Please use this identifier to cite or link to this item:
DC FieldValueLanguage
dc.contributor.authorXie, Haoran-
dc.contributor.authorWang, Philips Fu Lee-
dc.contributor.authorKwan, Reggie Ching Ping-
dc.contributor.otherZou, D.-
dc.contributor.otherWong, T.-L.-
dc.contributor.otherChan, W. H.-
dc.description.abstractWord knowledge is the foundation of language acquisition for second language learners. Due to the diversity of background knowledge and language proficiency levels of different learners, it is essential to understand and cater for various needs of users in an e-learning system. A personalized learning system which meets this requirement is therefore necessary. Users may also be concerned about the possible risk of revealing their private information and prefer controls on the personalization of a system. To leverage these two factors: personalization and control, we propose an explicit learner profiling model for word learning task recommendation in this paper. This proposed profiling model can be fully accessed and controlled by users. Moreover, the proposed system can recommend learning tasks based on explicit user profiles. The experimental results of a preliminary study further verify the effectiveness of the proposed model.en_US
dc.titleAn explicit learner profiling model for personalized word learning recommendationen_US
dc.typeconference proceedingsen_US
dc.relation.publicationEmerging Technologies for Education (Second International Symposium, SETE 2017) Revised Selected Papersen_US
dc.contributor.affiliationSchool of Computing and Information Sciences-
item.openairetypeconference proceedings-
item.fulltextNo Fulltext- of Computing and Information Sciences- of Computing and Information Sciences- of Computing and Information Sciences-
Appears in Collections:CIS Publication
SFX Query Show simple item record

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.