1. A massive data processing approach for effective trustworthiness in online learning groups
- Author
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Miguel Moneo, Jorge, Caballé Llobet, Santi, Xhafa, Fatos, Prieto Blázquez, Josep, Universitat Politècnica de Catalunya, Universitat Oberta de Catalunya (UOC), and Universitat Politècnica de Catalunya. Departament de Ciències de la Computació
- Subjects
aprendizaje colaborativo asistido por computadora ,parallel processing ,massive data processing ,information security ,processament paral·lel ,Team learning approach in education ,Seguretat informàtica ,Web-based instruction ,Enseñanza virtual ,fitxers de registre ,Informàtica::Aplicacions de la informàtica [Àrees temàtiques de la UPC] ,Informàtica::Seguretat informàtica [Àrees temàtiques de la UPC] ,Computer security ,Aprenentatge--Treball en equip ,MapReduce ,fiabilidad ,processament massiu de dades ,activitats d'aprenentatge virtual ,seguridad de la información ,seguretat de la informació ,archivos de registro ,Ensenyament i aprenentatge::Metodologies docents::Aprenentatge cooperatiu [Àrees temàtiques de la UPC] ,trustworthiness ,Computer-assisted instruction ,Ensenyament virtual ,computer-supported collaborative learning ,log files ,actividades de e-learning ,aprenentatge col·laboratiu assistit amb l'ordinador ,e-learning activities ,Hadoop ,procesamiento en paralelo ,procesamiento masivo de datos ,Implementation ,Ensenyament assistit per ordinador ,fiabilitat ,logs ,Electronic data processing--Distributed processing ,Processament distribuït de dades - Abstract
This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving http://olabout.wiley.com/WileyCDA/Section/id-820227.html This paper proposes a trustworthiness-based approach for the design of secure learning activities in online learning groups. Although computer-supported collaborative learning has been widely adopted in many educational institutions over the last decade, there exist still drawbacks that limit its potential. Among these limitations, we investigate on information security vulnerabilities in learning activities, which may be developed in online collaborative learning contexts. Although security advanced methodologies and technologies are deployed in learning management systems, many security vulnerabilities are still not satisfactorily solved. To overcome these deficiencies, we first propose the guidelines of a holistic security model in online collaborative learning through an effective trustworthiness approach. However, as learners' trustworthiness analysis involves large amount of data generated along learning activities, processing this information is computationally costly, especially if required in real time. As the main contribution of this paper, we eventually propose a parallel processing approach, which can considerably decrease the time of data processing, thus allowing for building relevant trustworthiness models to support learning activities even in real time.
- Published
- 2014