dc.contributor.author | Ruipérez-Valiente, José A. | |
dc.contributor.author | Alexandron, Giora | |
dc.contributor.author | Chen, Zhongzhou | |
dc.contributor.author | Pritchard, David E. | |
dc.date.accessioned | 2021-07-13T09:26:58Z | |
dc.date.available | 2021-07-13T09:26:58Z | |
dc.date.issued | 2016-04-25 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12761/219 | |
dc.description | DOI: 10.1145/2876034.2876037. | |
dc.description.abstract | The study presented in this paper deals with copying answers in MOOCs. Our findings show that a significant fraction of the certificate earners in the course that we studied have used what we call harvesting accounts to find correct answers that they later submitted in their main account, the account for which they earned a certificate. In total, around 2.5% of the users who earned a certificate in the course obtained the majority of their points by using this method, and around 10% of them used it to some extent. This paper has two main goals. The first is to define the phenomenon and demonstrate its severity. The second is characterizing key factors within the course that affect it, and suggesting possible remedies that are likely to decrease the amount of cheating. The immediate implication of this study is to MOOCs. However, we believe that the results generalize beyond MOOCs, since this strategy can be used in any learning environments that do not identify all registrants. | |
dc.language.iso | eng | |
dc.publisher | ACM Press | |
dc.title | Using Multiple Accounts for Harvesting Solutions in MOOCs | en |
dc.type | conference object | |
dc.conference.date | 25-26 April 2016 | |
dc.conference.place | Edinburgh, Scotland, UK | |
dc.conference.title | The 3rd ACM Conference on Learning @ Scale (L@S 2016) | * |
dc.event.type | conference | |
dc.pres.type | paper | |
dc.type.hasVersion | VoR | |
dc.rights.accessRights | open access | |
dc.identifier.url | http://dl.acm.org/citation.cfm?doid=2876034.2876037 | |
dc.page.final | 70 | |
dc.page.initial | 63 | |
dc.place.issued | New York, New York, USA | |
dc.subject.keyword | Academic dishonesty | |
dc.subject.keyword | educational data mining | |
dc.subject.keyword | learning
analytics | |
dc.subject.keyword | MOOCs | |
dc.description.refereed | TRUE | |
dc.description.status | pub | |
dc.eprint.id | http://eprints.networks.imdea.org/id/eprint/1333 | |