SLOAN: Social Learning Optimization Analysis of Networks

  • David J. Lemay Cerence Inc.
  • Tenzin Doleck Simon Fraser University
  • Christopher G. Brinton Purdue University
Keywords: social learning optimization analysis of networks, SLOAN, social cognitive theory, social learning, information theory, network analysis


Online discussion research has mainly been conducted using case methods. This article proposes a method for comparative analysis based on network metrics such as information entropy and global network efficiency as more holistic measures characterizing social learning group dynamics. We applied social learning optimization analysis of networks (SLOAN) to a data set consisting of Coursera courses from a range of disciplines. We examined the relationship of discussion forum uses and measures of network efficiency, characterized by the information flow through the network. Discussion forums vary greatly in size and in use. Courses with a greater prevalence of subject-related versus procedural talk differed significantly in seeking but not disseminating behaviors in massive open online course discussion forums. Subject-related talk was related to higher network efficiency and had higher seeking and disseminating scores overall. We discuss the value of SLOAN for social learning and argue for the experimental study of online discussion optimization using a discussion post recommendation system for maximizing social learning.


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How to Cite
Lemay, D., Doleck, T., & Brinton, C. (2022). SLOAN: Social Learning Optimization Analysis of Networks. The International Review of Research in Open and Distributed Learning, 23(4), 93-122.
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