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Monitoring of Students' Interaction in Online Learning Settings by Structural Network Analysis and Indicators
Elske Ammenwerth1, Werner O Hackl1
1Institute of Medical Informatics, UMIT - University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria.
Abstract:
Learning as a constructive process works best in interaction with other learners. Support of social interaction processes is a particular challenge within online learning settings due to the spatial and temporal distribution of participants. It should thus be carefully monitored. We present structural network analysis and related indicators to analyse and visualize interaction patterns of participants in online learning settings. We validate this approach in two online courses and show how the visualization helps to monitor interaction and to identify activity profiles of learners. Structural network analysis is a feasible approach for an analysis of the intensity and direction of interaction in online learning settings.

