A Basic Social Network Analysis for LA Seminar in Knowledge Forum

In spring 2015 semester, Dr. Bodong Chen has offered a course CI5330 – learning analytics seminar in UMN. He has used Knowledge Forum (KF) as the online learning environment. Knowledge Forum is an educational software designed to help and support knowledge building communities. The instructor can set up scaffolding keywords to help students build knowledge in the online community. Figure 1 shows the home page for CI5330 and figure 2 shows the KF page for week 2.


Figure 1. KF homepage for CI5330


Figure 2. KF page for week 2

My purpose is to analyze students’ basic interactions in CI5330 throughout the whole semester in KF. I want to know whether there are extremely active students and outliers or not. I also want to know whether there are highly connected small groups in the KF or not.

Based on the data generated by students and the instructor on KF, I created two csv files to represent nodes and edges. The node file (figure 3) contains information of the instructor and students; the edge file (figure 4) contains their interaction information. When one person builds on another person’s post, I add a record in the edge file.

Screen Shot 2015-04-25 at 12.16.49 PM

Figure 3. The node file

Screen Shot 2015-04-25 at 8.21.15 AM

Figure 4. The edge file

I use Gephi to do the social network analysis. Here are my results.

From figure 5 we can see that the differences of people’s in-degree and out-degree are not significant. One or two peoples’ degrees are relatively lower than other’s. This result can also be concluded from the in-degree and out-degree diagrams. The size represents the node’s degree. There is only one outlier in the in-degree and out-degree diagrams.


Figure 5. In-Degree and Out-Degree table


Figure 6. In-Degree Diagram


Figure 7. Out-Degree Diagram

Figure 8 shows the modularity class generated in Gephi. From this diagram, we can see that there are two groups. Most people in KF are connected to each other in a big group.

Based on this basic social network analysis, I conclude that people in this class are equally involved in this online learning community. My next step is to do a content analysis to get an in-depth picture of the topics people communicated in the KF.


Figure 8. The modularity class

Note: This SNA report is just for my personal purpose, please don’t use any information from this post for any research.

Finally, I wanna share a social network analysis site created by Christiane Reilly and me for a class session in this course.


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