The impact of technologies and changing demographics on UK Higher Education
Last week I had the honour of participating in a panel discussion at the Campus Management conference in London. I joined three impressive representatives from across the sector and beyond, and we discussed the impact that technologies and other trends are having (and might have) on the higher education sector, particularly in the UK.
I really enjoy speaking at conferences about digital communications, content strategy and online engagement. But this panel in particular posed some interesting questions.
I’ve always been fascinated by the cross-sector impact of technology and other trends on the business of higher education, not just the business of marketing and communications. So, I decided to take a moment to capture some of my responses to some of the questions I was asked – as well as a couple that we didn’t have time to capture during the panel discussion.
I might even articulate my thoughts a little clearer here! So, here goes… (Note: the questions come directly from colleagues at Campus Management).
This year the world’s internet users surpassed the 4 billion mark. WhatsApp grew twice as fast as the Facebook platform and is now the top messenger app in 128 countries. With the ever-changing popularity of social media platforms and ways that students prefer to be communicated with, how do you foresee universities and colleges leveraging technology to stay innovative and competitive?
The rapid adoption of messaging apps – and the shocking amount of content shared over dark social -tells us that people want content that is personalised and deeply relevant to them. This is the kind of content that you get from one-to-one or small group exchanges, not the content that you get from mass-messaging approaches.
To really leverage such trends in smaller-group communications, universities and colleges are really going to have to grapple with the issue of how to achieve deep relevance to our audiences. That means embracing opportunities from artificial intelligence devices to process individual interactions. Technologies such as chatbots have the potential to reign supreme here, but there’s so much that we need to do to lay the groundwork to make these work.
At this moment in time, artificial intelligence isn’t actually as intelligent as we would like it to be – showy displays from Google aside. There is a massive amount that we need to do in our organisations to move towards structured content and semantic mark-up, and we need a deeper understanding of audience intent before we can really use technologies to serve back, in an automated fashion, content that connects on a level of deep relevance with our audiences.
We can start by getting smarter in our approaches to segmented communications, and gathering our own intelligence through deeper audience insights and understanding. And we can help ourselves by moving towards content blocks, structured content and semantic mark-up too, as well as more sophisticated approaches to tagging and categorising our digital content.
Another area in which our thinking will be challenged relates to brand. We’ve spent decades gaining comfort with the concept of brands and branding in higher education. While in part that’s been driven by a need for distinctiveness and differentiation, it has also moved us towards narratives about consistency in communication, single voice, and identifiable brand. But in a world of deep relevance, personalised content and automated engagements, each member of our audience can have a unique individual experience of our brand. So perhaps this ushers in a new wave of the complexity of how we think about brand narrative – or, rather, brand narratives (plural).
A lack of 18-year olds in the UK population is causing a market squeeze until 2020. International students (outside the EU) are expected to prop up the market until 2020. EU students also expected to contribute (+8% applications) but acceptance rates are forecast to be down 2.1% in 2018 EU acceptances. With a declining population of the traditional age cohort, how do you see today’s universities vying for that population? What creative ways can you see secondary and tertiary student communities filling that gap?
We need to really live and breathe our mantra of lifelong learning in higher education. It’s a phrase that we use rather flippantly at times in our sector, but I’m not sure that we see a great deal of evidence of really living up to it. Most of the programmes and experiences we offer are still a moment in time – a 3 year programme, a 1 year programme, a 3 week executive education programme. Even MOOCs are often time limited in this way and follow similar learning structures that we’re used to in a traditional sense – a 6-week programme with new modules released each week.
If we’re really to meet the needs of non-traditional markets then we also need to fundamentally reconsider our modes of learning. This isn’t just about taking existing programmes and whacking them online. Instead it’s about reshaping and rethinking what higher education learning, experience and accreditation looks like.
I sometimes think that it’s the accreditation argument that holds us in a slow-moving space. Our perceptions of how learning is accredited and valued needs to be unpicked so that we can offer a far more modular pick-n-mix style approach. This could open up access to modular learning and learning experiences from all aspects of our life, not just from traditional institutions of learning and education.
Alongside this, we also need to rethink what we define as “learning”. Does it have to be about ring-fencing blocks of time to think critically and absorb? Does this take place in other areas of our lives? How can we credit and ensure that learning in non-traditional learning spaces – our workplace, our homes, our vacations, our visits to museums, our moments of self-reflection – actually counts in a meaningful way toward a recognised “education”. In this field, I’m fascinated by some of the thinking that’s coming from the potential in blockchain technologies. This video captures this really nicely:
Lastly, if we’re to really reach out and connect with non-traditional learners then we also need to address fundamental “distrust” issues that we’ve been experiencing towards the academy and “so-called experts”. The rhetoric of politicians such as Donald Trump and Michael Gove has done a lot to damage to public trust in experts, and that seems to resonate strongest with communities that don’t have close ties to the higher education sector – actually, the very communities that we probably most pressingly need to reach and be relevant to.
There is a tremendous amount of hope and angst tied to how technology will either free up or “simplify” our ability to function in higher education. As you look at technology over the next 3-5 years – what advice would you have for those working in institutions of higher education around how to prepare for this leap?
It’s pretty important that we lay the foundations now if we’re really going to be able to leverage the potential that technology can offer us. This holds true across teaching and learning, communications and marketing, and operational uses of technology too such as HR and finance systems. To me, this means:
– We need to really start to drive the technology solutions rather than just doing what the technology companies and solutions tell us can be done. In other words, instead of going with what the tools currently make possible, we need to be setting that vision and digital strategies for what we want and need technology to do for us. As a sector, that vision needs to present a challenge to the technology companies for them to develop the solutions that we really want and need.
– We must connect a university’s strategy together and break down silos. All too often we end up in technology solution hell because we allow organisational structures and operational decision-making structures inform our approach to implementing technology solutions. One division common to almost all universities is a divide between how we communicate with students on teaching and learning matters (the VLE) and how we communicate with them for pastoral issues (perhaps an intranet, but often a whole plethora or channels and platforms managed by different departments). Another divide is the mythical “internal vs external” divide, with an insistence that we lock all “internal” content into an intranet, and all “external” content into the institutional website. And yet the line between the two is often grey. Both of these examples generates a poor user experience simply because we have structured our technology solutions around organisational structures. The solution to this begs a better approach to content modelling and thinking of our institutions as information ecosystems instead of silos or organograms.
These are some of the big areas for us to get our ducks in a row and rethink how we leverage technology. Alongside them we also have the need to adopt a more database-driven mindset to how we think about and plan our content, as well as designing more coherent and consistent taxonomies, tagging and content-structuring so that we can effectively make multiple systems work in a more integrated way.
With advances in artificial intelligence, machine learning and cognitive services, where do you see the most important areas within our universities to apply this type of technology and why?
We’re already seeing massive opportunities in this field in using and processing big data for research projects. But alongside that we’re starting to see some interesting innovations in student experience too. Take a look at what Georgia State University has been doing in the use of artificial intelligence to form an early-warning alert system for students showing signs of running into issues. What I love about their lessons though is that it clearly shows the need for an integrated approach. For them, AI provides the data-driven warning signals, but humans – and increased resource invested in such roles – must still provide the intervention and support. AI isn’t yet advanced or empathetic enough to serve that role. But one day it might be.
Big data and AI could also be used to help students select modules and opportunities. It may sound a little creepy to us right now (but then all social media sounded creepy 15 years ago and now look at the adoption stats), but there is potential for a system that gathers insights into an individual students’ interests, motivations and values based on their digital behaviours or social graph, as well as their education record, and makes recommendations on what they should study. It’s a little like Netflix recommending your next movies to watch based on what you’ve watched before…
Lastly, and perhaps most pertinent to my area of work and consultancy, is the power for such technologies and big data to provide us with detailed insights that can take our marketing and communications activity to a whole new level. We’re not great at the moment in this sector at gathering really deep and meaningful audience insights and data. We need to get much smarter in how we do this, and technologies are paving the way for this. In turn, this opens up the ability for us to deliver automated personalised content to individuals and deliver the depth or relevance that we thought about at the start of this blog post.
Don’t forget, here at Pickle Jar Communications we can help you to get your ducks in a row. We do this through:
– Advanced audience research and insights
– Content strategy development, including content structuring, modelling and personalisation
– Helping with engagement around digital transformation initiatives.
Please get in touch if you’d like to discuss how we can help your university embrace an exciting future of technological opportunities.