DON'T JUST SAY THANK YOU: EXPLORATION OF TYPES OF POSTS INSPIRING AND HINDERING DEEP CONVERSATIONS ONLINE

  • Devayani Tirthali Independent Researcher
  • Yumiko Murai MIT
Keywords: MOOC, Discussion forum, sequential analysis, facilitation, professional community

Abstract

In an open online discussion forum, where there is no fixed structure or a facilitator like a course forum without any assigned themes, every participant is a facilitator shaping the direction and depth of a conversation. How can we as designers then make sure it leads to an engaging learning community that learners keep coming back to beyond the given course period? This paper reports on sequential analysis of 172 posts in 32 threads and close reading of two threads from an open online discussion forum in a free open online course, specifically looking at the impact of participant actions as facilitative moves, to gain better understanding of the types of actions that lead to deeper and sustained engagement with the ideas of interest. Sequential analysis is an approach that estimates which types of sequences of posts or interactions are most likely to occur in a threaded discussion. The results showed that sharing personal experiences attracted most responses, implying that it is important to encourage participants to share questions or cases connected to their personal experiences. In addition, somewhat paradoxically, we found that posts acknowledging responses tend to conclude and close down the conversation while posts that ask diverging questions tend to attract more discussion.

Published
2019-10-31
How to Cite
Tirthali, D., & Murai, Y. (2019). DON’T JUST SAY THANK YOU: EXPLORATION OF TYPES OF POSTS INSPIRING AND HINDERING DEEP CONVERSATIONS ONLINE. AoIR Selected Papers of Internet Research, 2019. https://doi.org/10.5210/spir.v2019i0.11049
Section
Papers T