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Journal of Computing in Higher Education
Erschienen in: Journal of Computing in Higher Education 3/2017

08.03.2017

The nature and level of learner–learner interaction in a chemistry massive open online course (MOOC)

verfasst von: Andrew A. Tawfik, Todd D. Reeves, Amy E. Stich, Anila Gill, Chenda Hong, Joseph McDade, Venkata Sai Pillutla, Xiaoshu Zhou, Philippe J. Giabbanelli

Erschienen in: Journal of Computing in Higher Education | Ausgabe 3/2017

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Abstract

Similar to other online courses, massive open online courses (MOOCs) often rely on learner–learner interaction as a mechanism to promote learning. However, little is known at present about learner–learner interaction in these nascent informal learning environments. While some studies have explored MOOC participant perceptions of learner–learner interactions, research is still lacking regarding the content and level of such interactions. Using the interaction analysis model (IAM) as a theoretical framework and social network analysis methods, the present study investigates the nature and level of learner–learner interaction within a popular Chemistry MOOC from Coursera. Findings suggest that learner–learner interaction: was limited to lower phases of the IAM framework (e.g., sharing and comparing information); changed (decreased) over time; and was heavily dependent on a few highly-engaged learners. Potential implications for the design of future MOOCs are discussed.
Nächster Artikel Erratum to: The nature and level of learner–learner interaction in a chemistry massive open online course (MOOC)

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Metadaten
Titel
The nature and level of learner–learner interaction in a chemistry massive open online course (MOOC)
verfasst von
Andrew A. Tawfik
Todd D. Reeves
Amy E. Stich
Anila Gill
Chenda Hong
Joseph McDade
Venkata Sai Pillutla
Xiaoshu Zhou
Philippe J. Giabbanelli
Publikationsdatum
08.03.2017
Verlag
Springer US
Erschienen in
Journal of Computing in Higher Education / Ausgabe 3/2017
Print ISSN: 1042-1726
Elektronische ISSN: 1867-1233
DOI
https://doi.org/10.1007/s12528-017-9135-3

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