Activity #2 – Conole’s questions
“How can we use learning analytics to foster more effective design practices?”
Learning and social analytics are important in understanding how people interact with your online content. In my world, where I create content for people I may never meet, I can use surveys to ask people about what they liked or didn’t like, found useful or found irrelevant. But, with analytics I can see where people stopped participating or what path they chose through the information, and potentially how this affected the learning outcome. I’m not assigning any grades, so the information I would look for is never user-specific.
The School of One scenario is also very interesting, and an exciting example of how we can use analytics to create a personalised learning approach that targets the areas we need the most support. I think it’s learning analytics at its best, and I would be interested to experience it as a student.
“What are the ethical issues around the use of learning analytics?”
Before reading about the “Klout kerfuffle” (Sengupta, 2011), I would have had a few concerns around this but I hadn’t imagined the scenario that developed with Klout. With any analytics, privacy is important. I think there’s a fundamental difference between tracking individual users interactions (which you can connect to a name or account) and collecting generic interaction data. And, while I feel comfortable with most analytics that are captured in order to improve the user experience, I don’t want to live in the analytics bubble that Eli Pariser spoke about.
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Sengupta, S. (2011, November 13). When Sites Drag the Unwitting Across the Web. New York Times. Retrieved online: http://www.nytimes.com/2011/11/14/technology/klouts-automatically-created-profiles-included-minors.html.
Posted in: Week 12: Social Analytics
Allie 10:26 am on November 23, 2011 Permalink | Log in to Reply
I like how you point out how analytics can be an effective supplement for surveys. It reminds me of one of the old adages of anthropology – what people *say* they do (in your case, surveys), and what they *actually* do (say, as perceived through analytics) can often differ. Both are significant pieces of data, and the points of difference and overlap between them can be illuminating.