Blog Posts

discussion visualization with gephi

I’ve been playing around with gephi today, to see what I could come up with to display the discussion threads from my research data. Lots of manual data entry later, and I’ve got this:

and this:

WordPress sites are shown in red, Blackboard discussion forums in blue. So far, just a pretty picture, but I’ll hopefully be able to coax out a diagram or two that shows the difference in interaction patterns between the two platforms…

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on the role of the lms in higher education

It’s fashionable to rail against the LMS, to lament the shackles of institutional constraint and to advocate for abandoning the concept in exchange for a DIY nirvana. There’s definitely something to the no-LMS movement, because it emphasizes individual control and grassroots innovation. But, there is also a role for the LMS in higher education. If for no other reason than the simple reality that most instructors, and many students, aren’t ready, willing, or able to forge their own solutions. Nor should they be required to. The DIY hobby craftsperson ethos is inspiring, but institutions have an obligation to provide tools to enable their faculty, students and staff. The LMS is only part of that - but I think it is a core part.

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discussion network visualization

I just put together some quick network maps for the online discussions from my thesis research data. Haven’t done any analysis - just some purty pictures to see any at-a-glance differences:

Both discussion platforms had about the same number of posts and responses, but the pattern of connections is markedly different for some reason…

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aggregated metadata for online discussions

here’s a quick look at the aggregated metadata for all of the online discussions I’m using in my thesis:

About the same number of posts in each platform, with a bit more of a time-spread in the WordPress discussions, substantially longer posts in WordPress, about the same (non) use of images, more links in WordPress posts, and more attachments in Blackboard posts.

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basic metadata analysis

Here’s a quick pass at analyzing the basic metadata for the online discussions.

I plotted a few calculated values (Excel pivot tables fracking ROCK, BTW…), to try to compare activity patterns. What’s interesting in this graph is the average wordcount (green line) - low for the Blackboard discussion board threads (the left 5 items) and markedly higher for the 8 student blog (the right 8 items).

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full online discussion metadata visualization

I’ve finally entered all of the metadata information for the online discussions I’m using in my thesis. This includes the person who posts something, the date, and the size of the post. I worked through my earlier visualization mockup, and wanted to try it with the full set of data. So, here’s the Blackboard discussions (top image) and WordPress blog posts (bottom image):


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on visualizing online discussions

For my MSc thesis research, I’m working with a bunch of data collected through online discussions during a blended course. Part of the discussions took place using Blackboard’s discussion board feature, part took place on students’ blogs. One of the things I need to do is to document how the discussions played out, to try and tease out any differences between the two venues. I’ll be using the Community of Inquiry model to describe the social/teaching/cognitive components of posts, but I’ve been wanting to describe the flow of discussion as well. How do the discussions occur? Are there patterns of activity, in time or size of responses? I’ve been struggling with how to document these. In my thesis, it’s really just a glorified case study, so I’ve had to constantly force myself to stop thinking of it as controlled experimental data. What I’m doing is describing the activity within a single course, in 2 venues of online discussion.

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photos from danielle & dallas' wedding

I didn’t get copies of the photos from the borrowed camera until just recently, and just finished going through and editing. This is the first wedding I’ve ever shot, with any sense of responsibility for capturing the whole thing. Lots of rookie amateur mistakes in there. It’s amazing how fast things happen in a wedding, when you’re trying to capture it all. And how quickly the lighting goes south - the wedding took place on a beach, just before sunset, so we had amazing light for most of it, and then harsh oblique shadows at the end. I didn’t have any lights aside from the on-camera flash, so things got messy in a hurry. Thankfully, I pumped off about a thousand frames - whittled down to 80-something.

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(How) do blogs need to evolve?

Interesting discussion about the nature of blogs, blogging, and where this stuff might be going. Some comments jumped out at me:

Paul Bausch:

The whole idea of comments is based on the assumption that most people reading won’t have their own platform to respond with. So you need to provide some temporary shanty town for these folks to take up residence for a day or two. And then if you’re like Matt–hanging out in dozens of shanty towns–you need some sort of communication mechanism to tie them together. That sucks.

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Ghostery - protecting your privacy online

I’ve been using the Ghostery extension in both Chrome and Safari for awhile now. It sniffs the web pages and blocks requests for the douchey stuff that tries to track you online. It lets the good stuff through, but prevents all of the creepiness from executing. It also reports on how many tracking items are attempting to worm their way through it on each page you visit. Eye opening.

It’s free. Runs in Chrome, Safari, Firefox, and IE. There’s also a custom browser for use on iOS, but I haven’t tried it yet.

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