A data visualization approach for trustworthiness in social networks for on-line learning
Tipo de documentoTexto en actas de congreso
Fecha de publicación2015
Condiciones de accesoAcceso abierto
Up to now, the problem of ensuring collaborative activities in e-Learning against dishonest students' behaviour has been mainly tackled with technological security solutions. Over the last years, technological security solutions have evolved from isolated security approaches based on specific properties, such as privacy, to holistic models based on technological security comprehensive solutions, such as public key infrastructures, biometric models and multidisciplinary approaches from different research areas. Current technological security solutions are feasible in many e-Learning scenarios but on-line assessment involves certain requirements that usually bear specific security challenges related to e-Learning design. In this context, even the most advanced and comprehensive technological security solutions cannot cope with the whole scope of e-Learning vulnerabilities. To overcome these deficiencies, our previous research aimed at incorporating information security properties and services into on-line collaborative e-Learning by a functional approach based on trustworthiness assessment and prediction. In this paper, we present a peer-to-peer on-line assessment approach carried out in a real on-line course developed in our real e-Learning context of the Open University of Catalonia. The design presented in this paper is conducted by our trustworthiness security methodology with the aim of building peer-to-peer collaborative activities, which enhances security e-Learning requirements. Eventually, peer-to-peer visualizations methods are proposed to manage security e-Learning events, as well as on-line visualization through peer-to-peer tools, intended to analyse collaborative relationship.
(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works.
CitaciónMiguel, J., Caballé , Santi, Xhafa, F., Snasel, V. A data visualization approach for trustworthiness in social networks for on-line learning. A: IEEE International Conference on Advanced Information Networking and Applications. "IEEE 29th International Conference on Advanced Information Networking and Applications, Gwangju, South Korea, March 25-27, 2015: proceedings". Gwangju: 2015, p. 490-497.
Versión del editorhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7098011