Before I write further posts as part of my viva preparation, I thought it might be helpful to provide a quick overview of what my thesis involves. The sensible way to do that – and the one requiring least effort – is by sharing the …
“BEST. PD. EVER!” Some teachers make bold claims for the way that Twitter supports their professional development, yet research into this area is rather limited. This study sought to gain a better understanding of the practices involved and the part that Twitter plays. It uses a sociomaterial sensibility informed by actor-network theory (ANT) to unravel the complex webs of relations which form, break apart and reform when knowledge practices are enacted in the mediated arena of Twitter.Read More »
In earlier posts, including this one, I’ve attempted articulate what flânerie involves. Like the urban wanderer, explorer, observer and chronicler of city life, I’ve approached my research as flâneur. Initially, that was in attempting to find an alternative way of describing my ‘ethnographic’ approach to Twitter. Initially, only somewhat playfully, I called this a ‘flanography.’ More recently, I included it within my thesis; it had become a ‘thing!’ What struck me at the time, and what was recently reinforced during a supervisory meeting, was that I need to articulate clearly what distinguishes flanography from ethnography. In this post I want to thrash around a few thoughts how that might be done.Read More »
Here at SHU there’s a couple of PhD researcher competitions on at the moment as part of the forthcoming Doctoral Showcase series. There’s the ‘Three Minute Thesis’ heats and local final, but the one that attracted my interest was the ‘SHU Doctoral Research Image Competition 2018.’ I’ve been producing visualisations throughout my study and I had in mind one I wanted to produce, but hadn’t because I knew it would suck up time. The competition provided the final impetus and although I suspect from the information and instructions, the organisers are expecting photographic images, I thought I’d have a shot at pushing the boundaries.
We welcome attention-grabbing images to intrigue, inform or excite a lay/non-specialist research audience about your research. Images may be arresting, beautiful, moving or even amusing but they must relate to your doctoral research project.
Entrants are also allowed 150 words of accompanying text; here are mine:
The flâneur of 19th Century Paris was an observer and chronicler of city life. In exploring the bold claims some teachers make that ‘Twitter is the best PD ever!’, I called on the spirit of the flâneur to guide my ethnographic approach.
One of several methods I employed in the study was participant observation; this image is formed from tweets collected during that process. Each of the districts or ‘quartiers’ contains tweets on one of the emerging themes, each typified by a magnified example.
Since flânerie inspired my approach to observation, analysis of the data, and presentation of the findings, I sought an image which spoke to that activity. Although somewhat playful, creating this image, and other visualisations during the study, was more than simple representation. On each occasion I found the attention to compositional detail which was demanded also yielded additional analytical insights.
Having set thesis drafting aside pending feedback from my supervisors, I’ve returned to my data … and each time I write that phrase ‘my data,’ it bothers me. It’s really not my data at all; I don’t have any particular rights over them, other than, with the help of a bunch of other folk. having assembled them together. Anyway, I’ve returned to my flânografie and am casting my eyes back over the notes I made during the seven months of participant observation. These were the episodes which appeared on Twitter, sometimes in my timeline, sometimes through using search terms on Tweetdeck and often as a result of someone pointing me towards a tweet or post they thought I might find interesting.
In this instance I have Andrea Stringer to thank for pointing me towards the blog post which prompted me to write this. “22 Ways To Use Twitter With Bloom’s Taxonomy” was written by Aditi Rao, @TeachBytes on Twitter. Usually when an item like this came into view, I’d make some notes describing what I saw and adding a few reflective comments. Back in January of 2017 when I read Aditi’s post, I remarked neither on Aditi’s brief introduction to the graphic, nor on its contents. What struck me more was the effect it was having on other people and how they might be learning from it. My attention was therefore drawn to the ways in which other people had interacted with the post and their reactions to it.Read More »
Several happenstances intersected to bring me to the point where I’m embarking on a different approach to my analysis which is more coherent with my overall study, as I outlined here. The purpose of this post is to put a little more flesh on the bones of the initial phase in which I explore data.
There were two strands which, though unconnected, brought me to this point. The first, as I mentioned in the previous post, was Martina mentioning the process of ‘data walking’ by Eakle (2007). The second was exchanges with Deborah, and me becoming intrigued by her blog title, the édu flâneuse and then captured by the quote with which she subtitles it:
“For the perfect flâneur, for the passionate observer, it’s an immense pleasure to take up residence in multiplicity, in whatever is seething, moving, evanescent and infinite: you’re not at home, but you feel at home everywhere, you’re at the centre of everything yet you remain hidden from everybody.” Baudelaire
When I began to explore further, there seems to a small but significant (and eclectic) body of research which draws on the notion of the flâneur in different ways. First it might help if I outline the origins:Read More »
As I mentioned previously, one of the outcomes of my last supervisory meeting was that I need to produce an overview or summary of how my analysis will be conducted. An extension if you will to the doc in which I summarised my data: