Tarun Wadhwa, Visiting Instructor, Carnegie Mellon University Ian Hart, Head of Product Category. Capita
The classroom of the future is in beta mode. Right now, there are hundreds of technologies being tested around the world. While the most hyped – such as AI and virtual reality – have yet to deliver on their promises, we are on the brink of creating powerful coaching and training systems based on machine learning that could fundamentally shift the learning experience in these critical formative years. The challenge is how to sort the fads from the genuinely useful developments. If it’s applied haphazardly, it is often damaging and a waste of money.
But if used correctly, it’s the key to unlocking what makes learning engaging, effective, and constructive. That’s because technology can be an enabler for us to explore our passions and learn in a way that works for us.
When used in the right way, tools and platforms should feel fun rather than a chore help to seamlessly align our ‘learning’ lives at school, university and work with our consumer lives, integrating learning into the everyday by harnessing our natural curiosity.
That message goes as much for higher education and adult learning as it does for primary schooling. Educational establishments and employers both need to leverage the right technology to engage learners and give them exactly what they need.
Read on to find out more about how we can optimise the experience for every learner.
Forbes declared that when it comes to digitalising education, “so far there have been some monumental failures and only moderate successes”. Although the idea of personalisation is a promising one, the problem is that it’s not yet clear how to make these systems work well, but there’s a rush to deploy them in the classroom anyway.
The example of McPherson, a school district in Kansas, is a clear example of ‘optimisation’ gone wrong. Eight months after installing a digital curriculum platform created by tech company Summit, 77% of parents expressed a preference against the new system. What went wrong? Very simply, the software brought its own share of challenges and drawbacks which were not appropriately mitigated – not least headaches, hand cramps, anxiety, and in one case, even seizures.
By letting ourselves be blinded by the concept of technology – and wanting change to happen as quickly as possible – we risk failing in our duty of care. Students can never be guinea pigs, and whilst deep personalisation must remain the guiding light of future education initiatives, we need to recognise that it takes time, patience, and numerous iterations to get there.
There are, however, proven approaches which succeed at using tech to teach the skills that young children need to learn. London-based company Little Bridge has created an online gaming platform to teach English skills to over 10,000 students around the world; GlassLab has borrowed concepts from the SimCity franchise to teach students about critical thinking, and platform Tynker teaches students computer programming skills.
Games can teach valuable life skills, but they also accept failure and encourage problem-solving when things go wrong, rather than just giving a big red cross.
In a similar vein, toys can teach children to gather new skills intuitively, without radically transforming existing school systems. Start-ups like Shenzhen-based MakeBlock and London-based Primo Toys blend hardware, software, and experimentation to create next generation toys; the latter having the most successful technology crowd-funding campaign in history with a kit designed to teach kids how to code.
It’s worth noting however, that it’s not just the tech itself that can make or break optimised learning. Maintaining a balance between the role of teachers and technology in the classroom is critical. In fact, rather that working in opposite directions, the two can complement each other well.
Using AI, teachers are able to diagnose errors and guide students through problems – helping them to understand the process and develop curiosity.
That’s what Alex Beard, Senior Director at Teach for All saw at the Rocket Ship school in San Jose, where a sophisticated computer programme learned the strengths and weaknesses of 500 different students learning via laptops – generating actionable data for human teachers.
Tech can also minimise the time spent on repetitive and easily automated tasks and give teachers the time to focus on the bigger picture, with companies like e-Rater already offer automated marking systems. It goes to show that, if you get the blend right, technology can actually reinforce what people are learning face to face.
Preparing students for future success is no easy task – and this will only become more difficult as the pace of technology accelerates. Rather than teaching teachers and students how to use individual tech tools, we need to teach them how to learn to use new technologies to supplement their ability to learn.
After all, thriving in this new world will require a different set of skills and talents than what worked in the past. It’s not going to be specialised knowledge that takes them forward; instead it will be the mastering the ability to adapt, learn and re-invent themselves and their careers.
Whilst early education provides a fundamental foundation for us as citizens as well as students, college and university offer multi-disciplinary approaches which afford us the opportunity both to broaden our horizons and focus in on our passions.
Or so it once was. Higher and further education institutions are now judged principally by how well they prepare us for our future careers – and the results in that department are striking.
Just a third of students surveyed by Gallup and Strada Education Network felt that their time at university would equip them with the skills and knowledge needed to enter the workforce. A distinct lack of personalisation and vocational knowledge is leaving young adults highly educated, but unprepared for the world of work – not to mention heavily indebted.
Universities and colleges are increasingly turning to technology to stem the tide, attract students and keep up with the competition.
But this has turned all too often into incrementalism – simply digitising existing courses, rather than conjuring up genuinely fresh thinking and new ideas.
Adding a stronger element of personalisation is key to boosting engagement which has previously been lacking – both in teaching itself, but also the other range of services universities and colleges provide. Students need personalised help both to navigate the institutions of higher learning and getting the knowledge they need, and the tools we are providing to them are only scratching the surface.
Yet we don’t necessarily need robots and AI to find inspiration from examples of how this can be done successfully. Again, it’s about finding balance: companies like Schoology, Moodle, Blackboard, and Canvas have reached great success in driving adoption of learning management systems which serve as an accompaniment to traditional teacher-led classes. Cloud technology enables broader access to courses and projects for students at minimal cost, which in turn means better opportunities.
To truly personalise learning and have it adequately reflect the needs of both learners and employers alike, we need the concept of the degree itself to change.
There’s currently very little flexibility in degrees, beyond individual module choices, meaning learners become siloed into specific fields with little opportunity to personalise.
A move towards ‘stackable’ or ‘nano-degrees’ would be a step in the right direction – but this would also require a better system of valuing and communicating individual credentials.
Companies like Parchment, the most widely adopted digital credential service, have helped facilitate millions of transfers – and blockchain technology shows real potential for other similar services – but many institutions are still not plugged into their network, and the problem is also cultural as well as technological.
Creating the ideal system is a big task. The University of California, San Diego spent almost 7,000 hours creating their MAIT, or Massive Adaptive Interactive Text on Bioinformatics.
Unlike traditional multiple-choice quizzes, MAITs contain collections of videos and documents in the shape of complex pathways students work through, with thousands of possible answers.
Long-term personalisation may lead to more projects on this kind of scale. In the short term however, further education institutions should be looking not just to make their content more digestible, but work together with business, technology, and government to personalise and make learnings as economically relevant to their students’ career paths as possible.
If businesses are to harness the full economic mobility of our workforce, flexibility and constant learning is crucial. But workers looking to upskill don’t benefit from a lot of choice as it stands, let alone personalised learning programmes.
Research from the Open University found that skills shortages are costing the UK economy around £6bn a year.
The problem is, even if the end product is digital, the thinking behind workforce training is still analogue. The focus is still on one-to-many activities like conferences, webinars, training bibles and online wikis.
The problem with these sorts of training schemes is that they require high levels of self-motivation – and often lack human contact or actual on-the-job experience to help understand difficult concepts or situations. What’s more, they often lack choice, with little regard given to the individual needs and desires of specific employees.
With the battle for talent getting hotter, improving training and learning opportunities has never been more important for businesses. A study by LinkedIn showed that 94% of employees would stay at a company longer if it invested in their career, and yet employees widely report feeling dissatisfied with the options they have available to learn new skills.
There are already technologies that can provide a leg-up here. The Open University, for example, has employed relatively common technology to develop one of the most successful distance learning platforms around. Start-ups like AVADO are using open-source software to build highly customized courses for companies based on their needs, whilst others, like Axonify and Grovo, are focused on creating “micro-learning” solutions, while education platforms like Coursera and Udacity are working with companies on more long-form content.
Interactive experiences are even more impactful. International retailer Walmart, for example, is using virtual reality to train employees for stressful edge cases and to improve their ability to empathise with customers.
Capita has found that virtual reality offers entirely new ways for employers and employees to communicate with each other.
Since 2013 we have partnered with the Army to assist in the recruitment process, and recently added the ability for prospective recruits to trial immersive experiences such as experiencing what it’s like to drive a tank or go parachuting.
We have also built a 360-degree immersive training environment to train firefighting professionals.
Beyond digitisation however, personalisation is also about having a sense of control. Other governments, such as those in France and Canada, are putting decision-making back into learning. Both distribute grants and allowances to workers for training – paid for by partner businesses – which individuals are then allowed to spend as they like, via an online platform which tracks their progress.
It’s a clear example of how self-guided learning, combined with the latest technology and strong business collaboration, can make a real difference to workplace learning.
Personalisation is crucial to boosting the learning experience. An enhanced experience is key to encouraging people – of any age – to proactively drive their own learning and engagement. This self-discovery process will propel them forward at every stage of their education – and beyond.
Technology can be a huge helping hand in this process. Whether it’s lightening the load on educators to help them facilitate better learning, analysing data to identify students’ weak points, or just making the process of learning more intelligent and relevant for learners themselves, every stage of education can benefit from the judicious use of technology.
And judicious it must be - because tech-supported learning must work in tandem with educators, not in competition with them, at every stage.
Using tech for tech’s sake is a foolhardy – sometimes even damaging – mistake. With so many new technologies appearing on the horizon on what seems like a daily basis, we must make sure that they help at every stage, rather than hinder.
Above all, in the face of rapid change, the most effective strategy for adapting to a world of uncertainty is learning how to disrupt yourself continuously. As we age and grow, learning is what keeps our minds sharp and our perspective current.
The most constructive thing we can do for ourselves, whatever our age, is harness technology to develop a positive relationship with learning – to not dread it, but see it as a benefit, and make it the habit of a lifetime.