Chapter 2

Handbook of Learning Analytics
First Edition

Computational Methods for the Analysis
of Learning and Knowledge Building

H. Ulrich Hoppe


Learning analytics (LA) features an inherent interest in algorithms and computational methods of analysis. This makes LA an interesting field of study for computer scientists and mathematically inspired researchers. A differentiated view of the different types of approaches is relevant not only for “technologists” but also for the design and interpretation of analytics applications. The “trinity of methods” includes analytics of 1) network structures including actor–actor (social) networks but also actor–artefact networks, 2) processes using methods of sequence analysis, and 3) content using text mining or other techniques of artefact analysis. A summary picture of these approaches and their roots is given. Two recent studies are presented to exemplify challenges and potential benefits of using advanced computational methods that combine different methodological approaches.

Export Citation: Plain Text (APA)     BIBTeX     RIS

Supplementary Material
References (42)
About this Chapter
Founding Members
Previous Image
Next Image

info heading

info content