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Visualizing the learning patterns of topic-based social interaction in online discussion forums: an exploratory study

Abstract

Online discussion forums are common features of learning management systems; they allow teachers to engage students in topical discussions in environments beyond physical spaces. This study presents a novel approach to operationalizing the connections between social interaction and contextual topics by visualizing posts in an online discussion forum. Using the weak ties theory, we developed a prototype of a tool that helps visualize the text-based content in online discussion forums, specifically in terms of topic relationships and student interactions. This research unveils a nuanced picture of social and topic connectivity, the nature of social interactions, and the changes in the topics being discussed when serendipity occurs. Our implementation of the tool and the results from testing show that the visualization method was able to determine that the strongly connected major topics in the discussion were related to the intended course learning outcomes, whereas the weakly connected topics could yield insights into students’ unexpected learning. The proposed method of visualization may benefit both teachers and students by helping them to efficiently the learning and teaching process and thus may contribute to formative assessment design, a collaborative learning process, and unexpected learning.

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Data availability

The datasets used and/or analyzed in the current study are available from the corresponding author on reasonable request.

Abbreviations

IAM:

Interaction analysis model

ILO:

Intended learning outcome

LDA:

Latent Dirichlet allocation

LDAvis:

LDA visualization

LMS:

Learning management system

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Wong, G.K.W., Li, Y.K. & Lai, X. Visualizing the learning patterns of topic-based social interaction in online discussion forums: an exploratory study. Education Tech Research Dev 69, 2813–2843 (2021). https://doi.org/10.1007/s11423-021-10040-5

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Keywords

  • Social network analysis
  • Topic modeling
  • Visualization
  • Weak ties
  • Text mining