The team behind the Manifesto for Teaching Online has just published a book! The book version (2020, MIT Press) was co-written by all the 2016 manifesto authors, and its purpose is to link the abbreviated, punchy statements of the manifesto to the large body of research and practice from which it emerges.
Online teaching has leapt from the margins to the mainstream in many universities around the world in 2020. It’s been good to find that the manifesto has held up, and I am really proud to have contributed to this in-depth exploration of how distance can be a positive principle, the way digital education reshapes subjects and practices, issues of distrust and surveillance, the recoding of education through automation and algorithms, and much more.
To launch the book, we are hosting three online events. The first is tomorrow (16 September), on the theme of ‘recoding’. The other two are ‘we are the campus’ (7 October) and ‘text has been troubled’ (15 October). All are free to attend. More details and signup information is here: https://www.de.ed.ac.uk/event/manifesto-teaching-online-launch-events
I was really happy to spend the first part of the week at the online Networked Learning conference – this is one of my favourite research conferences, and it was a really good few days.
George Veletsianos and I facilitated a session on speculative methods in networked learning – building on work each of us have been doing in this area over the past few years. A few people asked for some insights into how to design speculative methods into a research project. I wrote a textbook chapter a few years ago on this topic, and I thought I’d summarise what I see as the key ‘ingredients’ of a speculative project (in digital education.)
First, it’s important to say that there are many ways to enact speculative or inventive method – and some are explicitly theoretical in nature (see Lury and Wakeford’s 2012 collection on Inventive Methods for examples of this). I am focusing here on more applied approaches, and specifically those that can be used to think about the future of education and educational technology. These are not methods that can be implemented by following a straightforward recipe; they have to be designed in relationship to the question they are seeking to illuminate or the topic they seek to develop new questions around (see Ross 2017 for more on this). However, there are some ingredients which are likely to be significant:
A speculative question.What will it mean to teach or learn with an automated process like a ‘bot’? What learning does learning analytics not capture (Knox, 2014)? How can communities be stimulated to reimagine or reframe their understanding of energy demand reduction (Wilkie et al., 2015)? These examples of questions that have been addressed through speculative method have in common a flexible orientation to a situation which is either on the horizon or missing from current thinking around a topic or practice. Speculative questions may often focus on the future, but a focus on the future is never only about the future – it is also about articulating what is currently valued by particular people or communities or in particular settings, and what may be absent or unspoken in privileging those values.
An ‘object to think with’ (Turkle, 1997).The researcher developing a speculative method must create something with which participants or respondents can engage – an ‘object to think with’. This could be a scenario or set of scenarios, a technology like an app, a design prototype, a narrative or a combination of these. The object should be designed to provoke responses that will illuminate the topic of the research, to help construct the horizons or become aware of the absences that the questions of the research are aimed at addressing. A pragmatic consideration is whether the project will require specialist skills to accomplish it, and how the researcher might access the resources they will need. Taking the making requirements of your method into consideration early on will help you ensure you can address your question.
An audience to engage with. It is possible to make the object itself the focus of the research, without a strong focus on participant response and reaction. More commonly, however, the object, which might in its own right take considerable time to design and create, is put into a context in which it can be used, or can serve as a provocation, irritation or invitation. This context might be online, offline, or a combination of the two. The speculative object and its design, along with the responses to it, form the data from this method, so the identities and expectations of participants or respondents need to be carefully considered, along with the ethics of the approach to the object.
A way to capture and analyse design decisions and responses to the object.In some cases the responses to the speculative object can be integrated intothe object itself – as in the case of an app that gathers data, or a twitter streaminvolving a bot. In other cases, responses need to be captured for analysisvia other approaches – for example, making a video or audio recording ofa workshop; asking participants to keep a written or photo diary of theirinteractions with the object; or conducting interviews or surveys. Analysisof speculative method should analyse both the object and the responsesit generates. Decisions about how the object has been designed should be captured so that the object and the considerations informing it can be understood and shared. It may be helpful to consider the speculative objectas both an instrument and an outcome, and keep notes about the design process accordingly.
Speculative method can be a powerful approach to generating and examining new perspectives and questions, and to helping understand and shape complex topics, especially those that deal with the future. For researchers aiming to understand emerging ideas or technologies, the ability to work with uncertainty is a key benefit of such an approach. It requires, however, a willingness to take risks with the design and implementation of a research project – moving away from approaches which are well-established with clear protocols. Nevertheless, I think it’s an approach that can be carefully designed, and well-justified in terms of both quality and rigour – and I’m excited to see more such research emerging in our field.
adapted from Ross, J (2018). Speculative Method as an Approach to Researching Emerging Educational Issues and Technologies. In L Hamilton and J Ravenscroft (eds) Building Research Design in Education. London: Bloomsbury.
Knox, J. (2014) ‘The “Tweeting Book” and the question of “non-human data”’, TechTrends, 59(1), pp. 72–75. doi: 10.1007/s11528-014-0823-9.
Lury, C. and Wakeford, N. (2012) Inventive Methods: The Happening of the Social. London: Routledge.
Ross, J. (2017) ‘Speculative method in digital education research’, Learning, Media and Technology, 42(2), pp. 214–229. doi: 10.1080/17439884.2016.1160927.
Turkle, S. (1997) ‘Computational technologies and images of the self’, Social Research, pp. 1093–1111.
Wilkie, A., Michael, M. and Plummer-Fernandez, M. (2015) ‘Speculative method and Twitter: Bots, energy and three conceptual characters’, The Sociological Review, 63(1), pp. 79–101. doi: 10.1111/1467-954X.12168.
I’m pleased to announce the launch of the Digital Cultural Heritage cluster, part of the Centre for Data, Culture and Society. The cluster has been in development for the past year, and I’m the cluster lead/facilitator.
There are about 25 University of Edinburgh colleagues associated with the cluster so far, and we hope it will continue to grow as more people who are doing work in this area get involved. In addition to providing a way to amplify the University’s work in this area, we are also aiming to host workshops, showcases, roundtables and other events (including some to be co-organised with the Digital Cultural Heritage Research Network); facilitate research networking and exchanges; and develop exhibitions and teaching resources.
This is a really (really!) important time to be doing this work, and we hope there will be lots of interest in applying, even under the strange circumstances in which we all find ourselves. In addition to the project itself, the successful applicant will be part of the first cohort of the Edinburgh Futures Institute’s Baillie Gifford programme in the Ethics of Data and Artificial Intelligence. Have a look at the other four projects being advertised to get a sense of the interdisciplinary opportunities being part of that cohort will bring. Professor Shannon Vallor is leading the programme, and there are a lot of great plans being developed for the cohort.
gesturing toward a future that involves a deeper understanding of the role surveillance has played and continues to play in universities and tactics and strategies for interrupting and perhaps reducing or reconfiguring its impacts. This requires a willingness to speculate that some of the surveillance roles we have come to accept could be otherwise, along with an acknowledgment that we are implicated in what Lyon terms ‘surveillance culture’ in education. What can we do with that knowledge, and what culture shifts can we collectively provoke?
Two new things have so far emerged from the network. One is a research project called Co-designing with Speculative Data Stories. This was funded by the Edinburgh Futures Institute Research Awards scheme, and the research team (me, Amy, Anna Wilson, Jane McKie and Martin Hawksey) proposed to run ‘speculative data stories’ workshops with groups of colleagues in UK universities whose roles involve supporting, promoting and working with learning technologies. With the current closure of campuses and intense pressures on those very colleagues to support their institutions to move considerable amounts of university work online, we have had to put this project on hold – but we are hoping to be able to reimagine it in some form, soon.
The second new thing – and the prompt to write this blog post today – is that Karen Gregory and I have been successful in securing one of five new funded PhD studentships on the theme of data ethics (Edinburgh Futures Institute/Baillie Gifford). These projects will be advertised in the next few weeks – ours is called The University of Data: Ethical and Social Futures of Data-Driven Education. I am very happy, as is Karen, to hear from anyone who might be interested in applying for this! More info to follow soon, in a separate blog post.
A big part of my working life for the next few years involves the development of a new postgraduate programme, to be part of the Edinburgh Futures Institute (EFI). The programme is made up of a number of interlinked pathways, including one on Education Futures – this is the one I’m leading on. The programme will be interdisciplinary, challenge-led, and have core data and creative skills courses as well as a range of core and option courses for each pathway.
Education Futures is particularly exciting (in my view!) because it will focus on some of the key ideas and topics informing learning, knowledge and education across the whole life course, with an emphasis on understanding the relationships between data and education. I want to see the pathway appealing to people from all sectors of education and learning, including schools, workplace learning, community education, and higher and further education. Things are still in the early stages of development, but by studying this pathway, we want students to be able to:
Understand and critically examine possible futures for formal and informal education.
Analyse education’s role in shaping and responding to global challenges and social, political, cultural and environmental change.
Make critical links between education and data-driven innovation, exploring the geographies, mobilities, values, ethics and forms of measurement that come along with greater innovation with, use of, and reliance on data.
Course topics we’re currently discussing include the future of learning organisations; educating for the future; personalisation, surveillance and anonymity; policy, metrics and governance; education and work; agency and social change; participation, care, inclusion and culture; expertise, literacies, trust and data fluency – and more!