Week 4: Reflections & on Social Network Analysis

I’ve taken several courses online studying social networks. I can’t recall having heard the methods of analysis described in quite this fashion. I particularly liked this passage,

“…we are going to cover two groups of measures: those that are measuring the entire network, and those that are measuring the potential of individual nodes in a network.”

To date I’ve not had the opportunity to apply my studies of social networks, so I might be responding to differences which I find interesting such as the ‘potential of individuals…in a network’ (see what I did there). But I also would like to think there is a different constellation of factors in analysis for learning.

Previously I’ve encountered the subject from the mathematical domain where instructors use throwaway examples; however, this course is motivated in the reverse. And as we all know, the constellations don’t look the same if you’re not on earth!

So, if you haven’t guesses yet I’m not taking the course as a teacher; rather, I’m approaching the material as a communicator. My interpretation of the ‘applications of social network analysis to learning contexts’ is limited to those areas which overlap. That said, public speaking overlaps with instruction. Here is an awareness, if not concern, to interpret the signifiers of audience engagement–what we commonly refer to as audience feedback.

When considering feedback in a hypothetical learning context, I can imagine the benefit of quantifiers. An instructor who has quantitative data to associate with their perception from the day of instruction might, over time, develop important time saving shortcuts to managing their instruction. All of the measures of social network analysis could be applied to quantifying communications among students–provided the instructor has access to student’s course-related communications (which is a subject mentioned in the first weeks by Prof. Siemens).

For example, if the instructor perceived the students were ‘distracted’ on the day of instruction and subsequently ‘active’ in a course forum, this might indicate students were not engaged with the material on the day of instruction. A possible response could be to give a brief review at the next class session. You know, even if the instructor or institution does not provide social network forums for the course, students are communicating with these technologies. Then the question remains, How does the instructor obtain this data and in what form?

I must be learning something because my hypothetical example appeared also here in a link for Social Networks Adapting Pedagogical Practice (SNAPP) tool.

One Comment

  1. xtian

    UPDATE: A similar concern to obtaining student course related communications is processing the potentially large volume of data. Here is a link from Prof. Siemens tweet on HarvardX papers and my retweet on “Computer-Assisted Reading and Discovery for Student Generated Text in Massive Open Online Courses” or dealing with a lot of messages for short: