Fittingly after a week at the OER17: The Politics of Open conference, I am celebrating the birthday of my own ‘domain of one’s own’. I’d like to say thank you to Jim Groom and all the folk at Reclaim Hosting for their support – you are awesome!
This week saw the publication of a new book edited by David Hopkins called Emergency Rations #EdTechRations. This is a volume of contributions from dozens of individuals across sectors and below is a short description of what the book is about:
“What’s so important we can’t leave it at home?”
This book is a collection of 40 world leading teachers, academics, influencers, critics and practitioners who have answered the question “have you ever walked out the door to go to work, the shops, the gym, etc. and realised you’d forgotten to pick up your smartphone? And then turned around and gone right back for it?
It was fun to contribute my own emergency rations and I enjoyed having a writing challenge of a different kind for a change. Seeing the finished product drop through my letterbox and leafing through so many different contributions, mostly written in words, but also drawn and illustrated, made me reflect on what a productive collaborative effort this has been.
A lot of the work I do is collaborative and I know first hand that getting a large group of people to produce something specific for a specific deadline is no small task. We used a range of platforms from Slack to Google Docs and Twitter along the way and I learnt a lot from reading and commenting on drafts of colleagues and then going back to review my own.
In the end what I included only represents a small part of the content I ended up writing, but the other bits will end up in blog posts or journal articles over time.
A big thank you to David for pulling everything together!
For my part, I am going to use this experience to set my sights on more writing projects in future, both collaborative and individual. It’s been an inspiring experience to see collaboration in practice.
It’s the second week of the course ‘Learn to Code for Data Analysis‘ and we have started making graphs! Alongside my course participation on FutureLearn I am posting a short summary of my experience on my blog (you can read also my post from Week 1).
I found this week a lot quicker to get started, partly because I am now more familiar with the course structure but also because the Anaconda interface I am using is becoming easier to navigate. That was a good thing because I have less time this week. Picking tings up where we stopped in Week 1 this part of the course introduces new concepts and methods leading to learning how generate graphs using the plot function. I found generating my first few graphs and changing what they showed immensely satisfying. The data we are using this week is about the weather and the project of the week enables you to use weather data from your own location.
In order to practice some of the syntax and get more used to using the interface I have started creating my own fictional data set which I am experimenting with in a separate exercise book. Hopefully there will be more time to play with this and the weather project next week. For now, the course continues to engage and educate – enabling me to learn the basics at my own pace. One study resource that I have found particularly helpful is the weekly glossary. I have downloaded both of these and use them to help remember different concepts. See you in Week 3…
I’ve never met you, Felicia Day, but I am grateful to you for adding your voice to the story of the Internet, of gaming, of women working in tech-focused industries and for sharing your story of incredible achievement against many odds.
It’s inspiring to read how hard making things happen can be and how the generosity and engagement of your community has made things possible. It’s important I think to tell stories about living, working and playing with technology both good and bad.
If you haven’t read it, you might enjoy it. I certainly did. The only draw back is that it will probably be a decade or two until the sequel is published…
Contributing something #rhizo15 is part of my ongoing effort to become an open practitioner. This week’s topic, learning is a non-counting noun, made me reflect on how my own ideas of how we can count, measure or track aspects of learning developed.
Unlike most people who spent a lot of time in Higher Education my experience of studying and later infrequently teaching at university didn’t involve many written exams or a set curriculum. First Fine Art and then Anthropology were disciplines that afforded me enormous freedom. In the first case progress was charted by the sketchbooks filled, pictures taken, materials purchased and objects made. These units of measurement translated the ongoing process of thinking and making into external, visible signs of activity. There was no set path or goal instead we had open, critical discussions and at times the results of months of work was deemed to ‘work’, to be successful, to have meaning.
Anthropology meanwhile, while requiring more specific reading and skills, is such a conceptually broad discipline that it was impossible to find something interesting that wouldn’t be relevant. Here milestones came in the form of distances travelled, time spent ‘in the field’, interviews transcribed, maps made and diaries kept. Yet the ultimate aim of all the work was a particular quality of understanding, of knowing what it’s like to see the world through someone else’s eyes, of interiority.
‘True success’ as an Artist or Anthropologist depended on ongoing practice using tools that could be supplied, techniques that could be taught, but ultimately defied clear definition or indeed measurement. Instead of content, there was practice. Instead of grades awarded or exams passed, there was an ever growing debris of objects and information that together served as a physical record of the process of learning. The reason for why one artwork ‘worked’ while another one did not or how one of us achieved a real sense of their particular subjects in the field could never be more than guessed at, let alone measured.
Not unlike the way in which members of the Situationist International movement used what they termed ‘drifting’ as a new way to explore and chart a city (Simon Sadler’s The Situationist City is always an interesting read), making maps of spaces according to a different set of priorities and experiences than geographic maps for example, learning (journeys) can be charted in different ways. One of the challenges we face is being flexible, creative and curious enough to be able to value aspects or ways of learning that don’t fit into an existing pattern we already know about. To map or count learning not only in ways we can already understand, but leave space for the things we don’t.
I originally wrote this post and then lost it – then I found it again. So here is the original version:
Situationists, Sherlock and secrets. Thoughts for #rhizo15, on learning as a non-counting noun.
For me, contributing #rhizo15 is part of an ongoing effort to become an open practitioner. This week’s topic has made me think about a lot of different things, including how my ideas about learning have developed and how some of the technologies I now work with could be applied to things which at first glance might not be easy to track or measure.
At university I became curious about Situationism. The Situationists I was interested in were a small group of people gathered around Andre Gide who in the 1920s tried to experience the world, in particular the city of Paris, in a new way – by what they termed drifting. Simply put instead of following a map or grid to navigate the city, they would walk on foot following no pre-determined pattern, instead allowing the currents of their own minds and experiences to determine their path and speed – drifting on the currents of their city. Some of the results of this kind of practice were maps, depicting a city from a different perspective. In short they produced data that allowed us a glimpse of their city, their experience of it. I imagine that Situationists today could use things like Google Glass to help record their experiences (even if it would presumably result in a lot of circular maps and very blurry video footage, alcohol being a key part of drifting).
With the tools we have today to collect data we could probably come up with ways to track, measure or count a lot about different kinds of learning, including making, seeing and experiencing things. But the concepts that we’d use to analyise the data we collect would need to be appropriately flexible and complex. Giving a machine criteria to evaluate data of a (learning) journey without an end or aim is an interesting challenge. What I enjoy most about learning is when I don’t know where it’ll lead me.
How this came about
My concept of learning is shaped by my time at university, first on a Fine Art, then Anthropology degree. In stark contrast to those studying sciences or languages, my art degree involved no exams, a very limited curriculum of required reading and two hours of being in a particular room at a particular time each week. Studying Anthropology did involve more lectures, seminars and reading, but by its very nature trying to study our own species has enormous scope with practically nothing I could find being off-topic.
In place of content, there was practice. Instead of written exams, there was discussion. What I learnt to value most is being self-motivated, curious and reflective. Skills that still shape what I do and how I learn.
Units of measurement
During the first few years at university my progress could be measured in units of sketchbooks filled, pictures taken, new methods of making stuff tried out and by the level of mess that my studio space contained. Thinking and making as reflective, critical practice involved leaving a path of debri, discarded leftovers and treasured glimpses of inspiration. What ended up in a clean, white space three times a year for critical evaluation by peers and tutors was only a small part of the whole.
Anthropology had its own ways of charting progress or success, most notably distances travelled, days, weeks or months spent ‘in the field’, interviews taped, maps made and diaries kept. As my focus was on material culture, it also included a lot of objects examined, made and catalogued.
Secrets of mysterious enlightenment
Both of the subjects I studied at university placed an emphasis on creating a mind-set, a practice, of becoming an Artist or an Anthropologist as a specific way of being in the world. Both were supported by classes, reading, tutors and other mechanisms designed to give you the best possible chance of achieving that aim. And yet, in my experience, both relied on something that couldn’t be counted or measured, but a quality that was priced more highly than anything else. Doing all the right things, reading all the right books, did not compare to achieving it. In Fine Art this was a sense of something working – or failing to work. In Anthropology it was an understanding of what it meant to be in someone else’s shoes, seeing the world through their eyes, of interiority.
These mysterious qualities, these moments of everything falling into place, was what all the process, the thinking, reading, reflecting, discussing or doing, led to. Most of the time, you couldn’t explain why it had or hadn’t happened or replicate it. What you took away, if you were lucky, was a method, the tools to help you achieve the same kind of process or understanding again in a different way.
Deduction and data
When I think about learning and curiosity, two people I keep coming back to are Sherlock Holmes, the detective of the original stories, and Commander Data, the android officer from Star Trek. As childhood heros of mine their stories have coloured my understanding of learning and asking questions. Both rely on observation and deduction and have superior sources of information. Holmes has his own reference works and London’s institutions while Data has the computer on the Enterprise as well as his own database. Both encounter much they cannot initially explain or understand. Both are students of human nature. Each is the ‘hero’ of their own story, their character defined by exceptional abilities and knowledge in contrast with a need for a friend, their struggle with being different.
To me, they serve as a useful mental metaphor. Their stories prompt me to ask questions, to be curious. They also remind me to value what I can’t explain and don’t understand or indeed what I cannot count.
…”With policy and commercial developments firmly focused on ‘big data’ and all that entails, I was interested to come across quite a few sessions and speakers talking about how we use data in learning, particularly formal education at ALT’s Annual Conference earlier this month.
Earlier in the year, as part of ALT’s work for ETAG, the Education Technology Action Group, we had invited contributions from a range of individuals and organisations and received what I think is a really helpful contribution from Simon Buckingham Shum & Simon Knight, from the Knowledge Media Institute, Open University, UK (you can read their submission in full in this blog post from 5 June 2014). Personally, I found the way in which some of the terminology is explained helpful, for example, the way in which the concept of learning analytics was visualised”…
You can read my full article in FE News here. Published 24 September 2014.
For the past week I have been involved in running ocTEL, the open course in Technology Enhanced Learning – version 2.0. As well as helping with running the course, I have also done my bit to participate and now that the first few days are behind me, I want to reflect on my expectations of the course as a participant/organiser hybrid… .
So, first up, what am I hoping to achieve by participating? Like everyone else, this has to fit around all the other things I am doing and there are certainly limits to how much time I can spend on it. Still, participating is important to me and in an ideal scenario I would like to:
- explore how the open badges impact on my approach to the course and interacting with it;
- read a few posts each day to gain insight into what other participants are doing and thinking about;
- reflect on how this kind of course and its activities can share my own learning habits.
Thus far, and week 1 has only just started, I have some thoughts on each of these three areas:
First, in regards to the badges, I am finding that I want them! I like looking at who else has earned the same badge and I like the way in which getting a badge or trying to at least makes me more concious about what I am achieving. From a personal point of view then, they work for me – for what I want from the course thus far.
Secondly, reading through the posts of what others have contributed gives me a whole new perspective on what others are up to in regards to using technology for learning, teaching or assessment. It’s inspirational to see how many resources there are that are being shared openly and in particular I enjoy reading contributions from outside the UK and getting a glimpse of the global learning landscape.
Last, but not least, even during this first, at times slightly chaotic week, participating in the course has given me a renewed sense of enthusiasm for learning new things. Exploring random links via Twitter #ocTEL or finding something interesting in a post gives me a sense of shared curiosity. I am enjoying seeing how questions come up and get answered.
So, that’s my thoughts after a week of ocTEL 2.0. For this week, week 1 of the course, I am taking on a tutor role alongside Phil Tubman and others, but I shall still try and get a bit of the participant experience. After that – let the badge quest begin.
Recently there has been an upsurge in articles about artificial intelligence and how, according to Google’s Ray Kurzweil at least, by 2029 machines will supersede us, become better at doing the things we do every day. The idea, as I understand it, is that machines will be able to develop their own kind of consciousness, a sense of humour – in short be able to communicate with us as a fellow human being would. On the basis of the data they could have access to, they would learn from what we do and learn from what they themselves would do.
This is an interesting prediction in the context of learning, and education, as technology has a large role in shaping not only how we learn and make sense of the world, but also the way in which we live and work.
Some might consider this kind of thinking as Science Fiction or irrelevant to them. A future that looks like the Star Trek universe, in which the omnipresent computer which looks after operations is as far removed from reality as the largely peaceful vision of human kind living in harmony.
Yet why not imagine what things would be like, in 2029 or 2049, if these predictions were to come true alongside all the other technological advances one could reasonable expect by then. Things that come to mind are holographic displays, wearable or internal devices, instant connectivity, intelligent data analytics, automated every day processes – and a presumably sustainable source of energy and raw materials.
Work as we know it from manufacturing and food production, to expert professions and services, would presumably be changed substantially. Using the Stark Trek example as a starting point our expertise in engineering or medicine would be supported by sophisticated technology. Our every activity shaped and guided by intelligent machines. Our understanding of what it means to be a human being broadened by the data collected and analysed with the help of computers and networks which would make our current data infrastructure look insignificant. We would learn and teach others how to do the things we couldn’t use machines for or how to support the machines in their work. Maintenance, programming and operation of machines would become more important.
In the Stark Trek universe the absence of a capitalist economic system is replaced by a number of shared aims, such as exploring galaxies, advancing art and science, going where no one has gone before. But even in this imaginary future the human race, and indeed most races, remains mortal. Death remains a constant for all but very few. In most Science Fiction only beings that transcend the corporal plan of existence stop being concerned with mortality, replacing the need to learn and progress and make sense of linear time with a sense of being that is largely incomprehensible to us.
We endeavour to survive, improve, create and learn because we have a limited lifespan, for our children, to secure our place in history. Mortality is the great motivational force in human existence. But machines which develop their own sense of being would presumably not be limited by such corporal barriers.
If one of the devices I own were to develop its own consciousness, its own intelligence, then what would it want? To serve me as a typewriter, map or telephone? To support my activities, travels and relationships? Would my tablet want to make friends with other devices? Would it want to sleep and dream? Would it stop me from using it if it was busy? Would it want a pet?
These questions are not new of course. In Microserfs (Douglas Coupland, 1995), the lead character Daniel writes about this in his diary, reflecting the thoughts of many who work and live immersed in technology. If my machines could speak, what would they say?
So, if our devices had their own consciousness, network with each other, collecting, sharing and analysing data, then what would their aim in life be? I am not thinking about a hostile machine v man takeover scenario here, but simply the perspective of a mind quite different from our own. A machine not bound by the limits of their physical body or natural lifespan. Would they be bored like the fictional immortal characters we have created? Would they, like their counterparts in Science Fiction, play games with each other across time and space to which mortal beings would be incidental? What sort of future would they wish to create and for whom?
Learning, in my view, is all about change. We change, our world changes, and we learn to survive and succeed. We live our lives along linear narratives, making sense of our existence according to our own beliefs and experiences in the face of mortality. We have a sense of urgency, of time passing, of acting before our time is up.
So, in the future, might we see new subjects crop up not only for human learners, but also for the artificial intelligences living with us on this planet? Would there be a renewed interest in exploration of the universe? Would my tablet and I have a common hobby?
Clearly, we don’t have any answers. We cannot yet imagine what a consciousness outside our own human perspective would really be like. Similar to trying to imagine what four dimensional space looks like or how it works, our best approach is through mathematics and (computer) science. What is clear however, is that understanding the machines we create and how they work is becoming more important day by day.
This is a short video about the new LEGO house (work in progress) in Billund, Denmark. Designed by the Bjarke Ingels Group, the approach to the design is part of the LEGO philosphy – “Inventing the future of play through systematic creativity” (you can read the full info here).
It’s a really exciting idea. Can’t wait to see it become brick-reality.
Back from the ALT annual conference, this year celebrating 20 years of ALT and catching up with all the things I missed over the past three days. In addition to all the blog posts and tweets, one news items that caught my eye this morning is the Technology in FE and Skills supplement published today by FE Week. There is a short interview with me in it and a lot of interesting features with participants from across the conference, including the Learning Technologist of the Year Award #ltaward. I will also have a look at the open online platform to watch some of the already aired YouTube interviews from the live broadcast. Looking forward to next year in Warwick!