Clearly no marks for originality, but there’s my first tweet. Those which followed illustrate that Twitter for me was more about learning with and from other educators. It still is … but I digress. As I’ve been analysing the data from my research, the routes by which people come to Twitter to support their learning are rather different. My tweet above was at 18:33 on the 19th February 2009, and was prompted by a fellow Master’s course member, Geoff, who suggested I might find Twitter interesting. The path for me then began with a course (Technology Enhanced Learning, Innovation and Change), followed by a nudge from someone whose opinion mattered. Can you remember the route by which you came to use Twitter to support your professional learning?
Although discussing the paths which brought people to Twitter wasn’t a specific goal of my research study, it’s nevertheless emerging from my data that different people had different experiences, though with a few common threads. When I started to pay attention to this and wondered what it might be telling me, I was also faced with how best to represent that data. I could of course simply describe them in plain text, or perhaps summarise and tabulate the outcomes. Of course I chose neither and instead elected to take the longer, but for me, more fruitful path of attempting a visualisation.
Here are the paths taken by just over thirty people who have used Twitter to support their learning. The red(dish) rectangles are authors of blog posts, the green ellipses are interviewees and the blue(ish) button shapes are tweets. The path from each node passes through one or more other nodes on its way to ‘Professional’ Twitter. Some people mentioned how Facebook, or personal use of Twitter, or creating a class account in school provided stepping stones on the way to them using Twitter professionally. There were also influencing factors like an inspirational colleague, or having attended a conference, or being on a particular course. Some folks are just curious people and when new things come along, they are drawn to trying them out, just to see what they do and how they work. If I’d been on the vis, my path would have passed through both the ‘Course’ and ‘Colleague’ nodes, but probably ‘Curiosity’ too.
(Although several participants gave their consent to be cited by name when I present my findings, many of the blog and tweet authors above haven’t had the chance to do that, so in deference to them, I’ve anonymised everyone’s names. The labels in each shape merely provide a reference for me to be able to return to the data.)
Before commenting on what I take away from the visualisation, it’s probably important to note that there may indeed be other calling off points in people’s paths which were not mentioned in their blog posts or interviews. And obviously a tweet has limited space through which to give a full account. I’ve also committed the sin, at least from my epistemological standpoint, of data reduction in the name of simplification. For example, where a path has passed through ‘Conference,’ some of the participants were inspired by a speaker, some by a person they met, and others, having found out about the conference backchannel, wanted to find out more. Where that was clear, I’ve drawn the path accordingly, but sometimes that level of detail was missing. As always, you have to balance the need to summarise with the loss of rich detail, whichever way you choose to represent the data.
Just like for me, we can see in the vis how important other people are in providing that nudge to get us started on Twitter (and doubtless following other initiatives too). Colleagues, peers, friends (and family?) are important influences. I was somewhat surprised to see how prominent the ‘Conference’ was in providing the initial impetus; I was lucky in my teaching career if I attended a single conference a year, and that was often in my own time, at my own expense. I’m pretty sure the majority of colleagues in my school were even less frequent conference goers. Perhaps there’s something about the people behind the nodes in the above vis being proactive, and that might predispose them to being more likely to consider the potential of Twitter? Or maybe that’s just my biased reading.
Educators who take to Twitter seem to be ‘Curious’ folk; a notable number of them having explored Twitter without prompting. Perhaps even the ones who came to Twitter via having set up a school account, or were at a conference and wanted to find out what the fuss was about, are similarly curious and it didn’t come through in the data? In some studies exploring the introduction of Twitter with teacher trainees (e.g. Carpenter, 2015), once the course has concluded, only a few continue to use Twitter in their professional practice. It’s clearly not for everyone, so maybe it’s the more curious folk who are predisposed? Curiosity didn’t appear to be a factor for those providing tweets in the vis, but again, this is perhaps more likely to do with the tweet as a fragment of data, rather than being indicative of anything about the people who tweet.
Somewhat surprising was how few folk seemed to be prompted by their prior experience of social media. Yes, some began with personal use of Twitter, though only a couple came via Facebook, but no other social media were mentioned. Although I declared my pathway into Twitter was through a course and a colleague/peer, what I didn’t mention is that I’d been using the Delicious social bookmarking service for a while and had recently begun to connect with other educators through that platform. Perhaps that had sown the seed that made it more likely that I’d give Twitter a try when someone gave me a nudge. Other participants represented in the vis may have had other prior influences, maybe their son using Facebook, a news bulletin, or an article they read in a edu supplement, but that didn’t come through in the data.
I acknowledge that the visualisation masks some of the more subtle aspects within the data, nevertheless I feel it does illustrate how convoluted the paths by which people come to Twitter use can be. That said, there seems to be a limited number of nudge points which help them on their way and perhaps these might merit closer scrutiny in terms of the part they play in helping to influence people’s behaviour?
Thinking about the visualisation process
Producing the above vis took far more time than it would have done to produce a table or some plain text, and yet that might have been a good thing. It certainly obliged me to slow down and gave me a chance to think. I’ve mentioned my concerns about using a vis to summarise and the inevitable data reduction that causes, but that would be the case, more or less, however I chose to represent the data. What I can say is that in drawing each path, I was obliged to attend closely to the evidence that each participant offered in a way that would have been less likely if I’d been say, simply counting how many people were influenced by this or that.
The format of the vis was dictated more by pragmatics than anything else; for expediency I needed to use something with which I was already familiar. A London Tube-style map might have been a good option, but I’ve discussed previously why that’s a tough ask. Using a concept mapping application with its tools designed for easily connecting nodes, with the added capability to easily shift them around, or indeed have them neatly spaced automatically, had some appeal, but the difficult part is in the design, not the drawing. I ultimately settled on Inkscape, and opted for a more manual approach, firstly because, as I mentioned, it obliged me to attend more closely to each path. Secondly, the manual production process results in something which definitely appears more chaotic and messy, and I felt that remained closer to the nature of different people’s experiences than a neatly ordered concept map-style version would have. (How convenient!)
For me, there’s no question that visualisations allow you to see things differently. That might not result in better interpretations, but it does at least encourage different ones.
Carpenter, J. (2015). Preservice teachers’ microblogging: Professional development via Twitter. Contemporary Issues in Technology and Teacher Education, 15(2)