Thursday, 19 August 2010

Retweets and hashtags as indicators of learning

Following on from my last post, I'm searching for examples of exploratory dialogue in Twitter, on the assumption that the presence of this type of dialogue suggests that learning is taking place. I'm looking at the 110 Tweets that went out using the conference hashtag #ouconf10 during the afternoon conference session on 22 June 2010. Previously identified chracteristics of exploratory dialogue are: analysis, challenges, counter-challenges, explanations, explicit reasoning, justifications and reflection on the perspectives of others.
 The table above codes the Tweets. By far the biggest category is the retweet. We don't retweet in F2F conversation, so this isn't an identified characteristic of exploratory dialogue.
Retweeting is akin to quotation, although perhaps quotation requires more cognitive input because it suggests that the quoter has remembered something (either the quotation or where it can be found) and has identified that it could be relevant to the conversation. Retweeting does not require the use of memory, but it does help to flag what participants in the dialogue are identifying as important elements. I therefore think it can be classified as cumulative dialogue which is another (perhaps more low level) form of learning dialogue.
In cumulative dialogue: 'Speakers build positively but uncritically on what the others have said. Partners use talk to construct ‘common knowledge’ by accumulation. Cumulative talk is characterized by repetitions, confirmations and elaborations' (Mercer & Littleton, 2007, p59)
If this is the case, a third of the conference Tweets in this sample can be characterised as cumulative dialogue. Is this an example of a learning analytic?
If a retweet contains a conference hashtag this is an indicator that learning may be taking place.
I'll take a look at this in more detail in my next post.

Wednesday, 18 August 2010

Identifying learning dialogue

I've switched to a different data source in my quest for learning analytics. I'm currently looking at interaction around the OU's online learning and technology conference this June. I have access to a lot of data around this conference, but I'm currently focusing on two elements: the Twitter stream, and the text chat that took place in Elluminate during the sessions.
The two data sources are superficially similar - short textual contributions shared online over a limited period of time and focused on similar subjects. Although they have asynchronous features, and have all been archived, they are largely synchronous communications.
I'm trying to dig into these to go beyond rich description of what happened, to find some underlying patterns that may be helpful for identifying/supporting learning in the future. I am currently focusing on / flitting between four areas: language, resources, individuals and networks.
In terms of language, I'm trying to identify patterns of speech and interaction that suggest learning may be taking place. I'm currently focusing on the patterns that Neil Mercer and his colleagues identified as characteristic of exploratory dialogue: analysis, explanations, explicit reasoning, justifications, reflection on the perspectives of others, challenges and counter-challenges. And I've narrowed the focus to learning about content, rather than to learning about the tools or learning about other people - so I'm setting aside discussions about how to make sure you can hear the speaker, or which types of biscuit are best to eat in a coffee break. I know those are all examples of learning, but I'm not looking for ways of encouraging reflection on the merits of custard creams.
This takes me on to resources - because descriptions of exploratory dialogue were developed in a face-to-face context, where the resources to hand were limited. In the context of online dialogue, maybe it is this linking out that supports exploration - or maybe it is linking out and then returning for discussion that is important - or maybe the important thing is linking out that moves the discussion to another venue (if that turns out to be the case it's going to be very difficult to research).
And maybe it's a mistake to set aside the people, because I may find that learning is associated with certain individuals. That may be because they are making interesting contributions, or because they are central nodes linking networks of people, or networks of resources, or because they are contributing think pieces elsewhere, or because they are asking interesting questions. In that case, learning about people may be key, because it's important to find and follow these people. So what marks individuals out as key? Is it because they initiated the hashtag, or is it that every conversation peters out if they are not involved, or do they mark themselves out as confident/off-the-wall by initiating conversations about virtual biscuits?
So many possibilities.