Learning analytics as a methodology for understanding medical practitioners’ informal learning in online social networks
AffiliationComputing and Information Systems
Document TypePhD thesis
Access StatusOpen Access
© 2017 Dr. Xin Li
Online Social Networks (OSNs) are used increasingly by medical practitioners to communicate, collaborate and share ideas with each other. This activity can be thought of as a type of informal learning, thus OSNs have important implications for ongoing efforts to support Continuing Professional Development (CPD) in the medical profession. Some of these OSNs are open only to registered medical professional members. In such OSNs the nature and scope of the learning that is occurring are neither well described nor transparent. The challenge of understanding the learning occurring in these OSNs makes it difficult to determine its value as a form of CPD, and more specifically to design and facilitate this type of learning. The objective of this thesis is to examine how learning analytics may serve as a methodology for understanding the process of learning in OSNs for medical practitioners. This research is based on a multi-method design that employs a set of analytic methods, including social network analysis, topic modeling, and context analysis, to investigate different components of the learning process (i.e. learning interaction, learning content and learning context) in the case of a large online discussion forum for medical practitioners. This research found that the proposed analytic methods were useful to gain a detailed understanding of the learning process; this set of methods can reveal what is occurring in such an OSN in an efficient manner and enable the development of intervention strategies for improving learning. The understanding of the learning process in the case study forum led to proposing four intervention strategies for improving the design and operation of OSNs for medical practitioners. These intervention strategies include: organising topics of discussion, recommending subject experts, alerting special discussions, and detecting learning groups. This research elaborates the intervention strategies by describing implementation approaches and relevant application scenarios. This research contributes to greater sophistication in the understanding and improvement of OSNs for medical practitioners’ informal learning, and in turn will support more effective design, operation and evaluation of such learning environments.
Keywordslearning analytics; social learning analytics; networked learning; health professional education; online social networks; continuing professional development; informal learning; social network analysis; topic modeling; context analysis
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