Monthly Archives: January 2010

Course-based ambulant social communities

An interesting idea coming out of a meeting with my friends from UHI Millennium Institute. UHI are about to roll out “campus”-wide wifi across all of its fifteen campuses and one-hundred or so Learning Centres covering the entire North and West of Scotland’s Highlands and Islands region. How can such big investment bring benefit to the users, i.e. Learners and Teachers?

Most students own a handheld device that is wifi enabled. With reasonable granularity between access points, these students can be geo-located on campus, in buildings and floors. Students can also be identified by courses they signed up on. Hence we know their peers on these courses and can bring them in touch. Although these courses are distributed across the different locations that UHI operates in, students on a particular course or module can be bundled together into a course-specific wifi subnet, on which the devices then register. This will enable wifi devices to recognise the presence of peer devices which can be location enhanced by adding the geo-location where that device currently is.

Here are some short scenarios that are possible from this:

– Student A can ’see’ (gets notified) that another student of their course has just entered the building on another campus. That peer student now appears as ‘online’ and available. Student A can use subnet-based chat to ask a question about an assignment.

– Student B needs help and sends from where she is (the library) a subnet broadcast message to all other online peers.

– Student C sees that Student D is a floor below in the canteen, sends a message to ask what’s on today’s menu, and whether Student M is with them. “I’ll be down in a minute”.

On the basis of this, ubiquitous connectivity that shows location information a la Google Latitude (where your peers are) and permits subnet chat, social connectivity becomes independent of computer rooms and static locations. Learning networks become ambulant (walk-in walk-out, moving) social communities.

For the institution a swarm analysis could show where students are most likely to congregate: the canteen, the library, by the coke machine, in the courtyard (smoking)? This could lead further to improvements in the estate services.