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The primary purpose of this chapter is to explain the framework that we have been developing to analyze learning networks and other complex examples of learning in situ (Goodyear and Carvalho 2013). We outline the evolution of the framework, and provide a rationale for its composition and use. Part of our argument is that more sophisticated methods of analysis are needed to represent the complexity of modern learning situations. We use some ideas from architecture, human-computer interaction, science and technology studies and a number of associated fi elds to analyze learning networks – including ideas about the relations between built forms (space, place, tools, artifacts, texts) and human activity.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 37 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |