Networks in Learning Analytics: Where Theory, Methodology, and Practice Intersect

Guest editorial of the Journal of Learning Analytics special section on Networks in Learning Analytics

By Bodong Chen and Oleksandra Poquet in publications

March 11, 2022


March 11, 2022


12:00 AM

Keywords: network analysis, networked learning, social network analysis, learning analytics, network science, editorial


Network analysis has contributed to the emergence of learning analytics. In this editorial, we briefly introduce network science as a field and situate it within learning analytics. Drawing on the Learning Analytics Cycle, we highlight that effective application of network science methods in learning analytics involves critical considerations of learning processes, data, methods and metrics, and interventions, as well as ethics and value systems surrounding these areas. Careful work must meaningfully situate network methods and interventions within the theoretical assumptions explaining learning, as well as within pedagogical and technological factors shaping learning processes. The five empirical papers in the special section demonstrate diverse applications of network analysis, and the invited commentaries from cognitive network science and physics education research further discuss potential synergies between learning analytics and other sister fields with a shared interest in leveraging network science. We conclude by discussing opportunities to strengthen the rigour of network-based learning analytics projects, expand current work into nascent areas, and achieve more impact by holistically addressing the full cycle of learning analytics.

Posted on:
March 11, 2022
2 minute read, 219 words
network analysis
See Also:
Network Motifs as Codes
Socio-Semantic Network Motifs Framework for Discourse Analysis
SoLAR Webinar: Analyzing Learning and Teaching through the Lens of Networks