These are pretty key questions if we’re putting together a Microethnography to look at a “Community” of people on a MOOC. I suppose we could look at community in terms of interaction. If we imagine a scale between 0 = no interaction between Learners (for example a MOOC with no way for students to communicate) up to say 10 = some sort of Vulcan Mind Meld between all the students, then we could look at the features that make important landmarks along that scale (students can post, students can reply, peer review etc). That would be one way to judge “Community”, but it would still be a long way from being an objective measure (for example, would we consider an active forum on an LMS to be superior or inferior to student discussion taking place on Twitter or Discord? What are we basing this on?).
The MOOC that I’m taking part in for this assignment is quite limited in terms of possible interaction between users. The course is broken up into weeks, with a number of topics in each week. Each topic then has some “content” (text, images, video, links etc) and a single discussion thread where users can post their thoughts and reply to those posts (for a while I couldn’t see replies as being connected to the initial posts, but this turned out to be a setting that I had unwittingly changed). It is also possible for students to “Like” posts and replies. However, there are no guidelines about how to use the discussion part of each topic, so mostly they’re just a set of individual musings without any connection to each other.
To try and get a sense of the Community on my MOOC I’m going to measure 3 things. Firstly the number of individual posts made on each topic, by each known user. Then I’ll look at how many replies are made, by whom and on who’s posts. I will also look at the number of “Likes” each person receives and map this to each topic as well.
This is going to take some time and a great big Excel file with multiple sheets 🙂 To stop the whole thing from becoming unmanageable I’m going to restrict myself to collecting data on the Week 1 topics only. I’m also going to restrict myself to posts and replies made during the period 9th Feb to 15th Feb (the first week of the course). This is a MOOC, and people join after the first week. There would be a problem with constantly having to update my data if I don’t set a specific snap-shot of time.
If this method gives me interesting insights I can then return to the MOOC and either map a different week, or compare Week 1 as it was on 15th Feb with how it looks further down the line. Both of these could be potentially interesting as the first option would show how the course settles down (presuming that a lot of people who drop out do so after the first week) while the second option could show differences between people starting a MOOC on the start date and those catching up (for instance do people playing catch up seem to post more or less? How far back do they go to leave replies – is it just the first page or do they read the lot?).
