It’s not often that you find a graduate thesis that is actually fun to read, but that’s exactly what I found in Revealing individual and collective pasts: Visualization of online social archives by Fernanda Bertini Viegas, an alumna of MIT’s Media Lab. The bibliography alone is worth the trip; she does an amazing job of pulling together a critical mass of the credible literature on online social interaction (which can be hard to find amid all the garbage that’s churned out). Beyond that, her empirical research into visualization tools is fascinating. There’s a lot here that we can use to improve online learning environments.
In this first post, I’ll review some high-level lessons that can be gleaned from the paper regarding best teaching practices in today’s learning environments. In my next post, I’ll follow up with some analysis about how this research can be used to improve those environments.
Since most of the material for this first post comes out of the background section of the thesis, I’m not going to make much of an attempt to reconstruct the narrative of the relevant parts of the paper. But the set-up is very nice and worth looking at for just a moment. She starts by showing us city scenes–a crowded street and an empty one. She asks us to come up with adjectives to describe those public spaces. Then she shows us screen shots of a news reader (the old Usenet news, not a feed reader) open to various news groups and asks us to come up with adjectives to describe those public spaces. Needless to say, the second task was a bit harder than the first one.
From here, she launches into her literature review of research on perceptions of virtual (textual) versus physical social spaces. Here are a few highlights, along with my comments about translating into online teaching:
- Good things come to those that wait: Old theories of online communication held that less information is conveyed, therefore making it inherently less intimate. Emperical research has shown this to be false, however (and obviously so to any good online teacher). What is true, however, is that the there is less social information density in communication. Familiarity therefore takes more time. This is why frameworks like Gilly Salmon’s five-step model for e-Moderating are really useful; they give us cues for recognizing stages in the temporal arc of online group dynamics.
- Love is blind (but not deaf): Because people inherently desperately want to connect with and understand other people, online conversation participants who are denied the visual cues in face-to-face conversation tend to become hyper-sensitive to linguistic tone, speed of response, and other cues available in the textual environment. As many good online teachers know, this means responding frequently and quickly in the first weeks of class is very important, as is increasing the level affect in your language. Be obviously nice and it will be noticed.
- The night time is the right time for making love: The same comments made during business hours tend to be perceived as more intimate than those made during business hours. So log on to your class in the evening from time to time.
- A picture is worth a thousand words today, but don’t forget the effects of inflation: Pictures tend to “enhance relational outcomes” (i.e., make people feel closer to each other) when people are just getting to know each other in a textual environment. However, they tend to make people feel less intimate in situations where they already know each other well. So using images to help compensate for that loss of information density in the beginning of the class is a good idea, but keep in mind that it can have an effect on your cohort in the long term. The greatest affinity between users apparently occurs in long-term online communities without pictures.
For those who are not entirely convinced that we should care about levels of “intimacy” or “affinity” among course participants, there is a very good reason to care: retention. It is well known that completion rates for online courses are, on average, much lower than for face-to-face courses. There are a lot of reasons for this, not all of which is bad (e.g., more consumer choice means less forced loyalty). However, one reason is that students fail to feel engaged with the class. It’s a lot easier to tune out an online course than a face-to-face one. Increasing the sense of social cohesion among the class–quickly–can have a substantial impact on how many of your students actually finish the course.
There’s a lot more here; I’m just highlighting a few of the more obvious lessons. This paper is worth spending the time to read.
More on it in my next post.
