Topological Parameters of Networked Learning

This paper proposes a methodological linking of learning theories and social learning analytics, applicable in real-life settings. We view online discussions in learning communities as networks in which human agents and posts of content are the nodes, while the interactions between nodes are represented as edges. The collaborative learning process is thus viewed as the construction and growth of a network involving various types of interactions among learners and content items. We contend that online learning assessment should be grounded by a theoretical framework based on quantitative analysis of the collaborative learning process as reflected by learning communities' online discussions. This paper demonstrates our proposed framework through a case study of a single community's online discussion, which took place throughout one academic semester. We use social network analysis (SNA) and other log-based techniques to determine topological parameters or network characteristics, assessing both collective and individual learning process which took place as reflected by the community online discussion