Tag: diigo

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I’ve been a little distracted the last couple of days, as I’m presenting the paper I wrote for my final assignment for Digital Education in Global Contexts (Semester B, 2015-16) at a conference today. To be fair, a lot of the conference seems focused on the promise technology is perceived to hold for education (I’m thinking of Siân Bayne’s 2015 inaugural lecture, The Trouble with Digital Education, 8:20) and I’m not certain that my paper will be of a great deal of interest to the audience, but it is, nonetheless, a little nerve wracking. As a consequence of over thinking it, no doubt I’ll also be summarising week 11’s lifestream and adding metadata later tonight.

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Social Studies of Science. Vol 40, Issue 1, 2010

Another exploration in the pursuit of the idea of ‘imaginaries’ and how these fictions play a generative role in the culture of technology – and specifically (my interest rather than that of the article) in education.

ABSTRACT: Scholarship in the history and sociology of technology has convincingly demonstrated that technological development is not inevitable, pre-destined or linear. In this paper I show how the creators of popular films including science consultants construct cinematic representations of technological possibilities as a means by which to overcome these obstacles and stimulate a desire in audiences to see potential technologies become realities. This paper focuses specifically on the production process in order to show how entertainment producers construct cinematic scenarios with an eye towards generating real-world funding opportunities and the ability to construct real-life prototypes. I introduce the term ‘diegetic prototypes’ to account for the ways in which cinematic depictions of future technologies demonstrate to large public audiences a technology’s need, viability and benevolence. Entertainment producers create diegetic prototypes by influencing dialogue, plot rationalizations, character interactions and narrative structure. These technologies only exist in the fictional world – what film scholars call the diegesis – but they exist as fully functioning objects in that world. The essay builds upon previous work on the notion of prototypes as ‘performative artefacts’. The performative aspects of prototypes are especially evident in diegetic prototypes because a film’s narrative structure contextualizes technologies within the social sphere. Technological objects in cinema are at once both completely artificial – all aspects of their depiction are controlled in production – and normalized within the text as practical objects that function properly and which people actually use as everyday objects.

At this point, I have to be totally honest and admit I haven’t got round to reading this yet. It looks as though it could shed light on the intricacies of how fictions influence reality, of how imaginaries can work as construction tools. I hope to get time to read it more closely this week – but it’s a busy, busy week..

“The term ‘data’ functions as a powerful frame for discourse about how knowledge is derived and privileges certain ways of knowing over others. Through its ambiguity, the term can foster a self–perpetuating sensibility that ‘data’ is incontrovertible, something to question the meaning or the veracity of, but not the existence of. This article critically examines the concept of ‘data’ within larger questions of research method and frameworks for scientific inquiry. The current dominance of the term ‘data’ and ‘big data’ in discussions of scientific inquiry as well as everyday advertising focuses our attention on only certain aspects of the research process. The author suggests deliberately decentering the term, to explore nuanced frames for describing the materials, processes, and goals of inquiry.”
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Another great read this week – Markham (2013) suggests ‘data’ acts as a frame, through which we interpret and make sense of our social world. However, she adds,  “the interesting thing about frames, as social psychologist Goffman (1974) noted, is that they draw our attention to certain things and obscure other things.” Through persistent framings, particular ways of interpreting the world are naturalised, and the frame itself becomes invisible.  So is the case with ‘data’, the frame of which Markham  views as having transformed our sense of what it means to be in the 21st century, when experience is digitalised and “collapsed into collectable data points”. These data points are, however, abstractions, which can be reductive, obscuring rather than revealing:

“From a qualitative perspective, ‘data’ poorly capture the sensation of a conversation or a moment in context.”

Certainly, this is reflected in my experience of the Tweet Archivist data analysis of our tweetorial last week.  As such, I particularly enjoyed Markham’s call to embrace complexity, and to reframe the practice of inquiry as one “sense–making rather than discovering or finding or attempting to classify in a reductionist sense.”

“the complexity of twenty–first century culture requires finding perspectives that challenge taken for granted methods for studying the social in a digital epoch. Contributing to an infrastructure of knowledge that does not reduce or simplify experience requires us to acknowledge and scrutinize, as part of our methods, the ways in which data is being generated (we are generating data) in ways we may not notice. Changing the frame from one that is overly–focused on ‘data’ can help us explore the ways our research exists as a continual, dialogic, messy, entangled, and inventive process when it occurs outside the walls of the academy, the covers of books, and the written word.” 

Markham also writes of another strategy for reframing research, which is as a generative process achieved through collaborative remix. Here, the focus is on interpretation and sense-making rather than on findings per se:

“Using remix as a lens for thinking about research is intended to destabilize both the process and products of inquiry, but not toward the end of chaos or “anything goes.” The idea of remix simply refocuses energy toward meaning versus method; engagement versus objectivity; interpretation versus findings; argument versus explanation. In all of this, data is certainly available, present, and important, but it takes a secondary role to sense–making.”

I thought it was apt to include comment on that part of Markham’s paper here, owing to remix’s position within our last block in relation to notions of community cultures, but also because in a sense it speaks to ‘new’, more experimental forms of authorship, which have been a focus in the course.

“This paper looks at how data is ‘made’, by whom and how. Rather than assuming data already exists ‘out there’, waiting to simply be recovered and turned into findings, the paper examines how data is co–produced through dynamic research intersections. A particular focus is the intersections between the application programming interface (API), the researcher collecting the data as well as the tools used to process it. In light of this, this paper offers three new ways to define and think about Big Data and proposes a series of practical suggestions for making data.”
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A couple of points from this paper seem relevant this week.

1. The tools we use when researching ‘limit the possibilities of the data that can be seen and made. Tools then take on a kind of data-making agency.’ I wonder what the influence of the Tweet Archivist API is on my sensemaking of our data.
2. Data are always selected in particular ways’ some data are made more visible than others and the most visible doesn’t necessarily align with or take into account what was most valued by and meaningful to users. ‘It is important to remember that what you see is framed by what you are able to see or indeed want to see from within a specific ideological framework.’ What did we value most in our tweetorial (obviously different things for different folks)? We still need to construct research questions that focus on those things most important to us, even if the data are less readily available.
3. ‘Visibility can be instrumentalised in different ways, depending on the interests of those seeking to make something visible. Visibility can be useful as a means of control, it can be commercially exploited, or it can be sold to others who can exploit it in turn.’ How are we exploiting visibility in education?
4. The monetisation – or making valuable in other ways – of data makes the data itself unreliable. Helen suggests this in her blog post, where she muses that perhaps if she’d known what aspects of our behaviour in the tweetorial were being analysed, she would have ‘gamed it’.