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Erschienen in: Journal of Computing in Higher Education 1/2017

19.01.2017

Toward a generalizable understanding of Twitter and social media use across MOOCs: who participates on MOOC hashtags and in what ways?

verfasst von: George Veletsianos

Erschienen in: Journal of Computing in Higher Education | Ausgabe 1/2017

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Abstract

Researchers have proposed that social media provide complementary learning environments for Massive Open Online Courses (MOOCs) that might engender participation, engagement, and peer-support. Although suggestive, nearly all of the research in this area consists of case studies, making it challenging to determine whether or to what extent findings can be generalized to MOOCs beyond those studied. This mixed methods research used data mining techniques to retrieve a large-scale Twitter data set from 116 MOOCs with course-dedicated hashtags. Using quantitative and qualitative methods, it then examined users’ participation patterns, the types of users posting to those hashtags, the types of tweets that were posted, and the variation in types of posted tweets across users. While popular narratives suggest that social media provide a space for increased participation, this study provides little evidence to support these claims in the context of Twitter as an adjunct to MOOCs. Results show that learners make up only about 45% of users and contribute only about 35% of tweets. The majority of users contribute minimally, and an active minority of users contributes the preponderance of messages. These findings do not reveal substantive evidence of learners contributing to multiple hashtags, which may suggest that learners did not find Twitter to be a useful space that provided added value or responded to their needs. Ultimately, these results demonstrate the need for greater intentionality in integrating social media into MOOCs.

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Metadaten
Titel
Toward a generalizable understanding of Twitter and social media use across MOOCs: who participates on MOOC hashtags and in what ways?
verfasst von
George Veletsianos
Publikationsdatum
19.01.2017
Verlag
Springer US
Erschienen in
Journal of Computing in Higher Education / Ausgabe 1/2017
Print ISSN: 1042-1726
Elektronische ISSN: 1867-1233
DOI
https://doi.org/10.1007/s12528-017-9131-7

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