I have just installed a FireFox addon called Dispute Finder. Dispute Finder is an addon developed by Intel Research and UC Berkley that highlights disputed information on a web page and displays alternatives to that disputed claim. It uses both crowdsourcing and curated resources to try to expose you to alternative views about what you are reading.
As my Masters has progressed, I find myself becoming increasingly interested in adaptive learning systems and the role that technologies could play in shaping a users personal learning environment. Now, I am no computer scientist and when I hear words like ontologies being thrown around I have to admit my head begins to ache slightly. The depth of my knowledge of semantic web technologies doesn’t go far beyond a high level flyby of FoaF and RDF . Nonetheless, I remain interested in advancements in recommendation systems, both technical (semantic) and human (folksonomies) and the implications they could have for learning and constructing knowledge.
More and more on the web we are seeing personalized recommendations pop up for us to explore, often based on our past behaviours or, increasingly, recommendations provided to us by our social networks. Amazon recommends books to me not only based on what I have bought or browsed before, but also what other people who have bought or browsed similar titles to me have found interesting. Facebook will recommend friends to me based on who is already in my network, and adjust the information I see about that network based on my viewing habits (and some other variables, I am sure). When Facebook introduced a real time stream a few versions ago, it did so with a News view and a Live view. At the time I wasn’t sure what the differences were, but after using it for awhile the advantage of the News feed becomes clear. The News feed is content that the system deems to be more relevant to me – it is a filter to help control the tidal wave of network information (I have Clay Shirky in my head saying “it’s not information overload – it’s filter failure“). And most of the time, it is right.
I am intrigued by what it means for learning if some of the construction of these connections is being done by technology, and how educators can assist learners in setting up environments that are conducive to this kind of semi-organic discovery. On one hand, these types of recommendations help to bring order to the chaos and may open up paths for exploration that may not always be obvious. On the other hand, they also set up the possibility of developing echo chambers. If the only information I am being exposed to is information congruent with my own views, then how can I be expected to become a critical thinker? After all, being critical often means being able to discern between two opposing points of view. How can you do this if you are only being presented one point of view?
Which brings me back to Dispute Finder and why I find this project interesting. Dispute Finder seems to depart from the general trend of recommendation engines on the web. Instead of recommending things it thinks I will like, it shows me information that may not be aligned with my own views, which opens up a possibility for me to learn.
via interview with Rob Ennals on Spark
Adaptive learning, disputes, and breaking out of echo chambers by Clint Lalonde is licensed under a Creative Commons Attribution 4.0 International License.