Personal Learning Network

Weekly Personal Learning Network (click to view enlarged image)

Did any of the nodes or connections surprise you? 

Looking at my learning network, I was surprised at how many digital one-way connections I have. However, as my classes are online this semester, one-way connections will be more common as I tend to stay online and stick to the courses’ environment. As seen in my UVic campus node, the amount of two-way physical connections is significantly lesser than in my laptop node. I believe that more two-way connections would result if I were in in-person courses.

Are some of your classes or courses more or less connected than others?

With all my courses being online, I think that the majority are connected. In many of my EDCI courses, the amount of collaboration for coursework is equal in the form of discussions and blog posts. In comparison with in-person learning, I feel the interconnected nature is less in collaboration and interaction but more focused on active discussion of lecture material. Ultimately, the connectivity of courses depends on the environment in which the courses are placed and what kind of collaboration is applied.

Reflection

I chose this activity because it was interesting to visualize my week using data. As a person who wants to get into data analysis and data science, this activity aligns with my learning and career goals. In my research of learning maps, I have found some exciting benefits regarding network mapping. Network mapping is an effective way to measure what matters; for example, in this activity, I was able to measure my activity regarding my coursework. If I had mapped my entire interactions for the week, it would be difficult to analyze and form connections between different nodes.
Additionally, by condensing my interaction map to only my learning interactions, I can analyze my interactions based on frequency and relationship types. With these quantifications, I can track what I need to work on to improve my learning experience further. Ultimately, network mapping is a simple and effective way to visualize and analyze data and improve spatial thinking.