Multilevel Analysis of Activity and Actors in Heterogeneous Networked Learning Environments

Abstract

Learning in today’s networked environments is often distributed across multiple media and sites, and takes place simultaneously via multiple levels of agency and processes. This is a challenge for those wishing to study learning as embedded in social networks, or simply to monitor a networked learning environment for practical purposes. Traces of activity may be fragmented across multiple logs, and the granularity at which events are recorded may not match analytic needs. This chapter describes an analytic framework, Traces, for analyzing participant interaction in one or more digital settings by computationally deriving higher levels of description. The Traces framework includes concepts for modelling interaction in sociotechnical systems, a hierarchy of models with corresponding representations, and computational methods for translating between these levels by transforming representations. Potential applications include identifying sessions of interaction, key actors within sessions, relationships between actors, changes in participation over time, and groups or communities of learners.