists had struggled with the problems for years using traditional methods.
Where I have an issue with the ‘T-shaped’ person metaphor is in the downward stroke of the T – the disciplinary depth. My research with successful innovators in various disciplines has shown that one downward stroke is nearly always not sufficient. Rather, highly successful 21st century professionals tend to be ‘key shaped’ – they possess several areas of disciplinary capability at different degrees of depth. They may have one very deep area of knowledge and skill, but it is accompanied by several others of varying depth as well. These areas of disciplinary expertise become the ‘teeth’ of the key.
There seem to be two main reasons that multiple areas of disciplinary expertise is advantageous. First, as the number of teeth on the key increase, they support and widen the horizontal stroke / spine of the key. Put another way, possessing disciplinary knowledge and skills in multiple fields supports the ability to translate knowledge, collaborate and work with others from dissimilar backgrounds and knowledge regimes.
Second, more ‘teeth’ on the key affords the individual their own unique transdisciplinary perspectives that support creativity, innovation and problem-solving, and promote employability. A molecular biologist who has some background in gaming or 3-D visualisation might well come up with an innovative way of solving protein structure problems. Similarly, think about the possibilities if you were an architect who has an interest in inorganic chemistry, or a civil engineer / physicist involved in designing and building a deep-space telescope.
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Bridgstock, R., Dawson, S., & Hearn, G. (2011). Cultivating Innovation through Social Relationships: A Qualitative Study of Outstanding Australian Innovators. Technology for Creativity and Innovation: Tools, Techniques and Applications. IGI Global.
Cheetham, G., & Chivers, G. (1996). Towards a holistic model of professional competence. Journal of European Industrial Training, 20(5), 20-30.
Gibbons, M., Limoges, C., Nowotny, H., Schwartzman, S., Scott, P., & Trow, M. (1994). The new production of knowledge: The dynamics of science and research in contemporary societies. Sage.
Khatib, F., DiMaio, F., Cooper, S., Kazmierczyk, M., Gilski, M., Krzywda, S., … & Foldit Void Crushers Group. (2011). Crystal structure of a monomeric retroviral protease solved by protein folding game players. Nature Structural & Molecular Biology, 18(10), 1175-1177.
Neuhauser, L., & Pohl, C. (2015). Integrating Transdisciplinarity and Translational Concepts and Methods into Graduate Education. In Transdisciplinary Professional Learning and Practice (pp. 99-120). Springer International Publishing.