 Thank you, Aiman. Thank you very much to Aiman, Mark and colleagues for inviting me to give a keynote today. It's a real pleasure. I hope you can see the slides, OK. I have a fair few of them and I have a video later on. So if there's any problem with the visibility, please just shout. Yeah, my name is Shandbein. I'm from the University of Edinburgh. I thought I'd start with a nice little bit of Edinburgh eye candy to try and lure you all to come and visit the city at Christmas a mae'n gweithio, a'r ysgolwydd yma, o'r ysgrifennu ar roedd y maenifestog yma i leidio at amgarwyd â'r ysgrifennu Edinburgh a'r ysgrifennu o'r ysgrifennu, ac mae'n fwy o'n hoffod o'r ysgrifennu o'r ysgrifennu yma i'r ysgrifennu ar ysgrifennu o'r ysgrifennu. So Amon has already introduced me, but I am the director of our reasonably newly launched centre for research in digital education, which is based in the School of Education. So we have kind of four research themes that we address in our research centre, learning analytics, higher education policy, digital culture and children and technology. So do check out our website if you get a moment. I also teach on our masters, our MSc in digital education, which is one of the first distance education programmes to be offered by the University of Edinburgh big programme. We've got about 200 students on it across 40 different nations. So this is all just by way of giving me a bit of context to what I want to talk about in my keynote this morning. In terms of the wider context of what we do at the University of Edinburgh, I suppose we're quite fairly active in the field of digital education, particularly in terms of online and distance learning. So we have about 64 fully online masters programmes at Edinburgh and we've had a 10 year period of quite heavy investment in online distance learning in the university. So we now have about 2,500 distance postgraduate students. I've made this on a PC and the Mac has kind of crunched it all up, so sorry about that. But we have an expansion target for online distance learning. We're hoping to have a few years from now 10,000 distance students. So strategically we've been really quite invested in this area of digital education. We were one of the early European universities delivering MOOCs and we now have a portfolio of 35 MOOCs across three platforms and again with a kind of modest growth ambitions in terms of MOOC delivery. At the moment we're getting close to 2.5 million MOOC learners. We're also growing distance PhDs and we have a really quite strong I would say practitioner and research communities in digital education in the university. So I'm telling you all that because I think Edinburgh is a pretty good place to be doing this stuff but it's also a good place in which to be thinking about what it means to conduct digital education and how the digital is shifting and changing what it means to teach both now and in the future. So this is what I'm going to be talking about this morning. I want to introduce our manifesto for teaching online so I'll just explain how that came about and what we were trying to do by developing a manifesto for this area. And I'm then going to dig into two particular areas that that manifesto looks at, teacher automation and the notion of university space. And think about how research in digital education is asking us to really question those two particular areas. I could have chosen others and it's quite hard when I talk about the manifesto to kind of choose which areas to drill down into. But for me I think these are a couple of the most interesting and important ones facing teachers and researchers in digital education at the moment. So we first wrote our manifesto for teaching online back in 2011 and it was written by a team of about five of us who were teaching on the master's programme in digital education. Don't bother trying to read this. I'll show you a video in a minute which will make it a little bit more accessible. But what we felt at the time was that digital education needed some provocation. We wanted to write some short punchy statements which would provoke new kinds of critical thinking around the area of digital education. In particular we wanted to counter a tendency in the field not to adopt critical approaches but rather to sort of default to these sort of instrumentalist and determinist ways of thinking about technology. And we wanted to build a critical approach to practice based on our experience as teachers within our masters in digital education and our experiences researchers in this field. When I talk about instrumentalism and determinism I'm really referring to a paper written by Hamilton and Freisen back in 2013 where they describe digital education as being dominated by these two particular discourses. Instrumentalism which sees technology as kind of neutral means for ends determined independently by their users so technology as a kind of tool if you like. And we see this discourse a lot in the kind of terminologies that we use around the field of digital education when we talk about things like putting pedagogy before technology, using technology to enhance learning, developing tool kits for innovative learning. We're talking about the technology as though it is simply a tool to apply to a stable existing set of practices. And then when we talk about determinism again I'm drawing on Hamilton and Freisen's paper where they talk about technology, this is another perspective on technology which sees it as driving social practice. And we must as humans adapt to technological change so when we talk in our field about harnessing the power of technology or using technology to transform education we're talking about technology as though it's taking us in new directions and we have no choice but to follow it. And these are two kinds of perspectives which I want to challenge a little bit as I talk this morning. I should say that all the references I'm going to use in this paper I tweeted them earlier today, they're in a Google document so if anyone out there is on Twitter and could retweet that tweet that would be great there's a link to all these references so you don't need to be trying to write them down. Okay so when the 2011 manifesto came out it got a fair bit of publicity actually particularly in the states following an article that was written inside Higher Ed. The journalist there said that we were trying a different kind of advocacy tack which was suited to the viral culture of the modern web. It was a really nice article for us but I think it was based on a misunderstanding we weren't necessarily advocating digital education. We were trying to provoke thinking around digital education which is a subtle bit important difference I feel. People were saying it was the most exciting document to emerge in 2012. Some people were questioning whether we really needed this kind of pop culture meme like approach to thinking about digital education. Others were saying it had important implications for the ways in which universities and schools thought about providing educational services. So it made a modest but reasonable splash at the time. But then when it came to that earlier this year we felt that things had really moved on substantially since 2011. By 2016 we'd seen the rise of the wave of MOOCs, we'd seen a big focus of attention on open education in all its various forms. We'd seen a rise in questions around automation, big data, machine learning. So we felt it was time to revise and rewrite the manifesto at that point. At which point we did introduce some new kind of manifesto points on these topics. I should say I brought some manifestos along with me and in the break I'm going to put them on the table outside if anyone wants them. If they run out just email me and I'll send you some. Okay, so before I move on I wanted to actually let you see what we actually say in the manifesto and how we say it by showing you this video which was produced by one of our PhD students, James Lam, which presents the manifesto in a kind of audio-visual form. So this video is about three minutes long. I hope the sound will be okay. This essay will explore this notion of the urban planner and cultural heritage studies with mobile augmented reality using select locations in New York City as the environment to be mediated and mediated. Perceive this sea change, we have to look at a range of sources which come together and intersect in various ways. Diologic structures of the web are really not a natural fit with many of the profoundly individualist assumptions that we make about what it is to be. Social and perhaps educational interaction is best understood as being fundamentally dialogic. Discussion among people as to the extent to which or what can or should appear to replace the teachers, replace the teachers, replace the teachers. I'm just going to, as I say, dig into two particular aspects of what we've tried to address in the manifesto. I haven't really got time to look at digital textuality, to look at assessment and various other aspects, but I'll look at these two particular clusters of points. So we have a couple of new points in the 2016 manifesto relating to this issue of the automation of the teacher. Just to try to prompt a new kind of thinking about what it might mean to automate the teacher function, it might mean to automate aspects of what we do as teachers. I was a little bit dismayed, I have to admit, in that video when James faded my voice out saying replace the teacher, replace the teacher because that isn't my intention at all. But I think it's an interesting way of thinking about where we're going in terms of artificial intelligence and big data when it comes to education. So really this cluster of points was designed to address this kind of upsurge in research interest in really in the last couple of years around the automation of work and around the automation of professional work. So this was the key theme of the World Economics Forum conference in Davos earlier this year was on the fourth industrial revolution. The sense that all kinds of work is shifting through the incursions of big data, through improvements in machine learning algorithms. The famous study that was done in the Oxford Martin School about three years ago surfaced this idea that 47% of US jobs are at risk of computerisation. So this seems like a sort of massive shift in the way we think about what it means to be a professional is coming up over the next few years. And it's to do with how we choose or decide or are forced to interface our professional work with technology. Just to give a few examples, IBM's Watson supercomputer has been kind of pitched as it will soon be the best doctor in the world. So this is the IBM Watson artificial intelligence which will be, it's argued, uniquely able to work across the massive influx and emergence of health data and will be able to function as a diagnostic engine beyond the wildest dreams of human doctors. The Watson supercomputer in the context of healthcare is a diagnostic engine, it's not a doctor. And I think this is an important theme which emerges through our discussions of the automation of professional work. What we need to think about is how humans work with and alongside technology. But what we're seeing in much of the kind of dominant press kind of discourses around this field is this kind of fantasy of super-session. No more human doctors. We're going to have supercomputers. So that's the IBM kind of doctor. Then some of these kind of, I don't know, interventions in automation are much more bottom up. So this is one of my favourites. It's the world's first robot lawyer. And it's developed by, as these things always are, a Stanford graduate based in the UK called Joshua Browder, who developed an automated kind of legal services bot on the internet. It's fantastic. I signed up to this a couple of weeks ago. You sign up and then it's designed to help you challenge parking tickets. It does some other things as well, but the parking tickets thing is great. Unfortunately, I don't think it applies in Ireland yet. It's US and UK at the moment. But basically, you probably can't read that text. It asks you a few questions about where your car was parked when you got the ticket. Could you read the signs properly? Was it clear what was going on? And then it generates a letter for you to send to your council to challenge your parking tickets. Fantastic. 66% success rate, apparently, in challenging parking tickets. And then it feels like journalism, for example. So there's been a lot of focus on that recently as well. The Associated Press Agency is now publishing 3,000 news articles every quarter, which are generated by an artificial intelligence rather than by a human journalist. As one of the Guardian journalists wrote a few months back, maybe these artificial intelligences working in journalism, they won't necessarily be about writing high quality articles, but they'll be about personalising articles. So if you could have an artificial intelligence which personalised a news article and told you the example that uses here is exactly how your family will be affected by a war in a different country, that's something that could not be achieved by a human writer. So as with all these things, there are losses and gains. But to return to our core topic today, which is teaching, the work that was conducted at Oxford a few years ago on the likelihood of the computerisation or automation of jobs I don't know if you can read that, but it's suggested that the likelihood of teaching and educational professionals' work being taken over by computers is 4%. It's very, very low, only slightly higher than health professionals, whereas in other jobs such as sales and more manual tasks, it's very much higher possibility. Of course, this is because teaching is a highly creative profession, it's non-routine and it's very social. But I found it interesting when I was researching this to look at how the economists talk about the automation of education. So in this particular University of Oxford report, sorry, there's a bit of a long quote, but it talks about education being typically a low productivity growth sector because the teaching methods are typically labour intensive, use limited technology and labour costs rise when wages in such sectors have to compete with other sectors where technology is raising productivity. So they say, in one sense, the rising share of national income spent on education is not a huge problem because rising productivity and wages in other sectors allows us to afford it. So basically, as we get wealthier, we can choose to continue to find education to a high level, but then it seems to me that that's quite a big if. But then they go on to say, on the other hand, it could be that there will be technologies which will increase productivity in education and drive down costs. And then they use the examples of lecture capture. These reports often talk about MOOCs and provision of education on a massive scale or online distance tutor light, online distance education. Often, these aren't things that we would necessarily count as teaching. So on the one hand, we're saying we can choose if we want to socially to fund education, but we might also want to look at how we can use technology to increase efficiency. So I think it's a very kind of torn discourse and it's often very odd with itself in terms of how technology and automation of the teacher function should come together. So just to give, I think there are various kind of, I want to give a very quick overview of some of the ways in which, as the teaching profession, we are currently thinking about technology as standing in for some of what we do. So learning analytics is probably one of the most prominent examples at the moment, how we use data about our students to help us understand and improve their education is something that many of us are quite interested in, including myself. I think what we need to think about learning analytics as being is a kind of inscribing, or inscribing the agency of our teachers onto data. So instead of teachers having this kind of tacit understanding and awareness of their class and how they're progressing and where they might be stuck and what they might need to do to proceed, we are using data to kind of visualise that in a very different way. And that is about how we are reconceiving and reconceptualising what it means to teach and what teacher professionalism might consist of. Similarly with intelligent tutoring and adaptive learning where we are looking at ways in which computer software can simulate a human tutor. Again, there's a very clearly cost-efficiency driver often associated with intelligent tutoring. Lecture capture is another one. I don't know if you have much lecture capture here. We're just currently investing in it in quite a big way at Edinburgh. We're spending millions on putting lecture recording into 400 big lecture theatres. Again, this is a way of reconceiving what it means to teach, isn't it? I think, I mean, the teacher will no longer be present or be expected to be present in the room with the students but will be exist in different ways in relation to the student body. Automated assessment and algorithmic marking is another interesting one by which I don't really mean the automated marking of multiple choice questions but the capacity of machine learning to enable us to automatically mark essays, for example. There's been a campaign against this in the US which has been running for three or four years now which has been signed by many thousands of academics including Noam Chomsky, that's the one I've highlighted down the bottom there, against this idea that we should ask our machines to mark our students' essays. And then in the school sector, the behaviour and award systems have really become quite popular over recent years. I don't know whether you have much use of Class Dojo, for example, in Ireland, in Scotland and England. It's big. It's a way of automating the ways in which teachers manage the behaviour of their students and it's a way of opening up the record of student behaviour in the classroom directly to parents. So there are potential issues there around surveillance and so on. Plagiarism detection systems, one of the most widely used learning technologies we have. Again, it inscribes the teacher's capacity to understand and address where a student is plagiarising. It inscribes that agency onto a machine in a way which is often problematic and has been critiqued quite widely. We're seeing a rise now of campus-wide artificial intelligences. So Deakin University, for example, now uses, again, IBM's Watson to function as an answer engine for students across the whole of the Deakin campus. In fact, just last week, Pearson announced a partnership with IBM and Watson to use Watson as an adaptive learning tutor across all the Pearson Education Suite. Finally, automated teaching assistants. I don't know if you saw the case at Georgia Tech last year where a professor on one of their computing science courses without telling the students, again, used Watson to design an automated teaching assistant, set that loose in this course of 300 students and then there's a big reveal at the end of the course that guess what, this TA had been an artificial intelligence all along to mingled kind of horror and delight. We have a similar, actually not a similar, quite a different development at Edinburgh at the moment in terms of our teacher bot which I've spoken about elsewhere and I can answer questions on later if anyone's interested. So I think for me to make this kind of conceptual shift from thinking about what we do with technology is being about using technology as a set of tools to thinking about technology as somewhere we inscribe our agency as teachers is quite an important conceptual shift because for me it's important to bear in mind that the means by which we inscribe our agency onto these technologies is often highly mediated by venture capital, by big commercial companies like IBM, Pearson and so on who won't necessarily have the interests of teachers and students at heart in the same way that we might do as teachers. So Ben Williamson writes really fantastically on this stuff and points out that there's this huge investment of venture capital going into ed tech at the moment and we need to think about that and about how we respond to that landscape of heavy investment and heavy technology as teachers. I think there are various problems and issues that kind of emerge around this area which is heavily driven by computing science and often as I've said the cost efficiency or the apparent cost efficiency benefits of automation. I think sometimes these technologies tend to render the teacher invisible. I've been looking at quite a few of these systems diagrams of artificial intelligence systems and adaptive tutors and so on and it's often really hard to see where the teacher agency is positioned in these diagrams. Again the visuals aren't great here you probably can't see that so well but you can usually see where the learner is in these diagrams it's usually somewhere around the centre but it's very rare to see where the teacher and the expertise of the teacher is coming in to the system. It's usually a very heavily black boxed under something like pedagogical model or so on. I think that's an issue and something that we as teachers need to think about and address and I think associated with this there is a kind of the politics of algorithms is something that we need to address so I would recommend to you the work by Introna and Hayes if you haven't already seen it who they do something really interesting methodologically actually in that they interrogate one of the algorithms driving turn it in plagiarism detection and then they put the functionality of that algorithm up against an ethnography that they have completed of a group of international students I think it was at Lancaster University and they show in this paper which you'll find in the Google document how the winnowing algorithm within Turnitin actively functions to constitute international students as plagiarists when they aren't and as other UK based students as not plagiarists when some of them are so I think in terms of our capacity as teachers to be able to interrogate algorithms and how they work within our learning environments is something that we need to be addressing as researchers, as educational developers we need to think about how do we learn to get good at this stuff another interesting paper just earlier this year from Carla Perotta and Ben Williamson again interrogating cluster analysis as it's used in learning analytics and the way in which some forms of learning analytics will they say a stimulus circular way that the expert knowledge of data science is needed to support the forms of learning which are surfaced by data science so there's this kind of closed circuit whereby particularly reality is advocated through research which makes that research kind of a condition of understanding so I think that this is a really interesting strand of research and I would like to see kind of more critical algorithmic kind of research in education generally I think the other thing that we need to kind of think about is why might we want to do why might we want to engage with the automation of teaching I continually go back to this quote from Patrick Super as you can't see it here from 1966 where he says that this was back in 1966 he was saying in just a few more years millions of school kids are going to have access to an electronic equivalent of Aristotle will all have access to automated tutors that can guide us through our studies so there was this kind of strongly democratising kind of impulse behind automation there which is continues to be followed up by researchers now so you can see that reference I'm referencing here the report on intelligence unleashed that came through from Rose Luckin and colleagues at UCL earlier this year where again as Patrick Super was doing in 1966 they talk about the value of one to one human tutoring as being the most effective approach to teaching and learning and probably not many of us in this room would deny that but then they go on to say unfortunately one to one tutoring is untenable for all students not only will there never be enough human tutors it would also never be affordable all of this begs the question how can we make the positive impact to one to one tutoring available to all learners across all subjects my problem with that paragraph is that it assumes that it's inevitable that we will never be able to afford one to one tutors for everybody rather than acknowledges that this is a social economic and political choice our elite students the students who go to Oxford, Cambridge other elite institutions do have access to one to one tutoring so I think for me this is a kind of a nice example of kind of determinism and a kind of solutionism if you like where a problem is constructed as an inevitability and technology is then posed as the answer to that problem it's a really good report in some ways but there are aspects of it which I think are unhelpful so it's not surprising then that over the history of digital education over the recent history of digital education there's been a strong resistance to this sense in which the quote from Andrew Feinberg the goal of corporate strategists is to replace for the masses face to face teaching with an industrial product which is infinitely reproducible and the response as Feinberg was commenting back in 2003 is a kind of mobilisation in defence of the human touch and I think we have about a decade ago we saw more of this people were just saying no I'm not doing digital education I want to be a body in a classroom with my students and I want to see their faces and hear their size and hear the scratching of their pens and that's what real teaching is Sue Clegg one of my favourite papers actually in the area again 13 years ago now where she talks about the need to introduce a critical pedagogy approach into what we called e-learning back then one which refocuses attention away from the functionality of e-learning environments back to the core relations between students and teachers and the conditions in which they find themselves again there's a lot to sympathise with in this perspective but I think it's 13 years down the line it's become quite problematic to see e-learning environments over here and human teachers and students over here and to see those two things those two groups being in binary opposed to each other in a binary way and in 2016 I think where we need to look is at the space in between at the points at which students and human teachers become entangled with technology rather than being in opposition to it so there's this famous quote from Arthur C. Clarke which is a really very popular quote very familiar one to us where does this leave the human teacher any teacher who can be replaced by a machine should be on the face of it everyone goes yeah that's true teachers but actually I think it's a deeply problematic statement it assumes it assumes that deficit in teachers can be addressed by automation and it assumes that machines are capable of superseding teachers under certain conditions and for me this is one of the big issues that we have to work against as teachers is this sense that teaching can be superseded by technology I think we need to move to a position where we're seeing an entanglement of teachers and teaching and students with technology rather so I mean Tara Fennig and Richard Edwards work in this area is terrific and as Tara Fennig has said recently the point is that material things are performative and not inert machines have an agency so they will act together with other types of things and forces to exclude invite and regulate particular forms of participation in enactments some of which we term education so methodologically I think I will keep going back to this quote from Andrew Pickering from some years ago now where he says although traditionally disciplines don't do this but we need to try to see double we need to try to see the human and the non-human together rather than trying to strip one away from the other and I think that's quite a big challenge for research in digital education in the current moment there's an article in Wired which addressed these kind of issues a few a few months back saying much more simply everyone doesn't really realise that everything on the internet is a mixture of automation and humanity that's just how the internet works so that's kind of where these two very brief kind of points were coming from the idea that we don't need to see automation as impoverishing education if we see technology as an entanglement with teaching we can see it positively but we do need to think about it critically and we need to think about how machine learning and artificial intelligence and analytics are recoding, reforming and reframing what it means to do education but I think associated with these two points are a couple of other ones which I think are also important one about online teaching need not be complicit with the instrumentalisation of education for me is one of the most important statements in the manifesto it's working against this idea that there's somehow some kind of neoliberal performance kind of instrumentalisation agenda that we're seeing affecting the way in which higher education is governed at the moment of seeing online education as being complicit with that and I don't think it has to be that's about what we do as teachers and researchers when we work within this highly technologised space I've just flagged, again it's on the google document that hopefully you'll be able to link to but if you want to read some more of these specific manifesto points they are there in the work of myself and my colleagues at Edinburgh so I have about another ten minutes I want to use that to talk about another aspect of the manifesto which relates to the changing conceptions and shifting nature of university space in the digital era so again we have quite a few points in the manifesto which try to kind of shift this position that online is some kind of second best option I think we open the manifesto by saying online can be the privilege mode at distance is a positive principle not a deficit we have some points on space being continuing to be important online but it can be about distance in space but it can be about distance in time political and effective distance so really this is coming from again a body of research in spatial theory which talks about how in the current era we need to think about space as something which is becoming something which is emergent not something which is fixed and given so Rob Kitchen and Dodges book on code space if you haven't already read that one it outlines changing conceptions of space from Euclidean space space which we can measure and is objectively perceived to relational space which is about space which is contingent and produced through social relations to space which they call ontogenic ideas of space which is really a focus on how space becomes so if we see the university not for me it was being quite a rat this theory has really helped me think very differently about what it means to do distance education if we think about the university not as a place or a set of buildings or a campus but rather think about it as a set of practices and a set of relations that fundamentally shifts what we think about when we think about distance education it means that the space of the university is genuinely a global space which is enacted through the practices of our students who may be on campus and may not where is no longer a simple question in education I would say I'm going to skip over this bit so we need to drawing on mobility's theory think about the university as a space of flux and flow by which and I'm quoting from Sheller and Urie's work here on mobility's theory host, guest, buildings, objects all this stuff are contingently brought together to produce certain performances in certain places at certain times and I think that applies really nicely to the university so for me one of the most important critical kind of takings from this area of theory is this idea about sedentarism so again Sheller and Urie kind of foreground this notion in which the emergent mobility's theory undermines sedentarist's theory which treats as normal stability meaning a place and treats as abnormal distance change and placeness so we need to kind of work against this kind of what I think is still a really endemic sedentarism within universities where we do tend to think about what happens on campus as being the authentic academic experience and what happens off campus as being somehow other so we see this kind of I think distance education as a term itself discursively others distance education assumes education is what happens on campus and distance education is what happens online and we need to try to shift this and I think one of the ways in which we enact this sedentarism as universities is in our publicity and our promotional materials and we do this a lot at Edinburgh because we have a beautiful campus a beautiful city so we continually kind of use it as a way of framing and publicising what it means to be a university and I would argue that it's through this kind of fetishisation of the campus that we construct to kind of insiders and outsiders by depending on this kind of bounded space which we see as the authentic university space so how can we shift that to take account of digital space so Edinburgh actually last week an email went around to all students who were on courses in which someone had been diagnosed with measles I don't know if you've had the measles outbreak here but it's been quite a big deal for us but this email went out to our distance students as well so it's been gone in Tanzania, in Australia the students they they thought it was hilarious but I was just like this isn't okay you know it's not okay to assume that the on campus experience is the normal normative experience of being a student at Edinburgh so we had a research project two or three years ago which actually asked this question what does it mean to be a student at Edinburgh but not in Edinburgh and we asked us some of our distance learning students to send us images of their study spaces and stories about where they studied and what it meant to study even though these are the students who had never come to the university but very much felt themselves to be part of the university and we got this very nice kind of mixed picture of what it means to be a distance student many of our students were very kind of anchored in highly domestic spaces this is one of our students at the time we just had a baby his university was that bed and that laptop with that baby others were talking about how their space their university space was the kitchen table with the baby snorting on the side other students talked about their connection with the university and with the city as being about a question of diaspora so we had quite a few students saying that they had a family history and a family heritage issuing from Scotland the quote I've given you here is a student who was based in the US who traced his family back through three waves of migration from Scotland to the US and he ended by saying by registering on this online program with Edinburgh it was a kind of virtual homecoming for me so there's a strongly kind of sentimental connection to the university which was nothing to do with being present on campus other students were very what you might expect from distance students, highly mobile professionals engaging with their course from multiple countries, multiple cities multiple continents sometimes studying all over in hotel rooms so these were students who were constructing the space of the university on buses and coffee shops in hotel rooms at airports so I think I think we need to think seriously about what it means to be a student in higher education in a digital era and start to try to rethink what the space of the university in particular constitutes and that's what these particular points in the manifesto were trying to address culminating in what I think is probably my favourite manifesto point which is don't succumb to campus envy we are the campus and this is a kind of call to arms really for our distance students to feel they are the campus, it doesn't matter where they're based they do constitute the university again there's a couple of papers I've highlighted in the google doc which specifically and directly address this particular research project so before I end I just want to explain why we produced a manifesto why didn't we just write a series of research papers or make a video or make some blog posts or whatever and we were quite kind of influenced by what Latour says about what it means to create a manifesto he says it makes explicit a subtle but radical transformation in the definition of what it means to progress that is to process forward and meet new prospects not as a war cry for an avant-garde to move even further and faster ahead but rather as a warning, a call to attention and that's really what we were trying to do by writing this particular manifesto it's a call to attention a call to think seriously and critically about the big social, political pedagogic kind of movements that are currently shaping our field and how we want to address them as researchers but also as engaged and committed practitioners and on that point I'll end with a link to the references for this talk and to my email address if you want to follow up on anything and thank you for listening