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Social interactions clustering MOOC students : an exploratory study.

Shi, Lei and Cristea, Alexandra I. and Toda , Armando M. and Wilk, Oliveira and Ahmad, Alamri and Chen, Nian-Shing and Kinshuk, (2020) 'Social interactions clustering MOOC students : an exploratory study.', in IEEE 20th International Conference on Advanced Learning Technologies ICALT 2020 ; proceedings. , pp. 172-174.


An exploratory study on social interactions of MOOC students in FutureLearn was conducted, to answer "how can we cluster students based on their social interactions?" Comments were categorized based on how students interacted with them, e.g., how a student's comment received replies from peers. Statistical modelling and machine learning were used to analyze comment categorization, resulting in 3 strong and stable clusters.

Item Type:Book chapter
Keywords:Learning analytics, Clustering, Social interaction
Full text:(AM) Accepted Manuscript
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Publisher statement:© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Date accepted:09 March 2020
Date deposited:11 August 2020
Date of first online publication:04 August 2020
Date first made open access:04 December 2020

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