Fair Trade metaphor as a Control Privacy Method for Pervasive Environments: Concepts and Evaluation

Abraham Esquivel, Pablo A. Haya and Xavier Alamán. Sensor 15(6), 14207-14229 (2015) doi:10.3390/s150614207 [download] (JCR, IF 2014: 2.093, Q1)

This paper presents a proof of concept from which the metaphor of “fair trade” is validated as an alternative to manage the private information of users. Our privacy solution deals with user’s privacy as a tradable good for obtaining environmental services. Thus, users gain access to more valuable services as they share more personal information. This strategy, combined with optimistic access control and transaction registry mechanisms, enhances users’ confidence in the system while encouraging them to share their information, with the consequent benefit for the community. The study results are promising considering the user responses regarding the usefulness, ease of use, information classification and perception of control with the mechanisms proposed by the metaphor.

Analysing content and patterns of interaction for improving the learning design of networked learning environments

Pablo A. Haya, Oliver Daems, Nils Malzahn, Jorge Castellanos and Heinz Ulrich Hoppe

British Journal of Educational Technology. Article first published online: 3 MAR 2015 (2015) DOI: 10.1111/bjet.12264 [download] (JCR, IF 2014: 1.394, Q1)

Learning Analytics constitutes a key tool for supporting Learning Design and teacher-led inquiry into student learning. In this paper, we demonstrate how a Social Learning Analytics toolkit can combine social network analysis and content analysis for supporting a global and formal teacher inquiry. This toolkit not only supports teachers in improving the organisation of the learning process but also generates important input to improve the students’ reflection on their own learning. Our examples show how combinations of different levels of analysis can provide deep insight in the learning process. We report a case study that exemplifies the main features of our approach and the kind of outcomes that can be obtained. Commenting and rating processes on videos are analysed based on user traces from a social learning platform. Finally, we point out implications on the learning design for networked learning environments in general.

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