We leave data trails almost everywhere we go: clicking on a link, posting a geo-location tweet, searching online, friending someone on Facebook/LinkedIn, purchasing a sandwich (with a debit or credit card), and so on. The explicification (it’s not a real word, but it should be) of our activities is a somewhat recent development. A few decades ago, I could go to the library, buy my sandwich with cash, have a conversation with a colleague…and I wouldn’t leave an explicit data trail that could be analyzed and dissected. Retailers are capitalizing on explicit data trails:
…what is changing, experts say, is the rapid surge in the amount and types of digital data that retailers can now tap, and the improved computing tools to try to make sense of it. The data explosion spans internal sources including point-of-sale and shipment-tracking information, as well as census data and syndicated services. Companies also track online visitors to Web commerce sites, members of social networks like Facebook and browsers using smartphones.
Similar data trails are left by learners online. Universities – whether to lack of vision or concerns over privacy laws – have done little to improve their practices through better data collection and dissemination. Usually, educators only get as far as looking at LMS login records to see how often a student logged in or how many posts they read. Educational analytics is a poorly developed field. Maybe that’s good, though. To date, most universities have been ineffective at creating compelling visions of new approaches to teaching and learning. Better data collection might only result in perpetuating existing pedagogical models.
Additional data commentary: How data will impact the way we do business
…and The state of information visualization
6 Comments
UK supermarket Tesco turned itself from just a supermarkt to a market leader through its ruthless use of loyalty card data [ http://ouseful.wordpress.com/2008/11/06/the-tesco-data-business-notes-on-scoring-points/ ].
Google uses data relentlessly too… but on of the interesting things about Google that it can use data as part of learning algorithm, because a lot of Google services get a user to generate a training (or error) signal. So for example,typos in google search generate “did you mean?” prompts; voice searches that turn up results links users click through suggest that the correct search query was identified; things like recaptcha can generate training signals for OCR; Gams With a Purpos (GWAP) provide other ways of hlping humans play a role in machine learning…
And in education, where many of these techniques were invented…? Err, erm, whatever…
PS hmmm it seems like Dunnhumby, who look after Tsco et als loyalty cards, are also in the optimisation game, especially now [ http://www.telegraph.co.uk/finance/newsbysector/retailandconsumer/6932828/Tesco-Clubcard-company-Dunnhumby-buys-KSS-Retail.html ]
As a teacher, I’ve been hearing a lot about data usage in education, but it isn’t harvested digitalyl–instead, administrators are trying to implement “data teams” as if the educational service districts (ESD’s) were weilding a scourge at adminstrators’ backs. The problem is that the administrators, the ones in my own district at any rate, have difficulty explaining what data teams are and how they should be instituted. Add that to the fact that many senior staff members have been desensitized by countless educational movements of the moment and are now resistant to commit wholeheartedly to any new impetus in education, and I am left wondering how my district, and by association the state is going to capitalize on the potential that data gathering could represent for pedagogical improvement. I hate to see sound principle spoiled by flawed execution and wish that I knew of a digital resource to help educators gather and organize information regarding individual classrooms and individual students on a regular basis. Is there an engine that educators could/should be making use of to chart specific trends/strengths/weaknesses for their classrooms?
Tony’s comment about Google’s learning algorythm employing human assistance is fascinating. I’d missed it before and find the idea that technology is making use of humans to learn a delicious twist on the usual emphasis in education. While educators try to keep up with/ harness technology to help advance human learning, technology is being engineered to keep up with/harness humanity to help it learn–and likely is doing a better job. Beautiful–shades of apocalypse, but I enjoy a bit of irony. Thanks Tony.
Educational analytics is a poorly developed field. Maybe that’s good, though. To date, most universities have been ineffective at creating compelling visions of new approaches to teaching and learning. Better data collection might only result in perpetuating existing pedagogical models.
I agree educational analytics is poorly developed but I don’t understand why Better data collection might only result in perpetuating existing pedagogical models. Don’t you think it is promising, with analysis of data traces, it would change the learning model .
I know that D2L is rolling out it’s Analytic Toolset, so maybe they’ve seen the same sort of knowledge gap that you’ve identified. I’m not sure that merely access to more data would change anything, but the interpretation and sensemaking of data that might promote change.