How learning and digitalisation can come together for future learners

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Geoff Stead’s keynote speech at the Cambridge Summit of Education explored why we need a more radical approach to technology in education, starting not with today’s education landscape, but rather how learning and digitalisation can come together in order to solve future learners. The main elements of the speech are outlined below.


Education in a changing digital world

When thinking about the future and tech, you have to stop and take a step back and think about what's happening in the world. We've got connectivity and data flowing around the world at a pace that it hasn't before. We've got rapid evolution in front of our eyes.

The challenge for all of us as parents, as teachers, as educators, is to try and navigate this changing world. We're not quite sure exactly where the destination is, so it is a fluid moment. As a tech person, it's also quite exciting, because it's an open world to try and improve things.

Digital = Open Access

Right now, any child in any school with Internet connectivity can get access to vast realms of good quality resources, lectures from eminent professors, Wikipedia, open education resources, and open source movements which are freeing up information. This is information that can make learning happen, and this is down to digital.

Digital = Scale and reach

I'm a chief product officer at a company called Babbel, a language learning app with learners dispersed around the globe. So I'm coming from the purely digital end of the spectrum, people learning mostly by themselves and using tech to support that.

An element of digital that I'm particularly invested in at Babbel is scale: the ability to create something that can be consumed by millions. You can have 10 fantastic educators working together, building a new digital product, and if they get the right combination of learning and tech and desire to learn, it can influence millions of learners.

Digital is there, people are learning digitally. It's just not happening in schools.

Digital innovation at the edges of education

I'm particularly enthusiastic about trying out new ways of learning with tech, and I've been quite frustrated at how slow mainstream education is to experiment with emerging tech. It feels a little bit like a Mexican standoff. It's not that nobody wants to innovate. In fact, everybody does. But everybody feels that it's somebody else that needs to change first in order to allow them to be creative.

A lot of tech companies get excited about what's possible, but really struggle to embed it into the mainstream. A framework I particularly like is the SAMR model,  which suggests different ways of introducing technology into education.


The SAMR model for integrating EdTech

Enhancement

Substitution

Technology acts as a direct substitute with no functional change

At the very beginning, it's a substitution. So, you're doing what you did before, but maybe a little bit faster or a little bit easier. So this might be when you're doing homework and you email the homework back to the teacher instead of physically bringing it in, or there's a digital class register, which makes it quicker and simpler, but you're registering in the same way as before.

Augmentation

Technology acts as a direct substitute with functional improvement

I lived in California for a while. The teachers at my son's school would have them do homework, take a photograph of it immediately and send it to the teacher. The lesson would be based on the homework that had come in the evening before. So augmenting is changing the dynamic a little bit. A lot of the tech I see in schools are in these two areas, substituting and augmenting. That's not bad, it’s not a progression from good to bad, but it's helpful to recognise what you're trying to do with technology.

Transformation

Modification

Technology allows for significant task redesign

The transformation stage is where technology changes the kinds of tasks that are possible to the extent that you're creating something or building skills that wouldn't have been possible pre-digital.

Redefinition

Technology allows for creation of a new, previously inconceivable task

Redefinition might mean that you're not sitting in a classroom at all; students are creating something using technology, using a more probing, constructivist type of learning approach, perhaps across several different subject domains at the same time.


Learner centricity in digital education

Digital only really works if learners want to be there. It's different in a real class because sometimes you don't want to be there, and you come in anyway. And a charming teacher can help turn that into a want to be there. But when you are only touching them remotely, digitally, it's tough.

Luckily there are methodologies which you can use to help. You hear a lot of the negative hype about the social media sites trying to draw you in and keep you spending more time there than you want to spend. The trick is to recognise that and understand: do you use it for good? Do you avoid it? What's the way to approach it?

To give you some perspective from Babbel: We have millions of users. They are spread out all over the world. We don't really have any way of knowing what they want and why they are there. We have different methods to try to understand from this mass of different people at different ages, learning different languages, why they're there and how we could help them be there.

  • We do classic AB tests. We would have two versions of a screen and we'd give one screen to one group and one screen to another group, and see which group uses the screen more.
  • We track people's usage and we cluster people into different behaviours and then we try these experiments with the different behaviours: the fanatic regulars and the occasional drop-ins.
  • If you’re arriving onto one of our screens, you might find a customer service window pop-up. If you respond, there’s a UX researcher chatting to you live. So we can push new features and understand what learners think, or they can make suggestions.
  • We have a wish board where we encourage anybody who's using Babbel to post a suggestions for improvements.

So we're collecting all sorts of different data points from millions of people who we really would otherwise not see. These are all touch points for us to try and understand, because the reality is, none of us really know. We try to guess.

Collecting this information is one side. The other side is analysing the data. There are different theories and thinkers, some coming from the learning side, some coming from the behavioural economics side like Richard Thaler with nudge theory, approaches to learning, and flow state. What organisations like ours try and do is stitch these together and construct something that works to help keep our learners.

We closely track analytics for what our learners are doing. We try and understand their motivations. Then we try and nudge some of them to come back more often because we see that a chunk of our learners use it regularly, some don't use it very often but really want to learn. We know that if you come only once a month, you're not going to learn anything, whereas if you are coming a couple of times a week you will. So we try and find ways to steer learners back in.

In Babbel's case, we enthusiastically try and use AI, but we do it in narrow lenses:

  • Machine learning to help us build different learner profiles.
  • Behavioural economics, e.g. 'nudge' theory.
  • Natural language processing and computational linguistics - we try and understand what people have typed in so that we can give them a more helpful response.
  • Speech recognition - a key part of processing what people have said.

We're trying to be very learner-centric. We're trying to say: what is a learner's problem that AI can fix, rather than trying saying: “hey, let's do everything.”

An example I particularly like is feedback. Computers are very quick to make decisions and can make them multiple times, but they're not always right and they don't have a very good feedback mechanism.

Typically, if you're answering a question, it's wrong or it's right. It's simple. Whereas if you think of a teacher or a parent teaching language, it's not black and white. You can be absolutely right, you can be absolutely wrong, but there's a big grey area in the middle. So, if I'm only a beginner and I get more or less the right words, it’s better to encourage than to correct. How do we get that grey area into the computer?

Luckily, we have millions of examples of people who've written or spoken answers to previous prompts in the product to help us answer that question.

Keep the learner at the centre of digital

Be clear about what problem you are trying to solve, and why. Which tech? Why do you want it? Be upfront about that and accept it.

If you are doing digital things, you need to be zealous at keeping the learner central. Whether it's about design or engaging, whether it's about really understanding what their problems are. In the digital world, learners only engage if you can really make a real connection with them.


Geoff Stead is Chief Product Officer at Babbel, leading the digital learning experience for millions of digital language learners. As a learning technologist, he specialises in shaping new technologies for maximum learning impact.

Prior to Babbel, Geoff ran digital innovation teams in California and Cambridge, where he was Director of Digital and New Products at Cambridge English.

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