June 26, 2007

Learning in an Attention Economy

Attention Please

Tony posted about attention on the web. This is a great topic. I posted about attention and learning in September of 2005 when I heard a discussion on the now defunct Gilmor Gang. In the post I said...
I immediately thought about the learning aspect of the attention.xml. I have been looking at adaptive learning models and how they can improve learning. Two key considerations are prior experience and on-task performance. If one could log or maintain a history of these things and convey that back to a web based system that could provide customized learning objects or resources, this might be quite powerful.
In an "attention economy" where so much information is coming so fast, educators, trainers, and instructional designers will have to facilitate effective learning content. I see this as a great thing. The competition for the right information, at the right time, the right size, and in the right context will drive training departments to continue to be relevant. The attention of the learner will be naturally limited, (isn't it always) and the irrelevant content will be ignored (as it is now). The new interesting thing to me is that we (we being the learner, not a controlling dictatorship before we start a flame war) can now begin to manage or track that attention and use that historical data to improve our interactivity with content and social networks as it relates to identified performance outcomes. We can also incorporate practice opportunities for a lot of the knowledge work that we do, like writing a blog, solving a problem, or creating a web site.

These are all things that we spend our attention on and if that attention could be analyzed we could undoubtedly begin to make decisions and engage decision support systems or new learning management systems to assist us with our performance outcomes. I know this is vague and kind of out there, but there is a lot of research in Intelligent Tutoring Systems and Adaptive Learning that shows us that significant learning improvements can occur through basic adaptive frameworks. These frameworks can be both machine-based and instructor-based support systems.

If a social network holds learners attention it is probably due to the relevant interaction they are getting from those participating in the network. But then one has to wonder if you are getting the learning outcomes that you need just by engaging in the network? Maybe so... One question that might be asked then is ... do you put the content in the social network? Do I post my video to my new Facebook site.

Some have mentioned speed as the key driver of training in this new web 2.0 world and that is important when you consider how long it takes to create learning modules now, but I really am thinking that it is more about timing. Isn't it really about providing your peers (learners) the information they need, right when they need it. So that might involve pulling out old content and adapting it to the new context, it could be a blog post about the new process, or it could involve creating an elaborate simulation that they can use to improve skills they will need for years to come... but it has to be effective in improving performance.

3 comments:

  1. Hi Lee,
    I just came across your blog while doing some research on intelligent tutoring systems. In fact, I work for a software company that had developed precisely what you are talking about: an adaptive learning platform based on ITS principles.

    I appreciate your blog and commentaries. You are absolutely right in that social networks are able to keep a captive audience because to interactions... I believe that is the difference between eLearning and ITS Learning.

    Be back soon
    David Abitbol
    uMind

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  2. David,

    Thanks for the nice comments. The ability to integrate (seamlessly) these frameworks into the socail web or web 2.0 is likely how we will be able to continue to improve the effectiveness of learning solutions. There is still a lot of work to do before these system can dynamically support the process, but it seems that we are much closer.

    Lee

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