Open AccessOnline Learning Communities in the COVID-19 Pandemic: Social Learning Network Analysis of Twitter During the Shutdown
Author(s) -
David John Lemay,
Tenzin Doleck
Publication year - 2020
Publication title -
international journal of learning analytics and artificial intelligence for education
Language(s) - English
Resource type - Journals
ISSN - 2706-7564
DOI - 10.3991/ijai.v2i1.15427
Subject(s) - social media , social learning , shutdown , pandemic , covid-19 , seekers , microblogging , online learning , computer science , internet privacy , knowledge management , world wide web , political science , engineering , infectious disease (medical specialty) , medicine , disease , pathology , nuclear engineering , law
This paper presents a social learning network analysis of Twitter during the 2020 global shutdown due to the COVID-19 pandemic. Research concerning online learning environments is focused on the reproduction of conventional teaching arrangements, whereas social media technologies afford new channels for the dissemination of information and sharing of knowledge and expertise. We examine Twitter feed around the hashtags #onlinelearning and #onlineteaching during the global shutdown to examine the spontaneous development of online learning communities. We find relatively small and ephemeral communities on the two topics. Most users make spontaneous contributions to the discussion but do not maintain a presence in the Twitter discourse. Optimizing the social learning network, we find many potential efficiencies to be gained through more proactive efforts to connect knowledge seekers and knowledge disseminators. Considerations and prospects for supporting online informal social learning networks are discussed.