Rachida Ajhoun

C-MADAR Learning: Cloud based learning environment

With a huge number of resources, users and services, E-Learning systems may encounter some challenges regarding dynamic concurrency, access to resources or handling the rapid content storage. Also adds to these issues, optimization and control of resources and costs. Through cloud computing, we can not only answer these needs but also provide an architecture that guarantees better availability, broad scalability, and a higher quality of service. This paper explores the cloud computing advantages in the learning field by the integration of several technologies such as virtualization, SOA (Service Oriented Architecture) and grid computing in order to improve our pervasive learning environment: MADAR Learning.

Semantic Interoperability in the d-learning in the era of cloud computing: Simplicity or complexity

Since traditional computing of the 60s, to the innovations of the 80s, passing by emergence of internet, the virtualization advances, the concept of cloud computing have a promising future. Certainly much remains to be done especially for interoperability but also the establishment of norms and standards that will allow to build a set of heterogeneous systems.

Knowledge construction in the Connectivist Learning Environment — CLE

Technological advances have brought great changes in all areas, including education. The distance learning evolution (D-learning, E-learning and M-Learning) has prompted the adoption of the most interesting pedagogical approaches such as constructivism and social-constructivism... The adoption of these pedagogical trends improved the quality of learning by providing the personalization of learning and collaborative learning. Through this technological evolution and with the development of the Web 2.0, a new pedagogical approach called Connectivism has emerged [1]. Its a promising pedagogical approach that covers learning in heterogeneous communities (humans or not) and is based on the contribution of new technologies. However, Web 2.0 is not efficient to reach distributed knowledge in networks in a smart way and where the ability to learn becomes more and more important [2]. The objective of our works is to conceive and implement CLE Connectivist Learning Environment which is a clouded and ubiquitous learning environment. The intended purpose is to adopt connectivism as a pedagogical approach in order to construct knowledge through collaboration between heterogeneous communities composed of humans and intelligent objects.

Platform for Dynamic Adaptation of Learning Content for Pervasive Learning Environments

With the evolution and convergence of wireless technologies, mobile devices and sensors, the mobile and ubiquitous learning have appeared next to the e-learning. Far from being simple extensions of distance learning, they pose several challenges. Most of learning content used in learning platforms are built to be consumed on broadband networks and powerful terminals. However, technological advances have allowed their access over low-flow wireless networks, and terminals with limited resources such as ubiquitous and mobile devices. With this type of access, there is a strong need for learning content adaptation systems. Our work focuses on pervasive learning environments which are the new trends of distant learning and proposes to solve a big range of constraints posed by the use of various technologies in learning. We are interested in studying the various limitations of learning in pervasive environments and the development of a platform for dynamic adaptation of learning content, taking into account the challenges posed by the evolving learning context.

Time Aware Recommendation

The overload of information can become a significant challenge in relation to information retrieval systems. Often users will need to carry out extensive research to get the information they desire. This issue will only become more challenging as the quantity of data available on the internet increases. This increase shows no signs of slowing down and inevitably demands better solutions. One such solution proposed in this paper will look at the quality of the service discovery, such as adaptation customizing recommendation. In our project we considered ways to customize the contextual recommendation by creating a time awareness system.

Promises and Challenges with Organization 2.0 Paradigm

This paper focuses on five challenges we consider the most relevant for any future organization that seeks sustain advantage. For each of these challenges, we sought an inspiration that may offer a useful analogy to stimulate and guide our thinking. Next, we selected three companies whose success has been the most consistent throughout the 20 th century and which have provided innovative solutions to our problems. After having briefly presented them, we highlighted some of the lessons learned from them. We finish by describing design features of the organization 2.0.

Multicriteria-Based Decision for Services Discovery and Selection

The requirements brought by the heterogeneity of service discovery protocols leads to a non-optimal resource distribution in pervasive environments. In such environments, servers and clients use different discovery protocols respectively for publishing or looking for services. Such lack of cooperation between discovery protocols (SDP) reduces the network performance. The interoperability between (SDP) would allow users using a large variety of devices to discover and make use of numerous network-based services. However, selecting the most favorable service among a set of appropriate services according to a given request, can become complex and time-consuming for the user. In such situations, interaction between the user and the device should be minimal for ease of use.The main goal of this work is to improve the service discovery, by including intelligent service selection based on AHP multi-criteria methods within an OSGi-based middleware for service discovery.

Identity Management Systems: Techno-Semantic Interoperability for Heterogeneous Federated Systems

The identity management domain is a huge research domain. The federated systems proved on theirs legibility to solve a several digital identity issues. However, the problem of interoperability between federations is the researcher first issue. The researchers final goal is creating a federation of federations which is a large meta-system composed of several different federation systems. The previous researchers’ technical interoperability approach solved a part of the above-mentioned issue. However, there are some-others problems in the communication process between federated systems. In this work, the researcher target the semantic interoperability as a solution to solve the exchange of attribute issue among heterogeneous federated systems, because there is a significant need of managing the users’ attributes coming from different federations. Therefore, the researcher proposed a semantic layer to enhance the previous technical approach with the aim to guarantee the exchange of attribute that has the same semantic signification but a different representation, all that based on a mapping and matching between different anthologies. This approach will be applied to the academic domain as the researcher application domain.

A Semantic Recommender Engine for Idea Generation Improvement

In order to develop the ability to be competitive in considering rapidly growing global market and enormously changing in technology, organizations are looking for up-to-date procedures to respond to all these transformations. Being smart and innovative is actually the most significant pillars of successful organization strategies. In other words, organizations need to encourage learning, manage knowledge and create innovative ideas. A major issue of creative ideation is improving the quality of the ideas generated. In this paper, we propose a semantic recommender engine for idea generation in order to assist organizations to improve their ways of generating new ideas. Through this novel system, innovation actors will be able to consider new perspectives, make new connections, think differently and thus produce new promising ideas. We initially introduce the concept behind a smart organization, explore the idea generation in such organizations and examine the role of recommender systems for managing this stage and identifying breakthrough ideas. Next, we present the context of design, the conceptual architecture of the suggested system and finally expand the workflow of semantic similarity matching of ideas with a focus on the key components of the semantic recommendation engine.

Towards Innovation Excellence: Why and How to Measure Innovation Performance?

To maintain competitive advantage, today organizations need to be able to innovate - not just occasionally, but consistently. Mastering the process of innovation requires identifying the factors that support or hamper the achievement of innovations. The success of such process usually depends on the quality of the best opportunity identified, which is not enough. So, a systematic research and delivery framework spawning a set of performance measurements and improvement metrics is required, because, what is not measurable cannot be neither managed nor improved. This paper identifies three complementary components specifically developed to enable such measurement. First, Innovation Granularity Scales enabling highly targeted yet flexible performance analysis ranging from knowledge assessment to high level progressions and improvements; Second, Innovation Capability Stages referring to the minimum capabilities required by transformational milestones along the innovation continuum; Third, Innovation Maturity Levels representing the quality, predictability and performance within the innovation stages. This paper explores these complementary components and presents them as a systematic model underlying a specified innovation performance measurement framework.