Rupert Ward on Badging and Digital Trust

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Backslash, New Pathways. Getty Smart Getty Smart You are listening to the Getting Smart podcast. I’m Nate McClennan, and today I am excited to have Rupert Ward join us.

Rupert is a former special advisor and project lead for IDEA, which is an amazing badging platform and free educational technology. I actually just completed my first badge on the platform, focused on the UN Sustainable Development Goals. He’s a professor for learning innovation and associate dean within the School of Computing and Engineering at the University of Huddersfield in the UK.

National Teaching Fellow, Principal Fellow of the Higher Education Academy. And I think most important, he believes deeply in personalized learning for every learner in the world. And I think we share that. So welcome Rupert. Super excited to have you. It’s a pleasure to be here. Thanks, Nate.

Yeah, and Rupert and I and Shawnee, one of our colleagues had a chance to talk a few weeks ago. And we decided after we said we should have a podcast because Rupert has a lot to share. He’s done a lot of interesting work and has some big ideas about conversations around credentialing and badging and personalized learning and how really we are ready for a shift into a much more effective learning environment for all individuals. So let’s start off and just give our listeners some context.

What got you started in this space? Was it education first that you were a learner first or were you always excited about technology? And what were you like as a learner? Okay, so I mean learning first, I would say that’s always been the case. Even when I was at school, I was always looking at doing additional learning.

I did night classes, I took extra qualifications, I did things for fun. And it’s something I’ve been doing throughout my career. I’m on my eighth postgraduate qualification at the moment. So yeah, I think maybe a learning addict would be a better phrase. I don’t know. But yeah, so I started with learning and then I sort of went through my educational process and I didn’t know what I wanted to do.

So I stayed in education for as long as I could until I decided that I wanted to be a teacher. So I went into doing that and again that was focusing on the learning side. But then actually over time I realised actually what I wanted to do was support learning rather than to teach. And I started then on a journey of how do you best support learning and technology during my working life. As evolved significantly. So I started about 15 years ago with overseeing innovations in terms of digital film courses and using Second Life to support learning.

And then from there focusing more on things like assessment feedback and technological solutions for the institution that I worked at and developing those. Which basically a lot of the work I was doing there was about understanding the learning ecosystem and understanding the processes involved in that. And the technology was very much a tool and a technique to address those parts of the system. So it was very much not led by the technology. It was very much about how can the technology help support the learning. And that led onto my work in terms of badging and micro-credentialing and personalised learning.

Got it. And so let’s dive into badging and micro-credentialing. I guess first let’s just set up some baseline definitions. Do you discern between a badge and a micro-credential and maybe a competency? How do you differ between those different vocabs? Yeah, I’ll give you some definitions of key terms I guess. So I guess the first thing to start with is to understand the difference between learning and earning.

So to understand difference between what we do in education traditionally and what we do in employment. So in education we usually define the capabilities that are being developed through what are known as learning outcomes. So we say look this is what you will have learned. This is what you will be capable of when you have studied this program of study. So the education side is about capabilities. It’s about learning outcomes. The workplace side is about competencies. It’s about applying that learning to different contexts.

So to give you a simple analogy to illustrate the difference here. Imagine a difference between learning to pass your driving test, which is education capability, and driving in different traffic and weather conditions in different countries on the other side of the road, which is applying that to a context. So that’s the competency side. So we can come back to this, but the issue fundamentally is that those two things don’t usually align very well.

So those are two key definitions. And then I guess the two that are relevant then within this conversation are badges and micro-credentials. So badges are very much about learning activities in the broadest sense that can be recognized. So a thing that you are doing that can be recognized. Now micro-credentials, as the name implies, are a way of breaking down traditionally recognized qualifications,

traditionally recognized credentials into sub-components, into parts of those. So there is a subtle difference between the two. So you could, for example, do a set of badges to make up a micro-credential. But similarly, you could do a set of micro-credentials to make up a credential. There’s different ways in which these can be used.

But underpinning both and linking between the capability and competency point is skills. The universal translator, the Babel fish, if you’re a hitchhiker’s guide to the Galaxy fan, is the skills. The skills allow you to connect between those two areas of capability and competency, and they enable you to understand both badges and micro-credentials. Got it. So the link between capability and competency, we need to link these more closely because they’re disconnected at the moment.

Skills are the linking piece. Badging is the recognition that you’ve shown, the learning activity that’s recognized, and then you may stack badges into a micro-credential or whatever level of granularity that might exist. Is that a good question? Yeah, that’s a reasonable summary of the space.

Gotcha. So now let’s think. You have been part of building IDEA, which is the largest badging organization in the world, 10 million badges in five years and 95% of countries. That is massive. So when you started that project, was that the vision to get to that size? What was the genesis of that project? Okay, so this was working for the Royal Household in the UK.

So the aspirations are always high as to what’s going to be involved in there. But I guess the challenge is what’s the context in which you are setting your targets, right? So you could set a target of, let’s say, a million people using the platform, but what’s reasonable in the space, right? So I think the metric that’s been settled on in terms of the badges completed is a good one.

We started off, and actually initially it was quite slow, the progress rate in terms of badge completion, but the acceleration was significant. And basically, you know, certainly from my perspective, it’s been predominantly organic growth. It’s not been hugely promoted. It’s not been usually marketed. But when people have become aware of it and have used it, they’ve shared it with others,

and it has utility in lots of different areas of society. So I think its popularity has come about because of its utility, because of what it can do and how it interacts with the person doing that. And so, yeah, the aim was to get to a million, to get to five million. We got to 10 million this year.

But just to give you a simple example of how the acceleration can happen in an unplanned way is, at the beginning of the pandemic, in the first six weeks of the pandemic, a million badges were completed on idea in six weeks, right? So, you know, why did that happen? It happened because people were suddenly looking for ways to learn, looking for free, exciting, fun learning that was out there.

And so it became a lot more popular pro-rata than it had been before, just because of the environment. So, yeah. And did you find, or given that there’s been 10 million badges awarded, are you seeing use cases, the different use cases? In other words, I mean, I went on there and I learned, because I went and learned about the UIN and SDGs,

just because I was interested in it, learning for pleasure, interested. Are you seeing these badges apply into that, as you talked about, learning and earning, like into the earning? Are people using it in the earning space, mostly in the learning space? What’s your sense of that? It’s used across all of it.

So, I mean, the original focus was to provide award routes for young people, sort of, roughly, let’s say, from about eight to 10 years old through to 18 to 20. So, in that formative period where they’re looking to develop ideas of where they’re going to go with their lives. So, that was the original focus of the materials. And so it’s used, for example, in delivering the computer science curriculum in the UK. But it’s also then used in universities for professional development, personal and professional development.

So, additional opportunities alongside degree qualifications. It’s also been used within degree qualifications within universities. It’s been used in local government for professional development. So, in the workplace context there, it’s been used in helping people getting back into work that have been long-term unemployed, both through government initiatives and through educational initiatives.

And it’s, yeah, it’s been used in a broad range of other contexts where it’s simply providing a re-engagement mechanism to learning. I mean, we can explore this analogy further, but one of the things I talk about in my books is about learning fitness. And it’s really, it’s a way of enabling people to access learning fitness activities. So, you see lots of adverts on television, particularly during the pandemic, but even since then, for different ways of getting fit, physically fit. Okay, this is a different way of getting learning fit, of getting yourself back into learning, getting yourself developing certain strengths in learning,

giving you a routine and a regulation within learning lots of different component parts. So, it seems that the use case really has been as part of someone’s learning ecosystem. You and I use those words when we last talked. So, there’s all these opportunities to learn. Idea fits in there in a huge number of settings as an opportunity to learn, whether that’s in a formal setting or an informal setting, and that is part of this larger learning ecosystem,

which brings me to this bigger question that you and I talked about before. So, what is your biggest interest in big unifying ideas? You have a background in theoretical physics, so I’m thinking the big idea of string theory or whatever the universal unifying ideas are of the universe. What is yours for learning? What is the big idea that will be driving us into the future or should be driving us into the future? So, I mean, if we’re looking for a grand unified theory of education,

I think what it is is we should be looking at personalized learning as that. We can only learn in the context of who we are, what we’ve done previously, our experiences, and how they then impact on how we access and engage with learning. I mean, again, coming back to this learning fitness analogy, right? You know, people have different levels of physical fitness. They have different exercises they like to do,

different routines they like to do if they’re trying to stay fit. Okay? The same is true of our education, our learning. You know, we get put through in formal education a fairly standardized exercise regime in terms of learning, right? And it’s not really delivering for most people. It delivers for maybe some people in the middle of the normal distribution,

but it certainly doesn’t deliver for most. And it’s not enabling as many people as possible to get learning fit. It’s not optimizing learning fitness, right? And if you look at what’s happened in physical fitness in the last few years, things like fitness trackers, things like having different ways of accessing fitness, you know, as exploded.

And within that, the personal trainer has exploded as a way of getting people tailor-made exercise opportunities. Now, you know, there’s a cost with that in the real world in terms of physical fitness, but in terms of education and learning fitness, a lot of that can be done online, and a lot of it can be done for free in an in fun and engaging way with gamification elements if there’s sufficient world power and effort to do that.

Right. And so, hmm, I love this analogy because, you know, I think about, I like exercise, I think about in sport, I think about physical fitness. I haven’t made that connection to learning fitness. So I like the use of those words. So when we think about being physically fit in a personalized way, we’re looking at our own statistics.

It could be pulse, it could be blood pressure, it could be strength or whatever the case may be. So going back to badges and credentialing and skills, it seems that there is some analogy towards measurable pieces of learning that are, you can see growth across to overtime, right, for any particular individual. Granularizing the learning-earning journey, right?

So granularizing it, breaking it down into component parts, a sufficient level of abstraction so you can understand what those bits are. Okay. But granularizing it so that people can make progress at the rate that they’re able to. They can get fit at their own rate. You know, it’s insane that you have to go through your education in a set number of years,

going all at the same pace, and if you don’t keep up, you drop out. If you’re going too quick, you get bored. You know, how does that work? There’s no need to do that anymore, right? All we need to do is to get people to a level of fitness at the right point in their life for them.

And given how long we work and what we do nowadays, just think of the waste in society, both productivity-wise and societally, individually, that comes about from the current system. The current system is, as Sir Ken Roberson used to say, it’s a factory model of education.

It’s based on a conveyor belt. It’s based on widgets. And there’s a lot of discarded waste in that model, right? And really what we need now is bespoke widgets. We need personalized widgets to meet lots of different societal needs.

But we also need to reduce the waste level because it has health implications. It has implications in terms of how society functions and dysfunctions. It has implications in terms of productivity. But fundamentally, it’s about people having the happiest, most fulfilled purpose for lives. And we’re just not delivering that with the current model.

Right, right. We have a standard regime. And people are dabbling. Certainly, there’s efforts being made in personalized learning across the world. So people are recognizing this.

We’re recognizing that every learner is different. The standard model worked because it’s easy in a lot of ways, right? It’s all about delivery and not much about output or results, meaning it didn’t matter how many people got it. It was that you delivered something that was standard.

So in terms of thinking about how badging, credentialing, this helps solve for this personalized world, this is a record-keeping piece in a lot of ways, right? Like if you’re going to personalize learning and granularize it, it’s not going to be a set of standard exams that someone takes at the end.

It’s going to be a much more discrete description of the learning fitness of any individual using your words. It could be a record of achievement, for example. That would be a simple way of describing it. Right. But yet the embeddedness of traditional transcripts, letter grades or number grades,

whatever the system is in the country that people are in, it’s a really sticky system. So do you think, are you bullish that the idea of personalization, it’s going to get easier and easier so that it’ll just be a normal choice to say, we’re moving away from in the US, 8th UF, because it doesn’t make sense anymore

and all the technology is there, including the technology to record, to verify, etc. Is it an ease of use thing that will move us in that direction, do you think? No, it’s not an ease of use thing. It’s a trust thing. Right. So the issue is currently that however dysfunctional the system is, there is an abstraction and an understanding of value and currency in the current system.

Okay. So when it comes to a skills economy trading model, the current system works to some extent. If you’ve got a high school diploma, if you’ve got a degree from a university, that has a shorthand, it has a conceptual understanding that people can use.

And like most of the rest of the system, which is based on qualifications, it’s a filter. The traditional model was we didn’t need many people getting through the system. So what we’ll do is we’ll just put a filter in place. It’s like a set exercise target. If you can get to that, okay, you’re in. If you don’t, you’re not.

Yeah, right. Okay. So yeah, so that’s the traditional approach is very much one of, we only need so many people and we only need them once they get beyond this level. Right. The issue in moving away from that is how do people trust in this new model?

Right. And we can come back to this in terms of badger microcredentialing more generally. But the, you know, the challenge to some extent is a bit similar to the challenge with digital currency. It’s how do people trust it enough that it gains traction in society? Right. So there’s an easy way of doing this in the learner only journey, which is you, you peg the new things to the old things.

Right. So you say, okay, well, look, we’ve got these traditional qualifications. How could they be replaced in part in whole by badges and microcredentials? How would that look? And in fact, we’re just finishing off a national project that is showing how you could do that using skills. Right.

So once you’ve got that, you can then start saying, okay, well, look, this here is equivalent to that there. You know, we’ve already been doing it, for example, in our university degrees with LinkedIn learning. We’ve said, look, if you’ve done LinkedIn learning and you’ve done this amount of LinkedIn learning, that’s the same as this amount of credit that we offer. Okay. So we’ll recognize it as that amount of credit.

Right. So suddenly you’ve got a way to say, if you’ve got things out there that meet these, these requirements, you know, that are the amounts of study different skills, things like that, then, then you can equate them to what’s already there. And then what happens is over time, you can introduce more of that into the system. And you can make the assessments and the qualifications more flexible and more personalized. Okay.

So for example, doing it in the report that we’re just about to issue, we will show an example in there of if you did a university degree, you could reduce the amount of assessment and you could replace it with personalized learning elements. Yeah. Or, you know, and in that way you can differentiate between different learners doing the same qualification. So the employer then gets something they’ve been after all the time, which is an ability to understand who best matches their requirements in terms of the competencies they’re looking for for the workplace based on their record of achievement or their journey or whatever they’ve done. Right.

And, and without, without providing that you will always have what I call a capability competency chasm, you will always have this gap between these two areas, because there’s not the translation going on there. So as soon as you get employers, and in particular parents, on side, because they can see the utility of this, you know, and both of those, those stakeholders are interested in a smooth learner earn a journey. Right. So, so once you get both of them on board in the education space and in the employment space, it becomes straightforward. It builds trust through usage.

You know, it’s like cold tap list payments or pin, pin number, you know, things like that, you know, it takes a bit of time to get going. But once it’s done, people don’t even, you know, don’t even think about it anymore. You know, the, the, the, the trust, the system becomes trusted. Right. I think this is a key element, right. So, so while the system, the current system, the traditional system has significant flaws, it has a huge benefit and that there’s trust in the system.

Right. Meaning people believe that if you have a degree from X university, it means something right. What you’re saying is build into the current system, the system that you want. So granularize it through competencies, through the skill based trading work. So that, so that over time, people see the trust, I would say percolate down at a granular level so that they’re trusting the competencies, which then is trusted by parents to say that my child is getting the things that they need.

And I don’t need to see an ABCD or whatever the marks are and employers who actually have a better view of what they’re getting because at this point, we don’t necessarily, I think when we look at surveys of companies and, and those who are hiring is that a degree doesn’t necessarily mean skill. A degree means degree. They’re not necessarily asserting. They should assert, but they don’t always assert that that employee, the newly hired employees going to be fantastic at their positions. There’s a lot of reeducation, re-skilling, upskilling, etc.

So, so let’s talk a little bit about that’s the skills themselves because some of them, like my experience getting a badge about the UN sustainability goals are pretty straightforward. I was learning about the goals, the idea platform gave me some questions. But some of the skills that were really are, I think are missing our employers are who are survey are missing are around. Can you collaborate well? Can you lead well?

Can you communicate well? Can you solve conflict? All these, I call them durable skills. This I things that persist beyond content changes. And so I’m wondering how can this new system of granularity?

Can we accommodate that? Is that possible? What are you thinking about? That’s what the national project that we’re just about to report on it shows that. So, so basically, if you want to, if you want to translate between learning and earning in an effective way, using skills, you need to think at the right level of abstraction.

Okay. And the right level of abstraction needs to be sufficiently detailed so we can understand the individual nuance parts. You’ve given some examples there, right? But not so detailed that it’s not usable day to day. So what we’ve done in terms of the model we’re using, and, you know, and this is something that can be developed that the individual areas that are covered can shrink or grow.

But what it does is it uses 25 descriptors. So six of them are subject specific. 19 of them are transferable or durable as you would refer to them. And they’re based on six different thematic areas. So basically to do with the actual information, theoretical information that you’re accessing, understanding the environment that it supplies to.

So usually a business context, for example, and being able to develop new things. So a whole range of things there to do with a creativity and problem solving, for example, and things to do with how you deliver the actual product process service that you’re, you’re providing. And elements to do with you as a person and how you’re making sense of this and elements to do with communication and, and reporting and areas like that. Right. And, and they’re based on 21st century skills categories. But what they do is it means you can translate any learning outcome into them.

And you can translate any workplace competency into them. Right. And so we’ve got then labor market information from like cast what used to be emzy burning glass. Okay. So we’re using labor market job posting information, analyzing the skills that are in there. Analyzing the courses that they’re studying and the skills that are in there and then looking at how the two map or don’t map to each other.

Right. So, so then you have that great translation between capability and competency, right from learning or earning. It’s that it’s that skills framework super interested in seeing that report when it comes out because I think that’s this is this is the elusive chasm that you are talking about. We’ve got to be able to cross this chasm and be able to translate one to the other to identify gaps and also better set up every person. So we’re nearing the end of our time. I think we could go on for hours.

I’m pretty sure I have one more question. Before we wrap up is that I know you talked earlier about tech is just tools and but and I know that there’s a lot of hype around Web three and the blockchain and how that may translate into the education sector. Useful for this grand vision of yours. Not useful. What’s your what’s your take on it?

Possibly useful. I think what I would say is in everything I’ve ever done in this space, it starts with the it starts with the learning and the learner. It starts with principles and processes and then moves to technology. It doesn’t start the other way around. Right.

So, so blockchain has has uses. So, for example, it’s useful as a way of evidencing trust. It’s useful as a way of potentially decentralizing teaching as well as learning. So, for example, you could have an individual teacher and associate the learning with those individual teachers. So, you know, so it’s a way of showing a connection between things that can be useful.

But it could also be problematic. So it could be problematic, for example, if you choose to publish everything that’s recorded on on the blockchain, because what then then happens, it becomes a barrier to learning. Right. Because, you know, if you are worried about what people think about your performance and it’s taking you 15 or 20 times to do this particular learning exercise, you know, you’re going to not want to engage in that learning exercise until you know what you’re doing. You know, you can be successful.

You’re just not going to engage. Right. So, so there’s there’s there’s real issues there in terms of unintended consequences that need to be considered. And it’s why we have to start with the ecosystem, the principles and the processes that underpin the ecosystem. And then the the technology is there to serve the the improvements that you want to see that is not the other way around.

We’re not there to serve the technology. Right. Right. I appreciate that. And I think that gets into the whole other conversation of blockchain will record all transactions by design.

It’s the self sovereignty of the user or the person who owns the information to say I can release this information to the world. And I have control over that rather than someone else has control over. And I think that’s an important distinction that those who are learning in Web 3 and understanding is that that we need to be careful about so that people still are willing to go out and try things like that’s how we learn we learn by trying. So, Rupert, this has been amazing to wrap up. I always love to ask sort of two questions.

One is what’s the big takeaway message that you would like our audience to hear. And then the second one is who is a person or persons that you would like to amplify that’s that’s doing good work in the space and is and doing good work for learners everywhere. Yeah, so I think that the key message is about self regulation self regulated learning. So underpinning personalised learning and your personal learner and a journey you need to self regulate it’s like getting learning fit you need to self regulate and that requires self reflection. So you need to understand how your environment and your previous experiences impact on your ability to maximize your potential and how you can maximize your potential through re perceiving and re appraising.

Your previous experiences. Right. So, you know, so believe to succeed, but analyze to believe to succeed, I guess would be the. And then, and I guess, I mean, two people I guess I’d highlight that in different contexts are looking to innovate and looking to develop equity and make a difference around the world. I mean, the first ones, Andrew Schleicher who’s the OECD and he manages things like the P’s of the, the, you know, the global educational performance measures there but he’s very interested in this space and is very innovative in terms of how he looks to to influence how we we provide education around the world. And the second one is is Martin Bean.

Formerly, Microsoft and the Open University in the UK Vice Chancellor there and RMIT in Australia has now recently set up the Bean Centre which is working in space and he has a huge passion for for equity and and sees the potential of this space to deliver that. I really appreciate those recommendations. We’ll put these all in the call notes and any other references that you have certainly share with us and we’ll add them to the call notes. I just want to. So, number one, thank you. I these are the things that a couple things that I took away that were new for me. I love this idea of I thought a lot about learning to earning. I don’t think I’ve thought enough about the skills gap that you were talking that the skills matching gap that you’re talking about this idea that we are we are we are thinking about capability in the learning space and the competency in the earning space and we need to find the match between those two. I love this idea of learning fitness and that there’s a lot of analogies to physical fitness that we need to think about and that learning fitness can be customized and personalized. That’s that is personalization is the Holy Grail for us.

We need to be able to meet every learner where they are to meet their full potential in the world. And then I think the third one is this idea that we need to think about ecosystems, principles and processes before technology. You’re a technologist. I dabble in technology, but that can’t come first. That has to solve the problem or the challenges that we’re finding when we when we think about ecosystems, principles and processes. And then the fourth for me is around, which is the biggest idea for me is this idea of trust. We trust in systems right now that aren’t nearly perfect and don’t meet every learner’s needs. We have an equity issue there and not every person is meeting their full potential because of it. We need to build into those systems when we’re talking about badging and credentialing so that trust percolates down to badging and credentialing, which then allows us to expand that into the larger ecosystem.

So appreciate all your time today. I hope that we can continue this conversation and thanks for all the insights and all the work that you’re doing to advance the field. It’s been absolutely a pleasure and yeah, let’s have another chat at the time. I’d love to talk further about this. Thank you.