Network Analysis as a Research Methodology in Science Education Research

nodes and links as educationally relevant entities. We show how one can analyse networks as they
evolve over time − the dynamics of networks − and how one can model dynamic processes on
networks. We also explain how networks can have both visual and mathematical properties that
make them tractable as a way of generating knowledge about relational data. We suggest how
a theory that emphasizes relational aspects might be developed using networks by providing an
example about social networks, where we explain the generation of the theory-like structures rules
of interaction, which are meant to have explanatory power. Likewise, we make interpretations of
student discussions that are shaped in part by the algorithm we use to create discussion maps as
well as by the changes we make to the transcript. Th e article illustrates how in a teacher-student
dialogue, the structure of the network shapes the way we comprehend and talk about discussion
networks. All these are dependent on the relational character of networks and would not be the
same without that perspective. In other words, the theoretical positions we develop are shaped by
the nature of networks. We conclude the article by discussing three developments, which need to
occur to realize the potential of using network analysis in educational research.