Online practices such as viewing webpages, clicking on links, and posting content like photographs and video are becoming a ubiquitous part of a teenager’s daily life in North America. Every time teens go online they create a traceable pattern of their activity. Not only do they create a data record online, they also “teach” the algorithms that govern social media and search software. Search engines such as Google and social networks like Facebook have algorithms designed to adapt to our activity and present information based off our browsing history. There are characteristic decentralized network dynamics at work in these algorithms (Barabási, 2003; Pariser, 2011).
As art educators move to interweave social media into their curricula it is important to know that not only do learners have the ability to share creative works in a decentralized fashion; teachers can look to the dynamic patterns of a decentralized network to visualize attention and learning of a collective. The coupling of social interactions with online contexts creates the conditions for the amplified dynamics of decentralized networks. It is imperative to carefully consider these dynamics when teaching online. In this paper I present a method for visualizing decentralized ideation and learning online through activity such as image view counts and responses to creative works by participants in a recent study. The purpose of this paper is to discuss how decentralized networks are dynamic phenomena embedded in social behaviour and computer code and the rationale for critically incorporating these tools in teaching and learning art online. Additionally, by visualizing these dynamics art educators and research can gain an image of collective learning. This is particularly useful for not only art education researchers but also classroom art teachers who incorporate social media into the art curriculum.