dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | prof. dr. J.T. (Johan) Jeuring, dr. S.A. (Sergey) Sosnovsky | |
dc.contributor.author | Oerlemans, T.S. | |
dc.date.accessioned | 2018-08-21T17:01:12Z | |
dc.date.available | 2018-08-21T17:01:12Z | |
dc.date.issued | 2018 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/30483 | |
dc.description.abstract | This project investigates whether or not context-adaptive notification timing can improve responsiveness to notifications in a mobile language learning app. The app developed for this project has been created to send notifications that contain built-in quizzes. The goal is to provide users with a low-threshold form of learning that is adaptively initiated by the system. The app uses eight independent contextual variables, such as location and time, to make the system context-aware. We compared 30 users using a context-adaptive notification management model to 28 users using a context-unadaptive notification management model over a period of 11 days. We have found that users of the context-adaptive model respond significantly more often to notifications as opposed to the users using the context-unadaptive model. | |
dc.description.sponsorship | Utrecht University | |
dc.format.extent | 2511676 | |
dc.format.mimetype | application/zip | |
dc.language.iso | en | |
dc.title | Context-Adaptive Notification Management in Mobile Language Learning | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | Context-Adaptive Notification Management; Mobile language learning; Context-Adaptive Notification Timing | |
dc.subject.courseuu | Artificial Intelligence | |