The rise of personalised learning

Personalised learning can mean many things. But what are the most prevalent influences and why is tech at the core? Nicola Yeeles explores

If there has been one dominant trend in education technology in the last 10 years, it must be the move towards personalised learning. Students, like consumers, have come to expect a tailor-made digital experience. We asked some experts to explain the influences behind the development, as well as what the remaining challenges are and how personalisation might evolve and further improve outcomes.

Maximising outcomes

Educators have long been concerned about the lack of personalisation in classrooms, but why is technology so crucial in the delivery of personalised curricula today? 

Iona Clark is an English curriculum specialist at Century – an award-winning artificial intelligence education technology company, prior to which she was a secondary school English teacher in London. She explains the significance from her experience: 

“We teachers know that one of our biggest challenges is maximising the potential of our students as individuals. Many of us teach up to a hundred different learners every day, each with different abilities, learning behaviours and needs. Personalising learning for every single pupil in an accurate and meaningful way is a momentous task for any teacher to undertake, but it is made possible with the right technology.”

Elliot Gowans, senior vice president at software company D2L, agrees that technology’s role is almost inevitable given the scale of educators’ challenges:  “Understanding an individual’s learning preferences is difficult enough, but when a lecturer is challenged to do this across a whole classroom, or a learning and development professional at scale across an organisation, it’s near impossible to do without utilising technology.”

And for Dan Frost, learning technology lead for new product development at Cambridge Assessment English, the significance of technology is as such: “Simply because it scales. A machine can track an infinite number of dimensions about you and never gets tired so if you, for example, spend a day practising a skill, the machine is as alert and accurate at the end as it is at the start. Human teachers can’t compete with this scale.”

Data-informed learning

So now technology exists to provide personalised pathways through material, allowing the teacher to challenge or intervene as appropriate. This is largely due to the wealth of data analytics education technology can provide about each learner’s strengths and weaknesses. Saskia Watts, of adaptive learning technology company Acrobatiq, gives the example of digital textbook use: “Datapoints such as ‘Which objectives are my students having difficulty with?’ and ‘Which students are having difficulties?’ give instructors in-depth understanding into study habits, students’ mastery of objectives, and those who are likely to drop out.”  She believes that use of personalised learning materials like etextbooks can also support “the reading and study habits of a diverse population of students, providing them the freedom to choose their own personal learning space and work more collaboratively with instructors and peers.” Moreover, allowing students to manipulate such materials allows them to study in a way that suits their learning habits, including using dyslexic-specific fonts, or differing font sizes.

But the advances are not only having a direct pedagogical benefit; reducing heavy teacher workloads, for example, allows them to refocus their time where it matters.  Clark explains, “By automating much of the administrative elements of teaching, like marking and planning, technology can maximise the vital human aspects of teaching – allowing them to further personalise the education they offer.”

Customised learning has been influenced by a range of technologies, but especially by the advent of smartphones and tablets which require people to personally log in.  As a result, they can be identified, allowing for individualised learning, whether teacher- or machine-led. 

Frost observes that mainstream personalisation technology has been influenced by companies that offer games, streaming or e-commerce. But, he says, education is different: the biggest positive impacts on personalisation are going to be from studies of what really works and through iterative development. 

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“So, weirdly,” he explains, “I think the biggest [positive] impact on personalisation in education comes from edtech firms who are studying the impact of what they build.”  One example is the way that Cambridge Assessment English innovates through regular hackathons, which provide an opportunity for engineers and pedagogy experts to collaborate on futuristic ideas ready for piloting. The organisation also maintains that they are “strictly agile” in their product development processes, which means engineers respond to live customer feedback and release new versions of software often. It’s a responsive, iterative approach that’s familiar to those in the world of software engineering.

Personalised learning

Widening opportunities

Jim Burton, CEO of Cascaid online career programmes, also notes that a major influence has been in infrastructure: “Cloud services have evolved to bring together personal data and rich user experiences delivered via web-enabling personalisation.” Like others, he also sees the influence of the media, specifically digital advertising. He notes that, “All the major services which are advertising-driven are constantly working to deliver a more personalised user experience (UX) so ads get more clicks and we buy more things. Of course, we all think that’s a real pain but they’re leading the way in personalisation and we can learn from this,” he says.

It’s clear that personalisation will evolve alongside these other technologies and allow us to offer more exciting experiences to learners as time goes on. As Gowans states, “Education technology providers, particularly those in the virtual learning environment space, are pairing personalisation with a diversity of options for delivery of course materials. Learning analytics enable teachers to identify the type of content a particular student better engages with, and modern learning platforms offer rich content including video, interactive quizzes and gamification models to suit that particular student’s needs at that particular time. In this way, it’s far easier for educators to create these personalised learning pathways for students and trainees and provide course materials in a form and context that best fits their learning styles.”

What’s next for personalised learning?

So how is tech likely to influence personalised learning in the next five years?  “We are in the early days of this sort of service; currently version 1.0 territory,” Burton explains. “Over the next five years, however, this should mature and become the norm and expectations from students will see personalised edtech enhanced learning as the norm.” Since edtech lags behind many other sectors, the most impactful technology for education personalisation probably already exists in another industry, Frost suggests.  Perhaps there are interesting developments already happening in the aforementioned gaming and e-commerce spaces that will soon penetrate the education field.  

Moreover, he predicts that other concerns will soon overtake our interest in personalisation itself. He says, “Tech isn’t going to be the thing we talk about in the next five years. It’s going to be privacy, GDPR and who owns the data. The technology is ahead of society’s understanding of it – technically, legally and politically. This is normal; think about the evolution of seatbelts, brake lights, indicators and other safety measures on cars. But it’s what will influence how we personalise learning the most in the next five years.” Collecting and using data with integrity and intelligence is going to be key, and the winners in the race to personalise may well be those education institutions that get these essentials right.


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