Abstract

Innovation, creativity and entrepreneurship (ICE) skills are increasingly recognized as being of importance beyond business school courses. Students from a wide variety of disciplines are being encouraged to lean these skills because they enhance employability and prepare them well for working in many kinds of public and private sector organizations. At the same time companies are recognizing the importance of internal entrepreneurship as a way of dealing with an increasingly volatile environment; they too are concerned with upgrading the skills profile of their employees. All of this raises questions about the ways in which learning these skills will be enabled and this chapter explores a ten year forecast of how that landscape might change, drawing on VISION, a major EU-funded research programme.

Keywords

Innovation, entrepreneurship, skills, learning, future

Introduction

Innovation matters – of course. It’s the driving force behind economic and social change and underpins our evolution as a civilised society. And with the kind of challenges we now face it’s also clear that the development of skills and capabilities to work with innovation are also becoming essential – they are no longer the province of specialists but something we all need to acquire and practice. They are becoming life skills – but developing them across the population raises a big question – how? What are the relevant capabilities and how to enable learning and skills development? How to teach them, who, along which channels, etc? Those are the questions being explored in the VISION project – a major European study looking at the changing landscape for education and training around innovation, creativity and entrepreneurship. At its heart is a vision of how things might develop over the next ten years and it poses challenges around what we might start doing now to secure a positive future.

The past is another country – they do things differently there. But so too is the future – we know it will be different and the VISION forecasting and futures process has explored a wide range of issues. In this podcast we’re going to look in more depth at some of the key dimensions for change – what will differ and by when?

Distilling nearly 200 interviews and 8 major workshops into a manageable framework isn’t easy but the team have built a structure to help focus our thinking. Think of it like a bridge between two worlds – the one here and now with which we are familiar – and the other stretching towards the distant mists surrounding the world of 2030. Getting to the other side requires structure – we have to pay attention to the architecture of that bridge and its core components. A real bridge would have steel and wires, nuts and bolts and rivets, platforms carrying road or rail tracks, piers to support them – and so on. It’s not just a magical insert plugging a gap in the landscape, it’s a carefully engineered structure. Our equivalent is made up of nine core components, each of which represents a shift from what we see today; we’ll look at each of these and the directions of change they imply.

Figure 1.1. Key dimensions of change in the learning landscape

• Purpose: Dealing with big problems and grand challenges 
• Structure: From disciplinary-centred knowledge transmission to problem-based learning and challenge-driven innovation.
• Collaboration: From expertise-centred to inter- and trans-disciplinary and cross-sectoral collaborations
• Spaces: From traditional classrooms and lecture halls to flexible spaces and the real world 
• Skills: From hard skills to soft skills and beyond 
• Teacher: From lecturers to coaches, facilitators and learning designers
• Learning outputs: From writing to doing & making
• Evaluating learning outcomes: From exams and papers to evidence-based learning
• Technology: From using to collaborating with technology 

Figure 1.2. Purpose

The first shift is all about the purpose of innovation. It’s sometimes easy to see innovation as an option, something we can choose to do or not. But that’s a long way from today’s reality – and certainly from the one we can see across our misty gorge. We’re already confronting huge challenges – quite apart from the pandemic we face big questions about whether our planet will survive. Climate change and the associated violent weather events have brought a sense of urgency – but this is just the tip of a very large iceberg. Our future is bound up in wrestling with population growth (and unequal distribution of opportunity), of resource scarcity including the very basics of life itself like water and food. Of trying to live peacefully on an overcrowded planet and do so while limiting the damage we seem to be doing to it. The widely-mentioned United Nations Sustainable Development Goals (SDGs) aren’t simply a useful political list to trot out but an existential agenda – if we want to survive we are going to need to work towards handling these ‘grand challenges’.

And that’s where innovation, creativity and entrepreneurship comes in – as a power tool we can deploy to help deal with them. We’ve got a good track record, we have evolved this far as a species through innovation but perhaps our biggest challenge is yet to come. And it’s one which affects the coming generations particularly. It’s not a coincidence that so much of the swelling protests to ‘do something!’ are coming from children and young adults, nor that this movement began in schools and colleges, their leaders young figureheads with a call to action to preserve their futures.

Innovation can help – and so learning the skills around ICE is increasingly important. But this knowledge and capability needs to be linked to a shift in thinking about the underlying purpose – what is innovation for? Not just for economic growth or job creation, certainly not just for making money or bringing more unnecessary things into the world. Increasingly its purpose is being questioned and reframed, with a growing concern for principles like responsibility and inclusion and a focus on social innovation as much as commercial. It’s about a shift towards big purpose, grand challenges.

Figure 1.3. Structure

Which brings us to the second shift – from a world where learning and the education process underpinning it moves from a narrow discipline-based approach to one which recognises the need for interdisciplinary collaboration. If we are going to solve grand global challenges then we need to think in terms of big integrated systems models. Innovation has never been a single discipline subject nor a theoretical one; it is a practice, the bulk of what we know having come from observations of success and failure in deploying that practice. It has more in common with a craft in the medieval sense, something which can be learned through practice, engaging with ever bigger projects and challenges. Yes, ICE is informed by many traditions – economics, sociology, psychology, engineering – but it acts as a funnel, channeling these different knowledge strands into something which enables us to understand – and operationalise – how ideas can create value.

Not surprisingly this shift towards seeing ICE as a cross-disciplinary challenge-led practice is leading to a shift in the structure of institutions designed to facilitate learning. These are already converging and the trend towards collaboration and mutual exchange is likely to accelerate. Already we are seeing institutes which recognise that challenges don’t come in neat disciplinary packages posted through the letterboxes of specific knowledge departments – they require collaboration.

For example many colleges and universities now have close links, joint institutes and other arrangements which bring different disciplines together – things like the healthcare innovation collaboration between Imperial College’s medical school (and its close ties to major teaching hospitals in London), its Business School and the neighbouring Royal College of Art with its world-leading expertise around design. Or the Norwegian University of Science and Technology which has ‘villages’ (i.e. areas of interest) of around 30 members which address questions such as ‘Biofuels – a solution or a problem?’, ‘Sustainable, affordable housing for all’, and ‘Portable technology and well-being’. Each village is run by a professor who divides students into smaller groups to work on problems in their topic area (Mulgan, G et al., 2016).

Figure 1.4. Collaboration

This idea of knowledge collaboration links with the third major shift towards cross-sector, cross-institutional collaboration. These days the ‘ivory tower’ notion of universities and other ‘seats of learning’ does not play well with the realities of our challenging environment. Rather than being connected to their communities by a narrow causeway they are increasingly embedded in those communities, supporting innovation by facilitating the flow and utilization of knowledge and experience across different sectors. In a world of ‘open innovation’ the emphasis has shifted towards knowledge flow, knowledge in motion. Enabling this is now at the heart of innovation policy and it underpins the ‘impact agenda’ in the measurement and justification for funding higher education.

It’s also a lesson we have seen played out repeatedly in the world of practice. Take the case of Boston, Massachusetts – a city which has reinvented itself repeatedly, riding out waves of growth and decline in industries as varied as textiles, gun-making, machine tools, information technology and now biotechnology(Best, 2001). Its ability to remain a centre for innovation owes a great deal to the complex web of links which it has built up over a century – it’s a knowledge-linked city. And its education system lies at the heart of its ability to innovate and reinvent itself. Around the world we’re seeing increasing emphasis being placed on building ‘ecosystems’ around education providers, enabling connects amongst the complementary players and mechanisms for allowing much higher levels of student mobility across these boundaries. And that’s going to increase.

The same is true of the research mission of universities – the growing interest in, and emphasis on, knowledge production which takes place in the context of application – the so-called mode 2 model (Gibbons et al., 1994). Far from being the guardians of knowledge held closely inside their libraries higher education providers are increasingly becoming ‘knowledge missionaries’ with students (via research partnerships, internships, and other forms of project-based learning) acting as their agents in the field.

One way in which we can already see this happening is in the role of innovation spaces as environments where such cross boundary collaboration can take place. Different labels are attached – innovation labs, incubators, accelerators, maker-spaces – but they come down to the same thing. A recognition of the need to encourage knowledge flow across boundaries and to n=engage many different players within them. We can see them as ‘stepping stones’ providing early prototypes for the kind of collaborative cross-boundary contexts within which students will move in the future.

And it’s not a one-way movement; for the wider workforce the idea of lifelong learning and continuous upgrading and updating of skills will mean a growing market for education provision. But this needs to take place within structures and environments which support learning in parallel with working – through part-time courses, online study, micro-credentials and other forms which bridge between the two worlds.

Figure 1.5. Changing learning spaces

Learning spaces is where we find our fourth shift. With innovation as a practice targeted at grand challenges and drawing on multiple strands of knowledge woven together in collaborative fashion the question is inevitably raised around the physical environment in which learning might take place. It’s not hard to think of the current model – still predominantly one which has been around for centuries in which learning takes place within a physically defined space – a classroom or lecture theatre – and where key roles are embedded in the architecture. The teacher is the source of knowledge, he or she transmits this to the attentive audience who often sit in rows like a Greek amphitheatre, absorbing and chewing on the pearls of wisdom being dispensed.

That’s changing, of course – we’ve seen growing interest in alternative models like the flipped classroom, or project-based learning. But we’re likely to see considerable acceleration in experiments around alternative approaches (and the environments they imply) which might be better suited to enable learning ICE. There’s a lot to be (re-) learnt from kindergartens where the underlying theory is all about providing ‘scaffolding’ within which children can learn by themselves through experimentation. We’re now seeing very different designs for learning spaces – not least their migration to the context in which innovation problems exist and within which skills might be developed.

A good example of a physical space created for the explicit purpose to nurture innovation and creativity is the Aalto Design Factory, founded in 2008. The idea emerged from a research project that was called the “Future Lab of Product Design” that focused on designing an optimal physical environment for product researchers and developers. Its core mission is “to build a new kind of passion-based learning culture” and support collaboration and co-creation across disciplines between students, researchers, and practitioners. The facility itself is an old wood processing technology building transformed into different spaces, that include different workshops, lecture halls, office and social gathering spaces. Its layout “inspires and encourages teachers to teach students with more hands-on problem-based methods while solving real life problems” (Munigala, V. et al., 2016).

And – thanks in no small measure to the Covid-19 pandemic – we are moving increasingly online. This has long been seen as a potential site of disruption to the current higher education model; online technologies enable massive reach (in terms of accessing students) but without compromising on the richness of the learning experience. Otherwise unknown institutions like the University of Phoenix (located in the middle of a desert but with a huge student base), the University of Southern New Hampshire (with its degree programme targeted at thousands of displaced people living in refugee camps) or Monterrey Tech which numbers a student base close to a million strong from the mountains of Mexico. Now the rapid scramble has moved institutions around the world to explore online options and the future is almost certain to involve some kind of hybrid provision rather than a return to the business as usual of face to face learning. It highlights a central question where is the locus of learning? Do we learn at an institution, or at home, or in some other context, or perhaps a combination of all of these?

Figure 1.6. Changing skills mix

We can see by now that we are not talking about incremental changes at the edge of the ICE learning world; these are big shifts, full of challenge and opportunity. Our next shift relates to the nature of the skills which effective ICE practitioners will need in the future – the ‘curriculum’ across which they will learn. What’s becoming increasingly clear is that possession of hard skills – know-how – may not be enough in a future context in which being able to effect change will be a key part of being a successful ICE player. Which requires much more understanding of people – whether in the context of why they might or might not adopt new ideas or being able to empathise with them. Design thinking has already made a big impact in ICE education by introducing the concept of empathy but there is considerable further scope for bringing in other ‘soft’ skills around emotional intelligence, influencing people, understand diversity and enabling inclusion.

The skills challenge also relates to the need to learn to think in systems terms. We’ve always known that moving innovation to scale, having a major impact, depends on systems thinking. Innovation architects like James Brindley (who built the canal infrastructure which enabled the accelerating Industrial Revolution in Britain in the 18^th century) didn’t simply start digging trenches for water to flow. He worked on pumping systems, tunnelling, locks to raise and lower water and boats, design of ships to navigate the canals, even inventing the concept of containerisation to speed up loading and unloading. Above all he knew that he couldn’t do it alone; he needed complementary assets and the skills to negotiate partnerships and alliances. If we are going to deal with the kind of ‘grand challenges’ we referred to earlier emphasize the importance of system thinking, moving from specialist- to generalist-driven curricula or their combination.

As one interviewee in the VISION research put it: “These need to be very well educated people who have systems thinking abilities, who have depth in many things. They’re not over specialised so that I wouldn’t call them generalists. They need to be more than generalists. And they really need to be systems thinkers, we need more people who think in systems and not in silos, I think what we saw in the last 20 years is a trend to over specialisation to some extent.

The skills challenge plays out across a much wider population. The future of learning will no longer be confined to people a the early stages of their lives but extend through lifelong learning. That brings with it the challenge of building capabilities to learn on a continuing long-term basis – learning to learn.

Figure 1.7. Changing role of teacher/lecturer

Our focus on the learner and the way in which they might change, in terms of the environment in which they learn, their skills development, and their engagement with grand challenges is mirrored in our next shift. How is the world of the teacher/or lecturer changing? In the past their role was as a source of knowledge, a transmitter. In the future this is likely to move away from simple information provision towards teachers being designers and facilitators of learning journeys. The role will involve several components – a curator of knowledge, a coach, a mentor; in the process we may find ourselves rediscovering the old models of universities as places where the bulk of activity was student-centred ‘reading’ for a degree. The role of the professor was to help students make sense of what they had earned – less ‘broadcasting’ of knowledge and more enabling its acquisition through tutorials and other forms of engagement.

Apart from their role in supporting learners teachers will also need to manage their own continuing professional development. And, given the shifts towards closer cross-boundary collaboration this is likely to place them in new contexts, interacting on a regular basis with the wider world in which the skills they help communicate are practised. Bringing the world of practice closer through such ‘teacher as practitioner’ approaches will help; so too will widening the scope for recruiting experience from the world of practice. Blurring the professional boundaries between ‘teacher’ and ‘practitioner’ is already happening with the growth in roles like adjunct professor and ‘entrepreneur-in-residence’ and we are likely to see an acceleration of this trend.

Figure 1.8. Changing learning products

Learning in traditional models is usually accompanied by some form of assessment and evaluation, measuring progress against external metrics like passing an exam of successfully completing a quiz. But in the future there is likely to be a shift in this whole evaluation structure – learners become what they produce, they become the changes they make. For example what better way to assess an entrepreneurship course than to review the venture they create – or at least rehearse up to pitching? Or take part in an innovation project – perhaps a new product launch or a change management initiative within an organization. Demonstrating the ability to reflect on practice and to utilise key concepts acquired during training might offer fruitful alternative pathways.

Figure 1.9. Changing evaluation landscape

Once again the mirror of this is the way in which educational institutions will need to adapt in the ways in which they evaluate and measure in order to award certification. Given the pattern outlined above, with more boundary crossing, project-based activity and the development of skills in the context of where and how they will be needed traditional evaluation models like examinations and essays are unlikely to be appropriate. Innovation is about converting ideas to value and the creative and entrepreneurial skills needed to do that may not lend themselves well to this form of assessment. Instead a move towards more project and outcome based models, involving a wider range of stakeholders in the assessment process is needed.

This pattern is changing; the International Standards Organization (ISO) is actively promoting a standard for innovation management systems but within that has begun to specific the kinds of skills which practitioners would be expected to have in the role of innovation manager (ISO, 2019). The emergence of a profession means that some form of evidence of prior learning will still be needed but so too will a portfolio of successful practice.

Figure 1.10. Technology

Finally there is the challenge of technology. Last but by no means least, this one offers significant opportunities to enrich the learning experience although the cost and scale of investment required will make it an issue of strategic priority. The shift towards online learning has already spawned a flurry of start-up activity bringing new ideas to the educational space and platforms to support video, audio and extended learning are amongst the biggest areas of growth in the late-Covid economy.

So far many of these have integrated what is currently available, making it possible to prepare and deliver at scale mixed media learning inputs and to distribute these to a wide and remote marketplace of learners. But other developments are still to come – for example in the field of virtual and augmented reality (VR/AR). Here it will become possible to configure learning environments of different kinds, transporting students to workplace situations and to classrooms, integrating virtual participants from different geographic regions, introducing avatars and even virtual ‘doubles’ of lecturers to enhance the learning experience. Machine learning might also play a key role in both delivery and assessment; for example offering interactive simulations which allow students to explore complex and challenging innovation situations as a rehearsal for the real thing.

But, as suggested above, this will not just be a matter of climbing technology learning curves. The costs of designing and implementing such learning systems and the demands placed on fast access high bandwidth communication networks will be significant. In addition educational institutions may increasingly need to rethink their role at a strategic level, including their physical footprint. Is there A role for large campuses with multiple buildings when much of the learning experience could be delivered virtually?

Conclusion

In this chapter we’ve seen the very significant shifts already beginning to take place around the basic architecture of how we enable learning about innovation, creativity and entrepreneurship. This picture isn’t pie in the sky or idle speculation; it comes from a well-informed Delphi-type forecasting process involving a wide range of experts from education, industry, public sector and policy worlds. These are well crafted science fiction pictures of the kind of world we are likely to see emerging over the next decade.

The big question that raises is around what we are going to do about it. We have the capacity to shape the future by our actions in the present, so it makes sense to look in depth at this emerging picture and pick out the elements we’d like to see, to amplify, to build in to create a positive context to support learning the key skills around innovation. And, by the same token, we need to look hard at what we don’t want to see, the ‘dark side’ implied by some of these predictions, and to take steps to ensure they don’t develop.

Acknowledgments

This chapter draws on the work of the VISION project funded under the Erasmus + programme of the EU. More details can be found at https://www.vision-project.org.