Handbook of Learning Analytics
Chapter 4
Cacophony of Networks in Learning Analytics
Oleksandra Poquet & Srećko Joksimović
Abstract
Network analysis, a suite of techniques to quantify relations, is among core methods in learning analytics (LA). However, insights derived from the application of network analysis in LA have been disjointed and difficult to synthesize. We suggest that such is due to the naïve adoption of network analysis method into the methodologies of measuring and modelling interpersonal activity in digital learning. This chapter describes the diversity of empirical research using network analysis as a cacophony of network approaches. Focusing on LA studies that evaluate social behavior of individuals or model networks, the chapter exemplifies aspects of the analytical process that require rigor, justification, and alignment to overcome the cacophony of empirical findings. The chapter argues that the clarity of network definitions, hypotheses about network formation, and examination of the validity of individual-level measures are essential for coherent empirical insights and indicators. Future work should also make effort to model the temporal nature, multiplex ties, and dynamic interaction between the levels where interpersonal interactions unfold.
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Title
Cacophony of Networks in Learning Analytics
Book Title
Handbook of Learning Analytics
Pages
pp. 38-45
Copyright
2022
DOI
10.18608/hla22.004
ISBN
978-0-9952408-3-4
Publisher
Society for Learning Analytics Research
Authors
Oleksandra Poquet
Srećko Joksimović
Editors
Charles Lang
Alyssa Friend Wise
Agathe Merceron
Dragan Gašević
George Siemens