dc.contributor.advisor | Muñoz-Merino, Pedro J. | |
dc.contributor.author | Ruipérez-Valiente, José A. | |
dc.date.accessioned | 2021-07-13T10:21:35Z | |
dc.date.available | 2021-07-13T10:21:35Z | |
dc.date.issued | 2014-09-25 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12761/1487 | |
dc.description.abstract | This manuscript is focused in two of the most prominent techniques for the next years for education advancement, which are learning analytics and gamification. There are a lot of research works in both of these lines independently, but not many research papers combine both techniques in order to improve the educational experience. One of the most used gamification techniques is the use of badges as a reward for making specific student actions. The analysis of users’ interactions and behaviors with the badge system can be used to improve the learning process. We present four high level indicators related to the behavior of students with a badge system and we particularize it for the Khan Academy platform. An extensive analysis of 291 different students interacting with the Khan Academy badge system is done processing real data from freshmen courses at Universidad Carlos III de Madrid. This analysis includes an overview of the global usage of badges, correlations between the badge indicators and other indicators related to the learning process and a Two-Step Cluster Analysis to group students by their badge preferences in order to personalize future experiences. | |
dc.language.iso | eng | |
dc.title | Modeling and Analyzing Gamification Behavior with Badges | en |
dc.type | master thesis | |
dc.type.hasVersion | VoR | |
dc.rights.accessRights | open access | |
dc.description.department | Telematics Engineering | |
dc.description.institution | Universidad Carlos III de Madrid, Spain | |
dc.page.total | 14 | |
dc.subject.keyword | Data mining | |
dc.subject.keyword | decision support | |
dc.subject.keyword | distance learning | |
dc.subject.keyword | education | |
dc.subject.keyword | games | |
dc.subject.keyword | human factors | |
dc.description.status | pub | |
dc.eprint.id | http://eprints.networks.imdea.org/id/eprint/981 | |