Security in online learning assessment towards an effective trustworthiness approach to support e-learning teams

(c) 2014 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.This paper proposes a trustworthiness model for the design of secure learning assessment in on-line collaborative learning groups. Although computer supported collaborative learning has been widely adopted in many educational institutions over the last decade, there exist still drawbacks which limit their potential in collaborative learning activities. Among these limitations, we investigate information security requirements in on-line assessment, (e-assessment), which can be developed in collaborative learning contexts. Despite information security enhancements have been developed in recent years, to the best of our knowledge, integrated and holistic security models have not been completely carried out yet. Even when security advanced methodologies and technologies are deployed in Learning Management Systems, too many types of vulnerabilities still remain opened and unsolved. Therefore, new models such as trustworthiness approaches can overcome these lacks and support e-assessment requirements for e-Learning. To this end, a trustworthiness model is designed in order to conduct the guidelines of a holistic security model for on-line collaborative learning through effective trustworthiness approaches. In addition, since users' trustworthiness analysis involves large amounts of ill-structured data, a parallel processing paradigm is proposed to build relevant information modeling trustworthiness levels for e-Learning.Peer ReviewedPostprint (author's final draft

Scientific Literacy in the digital age: tools, environments and resources for co-inquiry

This paper describes some European and International projects to promote Scientific Literacy in the digital age as well as technologies, environments and resources for co-inquiry. The aim of this research is also to describe computer applications, software tools and environments that were designed to support processes of collaborative inquiry learning to promote Scientific Literacy. These tools are analyzed by describing their interfaces and functionalities. The outcomes of this descriptive research points out some effects on student learning and competences developed known from the literature. This paper argues the importance of promoting scientific citizenship not only through schools and Universities (formal learning), but also non-credit online courses and community-based learning programmes (non-formal context), as well as daily life activities, educational open digital materials through social networks (informal scenario)

How to design for persistence and retention in MOOCs?

Design of educational interventions is typically carried out following a design cycle involving phases of investigation, conceptualization, prototyping, implementation, execution and evaluation. This cycle can be applied at different levels of granularity e.g. learning activity, module, course or programme. In this paper we consider an aspect of learner behavior that can be critical to the success of many MOOCs i.e. their persistence to study, and the related theme of learner retention. We reflect on the impact that consideration of these can have on design decisions at different stages in the design cycle with the aim of en-hancing MOOC design in relation to learner persistence and retention, with particular attention to the European context

Big Data Meets Telcos: A Proactive Caching Perspective

Mobile cellular networks are becoming increasingly complex to manage while classical deployment/optimization techniques and current solutions (i.e., cell densification, acquiring more spectrum, etc.) are cost-ineffective and thus seen as stopgaps. This calls for development of novel approaches that leverage recent advances in storage/memory, context-awareness, edge/cloud computing, and falls into framework of big data. However, the big data by itself is yet another complex phenomena to handle and comes with its notorious 4V: velocity, voracity, volume and variety. In this work, we address these issues in optimization of 5G wireless networks via the notion of proactive caching at the base stations. In particular, we investigate the gains of proactive caching in terms of backhaul offloadings and request satisfactions, while tackling the large-amount of available data for content popularity estimation. In order to estimate the content popularity, we first collect users' mobile traffic data from a Turkish telecom operator from several base stations in hours of time interval. Then, an analysis is carried out locally on a big data platform and the gains of proactive caching at the base stations are investigated via numerical simulations. It turns out that several gains are possible depending on the level of available information and storage size. For instance, with 10% of content ratings and 15.4 Gbyte of storage size (87% of total catalog size), proactive caching achieves 100% of request satisfaction and offloads 98% of the backhaul when considering 16 base stations.Comment: 8 pages, 5 figure