Modelling Student Participation Using Discussion Forum Data

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Across many different educational settings, course discussion forums allow students to learn from one another and connect socially with their peers and instructors. Content analysis of the messages that are exchanged has been used to model engagement using two well-established theoretical frameworks, Community of Inquiry and ICAP. However, manual content analysis is slow and expensive, and prior work on automation is limited. In addition, these two theoretical frameworks developed out of different disciplines, and little work has been done to bring them together. To address these issues, I will evaluate the use of advanced methods from natural language processing to automate the content analysis, considering both frameworks individually and together, and comparing the results with prior work in terms of accuracy and explanatory power. I will also contribute to the conceptual understanding of what characterises a high quality discussion forum contribution by identifying connections between the frameworks themselves and places where they offer complementary perspectives.
Original languageEnglish
Title of host publicationCompanion Proceedings 10th International Conference on Learning Analytics & Knowledge (LAK20)
Number of pages6
Publication statusPublished - 31 Mar 2020
EventThe 10th International Learning Analytics & Knowledge Conference - Frankfurt, Germany
Duration: 23 Mar 202027 Mar 2020
Conference number: 10


ConferenceThe 10th International Learning Analytics & Knowledge Conference
Abbreviated titleLAK20
Internet address


  • learning analytics
  • student engagement
  • Community of Inquiry
  • ICAP
  • natural language processing


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