Cycle Drifting for #udrift

This summer, I’m taking several online courses, of different kinds. One or two are MOOCs (Massive Open Online Courses), depending on your definition, and another is a mobile learning course, which pushes the boundaries of what we think of as “online”. The Urban Drifting course is about learning with mobile apps, connecting data between participants. Interesting, right?

Essentially what we are doing is exploring the effectiveness of mobile applications in learning. Mobile apps are all the rage in K-12 education, if what I saw at ISTE 2012 is to be believed. But this course is different, in that we are actually out in the world – rather than investigating BYOD effectiveness, for example, we’re out in the physical environment, considering geography, landscape, architecture, etc. using mobile apps. By tracking our movement with GPS and overlaying that with images, sounds, and video, we explore how well we can learn (gather, understand data) using mobile devices.

Here’s how our course leader Dennis describes our work:

In this context we explore ideas of the “digital flâneur,” media presence, and discuss implications of mobility, social media connectivity, and Twitter-flux. This is an experimental framework open to app exploration and the extension of learning and assignment production in the environment.

The course began Monday, so this is only day four, but I’m starting to get a sense for what I want to do for a project. I’m enjoying gathering data as I cycle Portland, and I think I’ll produce some kind of “CycleDrifting” video or presentation. I have a lot of time on the bike planned during the weeks the course runs, so it’s a natural fit to pair cycling with the course.

Like I ask my students to do, I’ll post a reflection on my learning for the first week of this course on Saturday or Sunday.

If you’re interested in what the class is up to, follow the tweets at #udrift.

2 thoughts on “Cycle Drifting for #udrift

  1. This is a good representation, another point could be: positioning ourselves in an environment in order to induce and harvest our position and relationships as generative — in the sense of situating technology between us and the environment in order to investigate place and phenomena. In other words, we are defining a way of extrapolating data from everyday activities and places.


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