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On the need for fine-grained analysis of gender versus commenting behaviour in MOOCs.

Cristea, A. I. and Alshehri, M. and Alamri, A. and Kayama, M. and Foss, J. and Shi, L. and Stewart, C. (2018) 'On the need for fine-grained analysis of gender versus commenting behaviour in MOOCs.', in Proceedings of the 2018 the 3rd International Conference on Information and Education Innovations (ICIEI'18) : London, United Kingdom, June 30 - July 02, 2018. New York, NY, USA: Association for Computing Machinery, pp. 73-77. ACM international conference proceeding series.

Abstract

Stereotyping is the first type of adaptation ever proposed. However, the early systems have never dealt with the numbers of learners that current Massive Open Online Courses (MOOCs) provide. Thus, the umbrella question that this work tackles is if learner characteristics can predict their overall, but also fine-grain behaviour. Earlier results point at differences related to gender or to age. Here, we analyse gender versus commenting behaviour. Our fine-grained analysis shows that the result may further depend on the course topic, or even week. Surprisingly, for instance, women chat less in a Psychology-related course, but more (or similar) on a Computer Science course. These results are analysed in this paper in details, including two different methods of averaging comments, leading to remarkably different results. The outcomes can help in informing future runs, in terms of potential personalised feedback for teachers and students.

Item Type:Book chapter
Full text:(AM) Accepted Manuscript
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1145/3234825.3234833
Publisher statement:© ACM 2018. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 2018 The 3rd International Conference on Information and Education Innovations (ICIEI'18), https://doi.org/10.1145/3234825.3234833.
Date accepted:22 May 2018
Date deposited:02 August 2018
Date of first online publication:30 June 2018
Date first made open access:No date available

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