Social Learning Analytics - Making sense of people making sense together

Thinking about information, together

Last time I talked about why the ways individuals think about knowledge, might impact on their behaviour, and how we could support more advanced behaviours.  Of course, this also depends on how we - collectively - think about knowledge and act on this, through our policy and the ways we structure websites, etc. For example, how education/assessment policy might encourage particular ways of thinking about knowledge.

I also gave an example of someone searching for a job – they might search for a job with a particular skill set, and then expand that set, come to know more about it, perhaps think about how the skills they have might be developed through new qualifications or experience, and end up with a better understanding of what range of jobs or qualifications they might be suitable for.  That’s hopefully a good step for them - they’ve gone from just having lots of ‘information’, to making sense of it, to having ‘knowledge’ in some sense.  But the next guy who comes along has the same problem – and that’s why trying to develop ‘maps’ and similar devices to share the sensemaking experience is so important.  It’s not about giving people the information, so it's not about trying to develop a 'directory' or a set of essential reading, it’s about trying to condense the process of turning raw data and information, into something meaningful.

Moving beyond 'hit counters' to understand information

This is important in lots of the things we do.  Raw analytics – ‘likes’, number of comments, page hits, etc. – are useful for some things, especially if we’re just trying to sell a product.  But for lots of the things the third sector is involved in, we want more, and that’s one reason we so often turn to interviews and written responses.  An area I’m interested in (and, disclosure – I’m moving to work on this at the OU in October), is ‘learning analytics’, some of which are trying to focus in on elements of this textual information in particular in the sort of social context I’m interested in.

So the question is – so what? We’ve got this 'stuff' someone else found, now what?  Well, a point we might make is that:

the world is changing so rapidly that useful knowledge/understanding (in contrast to data or information) is rarely well codified, indexed or formalized, while socially transmitted knowledge is growing in importance as a source of timely, trustworthy insight. ....[The] quality of interpersonal relationships, tacit knowing, discourse and personal passion [are] key capacities to foster, as we move in business from mere transactional relationships, to building and sustaining more meaningful relationships. (Ferguson & Buckingham Shum, 2012, p. 3)

Social Learning Analytics

So what we start to think about isn’t just information, or even trying to understand how people make sense of information on an individual level.  Instead, we become interested in fostering communities (and networks) of sensemakers, and trying to understand what they need to assist them – both in terms of content, and the sorts of ‘structuring’ that might help them, for example, whether they need more help in forging networks, or in structuring their work patterns, etc.  In that paper Ferguson and Buckingham Shum suggest five areas of ‘social learning analytics’:

• social network analytics — interpersonal relationships define social platforms

• discourse analytics —language is a primary tool for knowledge negotiation and construction

• content analytics — user-generated content is one of the defining characteristics of Web 2.0

• disposition analytics — intrinsic motivation to learn is a defining feature of online social media, and lies at the heart of engaged learning, and innovation

• context analytics — mobile computing is transforming access to both people and content.

As they discuss, there are ethical issues here, and issues with properly operationalising constructs, especially if we want to avoid ‘pigeon holing’ people in ways that don’t reflect their dynamic circumstances.  However, this sort of analytics is also a big step away from both the more traditional web-analytics, and the kinds of personality and disposition research (e.g. ‘learning styles’) of the recent past.  So it’ll be interesting to see how it develops – what do other people think?  Potential benefits, risks, blind spots, etc.?  Get in touch below the line or @sjgknight

Reference:

Ferguson, R., & Shum, S. B. (2012). Social Learning Analytics: Five Approaches. Presented at the Proc. 2nd International Conference on Learning Analytics & Knowledge, Vancouver, BC: ACM Press: New York. Retrieved from http://projects.kmi.open.ac.uk/hyperdiscourse/docs/LAK2012-RF-SBS.pdf