Context-Aware and Adaptable eLearning Systems

The full text file attached to this record contains a copy of the thesis without the authors publications attached. The list of publications that are attached to the complete thesis can be found on pages 6-7 in the thesis.This thesis proposed solutions to some shortcomings to current eLearning architectures. The proposed DeLC architecture supports context-aware and adaptable provision of eLearning services and electronic content. The architecture is fully distributed and integrates service-oriented development with agent technology. Central to this architecture is that a node is our unit of computation (known as eLearning node) which can have purely service-oriented architecture, agent-oriented architecture or mixed architecture. Three eLeaerning Nodes have been implemented in order to demonstrate the vitality of the DeLC concept. The Mobile eLearning Node uses a three-level communication network, called InfoStations network, supporting mobile service provision. The services, displayed on this node, are to be aware of its context, gather required learning material and adapted to the learner request. This is supported trough a multi-layered hybrid (service- and agent-oriented) architecture whose kernel is implemented as middleware. For testing of the middleware a simulation environment has been developed. In addition, the DeLC development approach is proposed. The second eLearning node has been implemented as Education Portal. The architecture of this node is poorly service-oriented and it adopts a client-server architecture. In the education portal, there are incorporated education services and system services, called engines. The electronic content is kept in Digital Libraries. Furthermore, in order to facilitate content creators in DeLC, the environment Selbo2 was developed. The environment allows for creating new content, editing available content, as well as generating educational units out of preexisting standardized elements. In the last two years, the portal is used in actual education at the Faculty of Mathematics and Informatics, University of Plovdiv. The third eLearning node, known as Agent Village, exhibits a purely agent-oriented architecture. The purpose of this node is to provide intelligent assistance to the services deployed on the Education Pportal. Currently, two kinds of assistants are implemented in the node - eTesting Assistants and Refactoring eLearning Environment (ReLE). A more complex architecture, known as Education Cluster, is presented in this thesis as well. The Education Cluster incorporates two eLearning nodes, namely the Education Portal and the Agent Village. eLearning services and intelligent agents interact in the cluster

InfoStation-based Adaptable Provision of m Learning Services: Main Scenarios

This paper presents an adaptable InfoStation-based multi-agent system facilitating the mobile eLearning (mLearning) service provision within a University Campus. A horizontal view of the network architecture is presented. Main communications scenarios are considered by describing the detailed interaction of the system entities involved in the mLearning service provision. The mTest service is explored as a practical example. System implementation approaches are also considered

Intelligent Car Parking Locator Service

This paper presents an InfoStation-based multi-agent system facilitating a Car Parking Locator service provision within a University Campus. The system network architecture is outlined, illustrating its functioning during the service provision. A detailed description of the Car Parking Locator service is given and the system entities’ interaction is described. System implementation approaches are also considered

Policy-based approach for context-aware systems

Pervasive (ubiquitous) computing is a new paradigm where the computers are submerged into the background of the everyday life. One important aspect of pervasive systems is context-awareness. Context-aware systems are those that can adapt their behaviours according to the current context. Context-aware applications are being integrated into our everyday activity aspects such as: health care, smart homes and transportations. There exist a wide range of context-aware applications such as: mobile phones, learning systems, smart vehicles. Some context-aware systems are critical since the consequence of failing to identify a given context may be catastrophic. For example, an auto-pilot system is a critical context-aware system; it senses the humidity, clouds, wind speed and accordingly adjusts the altitude, throttle and other parameters. Being a critical context-aware system has to be provably correct. Policy-based approaches has been used in many applications but not in context-aware systems. In this research, we want to discover the anatomy (i.e. architecture, structure and operational behaviour) of policy-based management as applied to context-aware systems, and how policies are managed within such a dynamic system. We propose a novel computational model and its formalisation is presented using the Calculus of Context-aware Ambients (CCA). CCA has been proposed as a suitable mathematical notation to model mobile and context-aware systems. We decided to use CCA due to three reasons: (i) in CCA, mobility and context-awareness are primitive constructs and are treated as first-class citizens; (ii) properties of a system can be formally analysed; (iii) CCA specifications are executable, and thus, leading to rapid prototyping and early validation of the system properties. We, then show how policies can be expressed in CCA. For illustration, the specification of the event-condition-action (ECA) conceptual policy model is modelled in CCA in a natural fashion. We also propose a policy-based architecture for context-aware systems, showing its different components, and how they interact. Furthermore, we give the specification of the policy enforcement mechanism used in our proposed architecture in CCA. To evaluate our approach, a real-world case study of an infostation-based mobile learning (mLearning) system is chosen. This mLearning system is deployed across a university campus to enable mobile users to access mobile services (mServices) represented by course materials (lectures, tests and tutorials) and communication services (intelligent message notification and VoIP). Users can access the mServices through their mobile devices (Hand-set phones, PDAs and laptops) regardless of their device type or location within a university campus. We have specified the mLearning system in CCA (i.e. specification based on policies of the mServices), afterwards, the specification is simulated using the CCA interpreter tool. We have developed an animation tool specially designed for the mLearning system. The animation tool provides graphical representation of the CCA processes. In terms of safety and liveness, some important properties of the mLearning system have been validated as a proof of concept

Intelligent Systems

This book is dedicated to intelligent systems of broad-spectrum application, such as personal and social biosafety or use of intelligent sensory micro-nanosystems such as "e-nose", "e-tongue" and "e-eye". In addition to that, effective acquiring information, knowledge management and improved knowledge transfer in any media, as well as modeling its information content using meta-and hyper heuristics and semantic reasoning all benefit from the systems covered in this book. Intelligent systems can also be applied in education and generating the intelligent distributed eLearning architecture, as well as in a large number of technical fields, such as industrial design, manufacturing and utilization, e.g., in precision agriculture, cartography, electric power distribution systems, intelligent building management systems, drilling operations etc. Furthermore, decision making using fuzzy logic models, computational recognition of comprehension uncertainty and the joint synthesis of goals and means of intelligent behavior biosystems, as well as diagnostic and human support in the healthcare environment have also been made easier

E-Learning

E-learning enables students to pace their studies according to their needs, making learning accessible to (1) people who do not have enough free time for studying - they can program their lessons according to their available schedule; (2) those far from a school (geographical issues), or the ones unable to attend classes due to some physical or medical restriction. Therefore, cultural, geographical and physical obstructions can be removed, making it possible for students to select their path and time for the learning course. Students are then allowed to choose the main objectives they are suitable to fulfill. This book regards E-learning challenges, opening a way to understand and discuss questions related to long-distance and lifelong learning, E-learning for people with special needs and, lastly, presenting case study about the relationship between the quality of interaction and the quality of learning achieved in experiences of E-learning formation

Context-Aware and Adaptive Usage Control Model

Information protection is a key issue for the acceptance and adoption of pervasive computing systems where various portable devices such as smart phones, Personal Digital Assistants (PDAs) and laptop computers are being used to share information and to access digital resources via wireless connection to the Internet. Because these are resources constrained devices and highly mobile, changes in the environmental context or device context can affect the security of the system a great deal. A proper security mechanism must be put in place which is able to cope with changing environmental and system context. Usage CONtrol (UCON) model is the latest major enhancement of the traditional access control models which enables mutability of subject and object attributes, and continuity of control on usage of resources. In UCON, access permission decision is based on three factors: authorisations, obligations and conditions. While authorisations and obligations are requirements that must be fulfilled by the subject and the object, conditions are subject and object independent requirements that must be satisfied by the environment. As a consequence, access permission may be revoked (and the access stopped) as a result of changes in the environment regardless of whether the authorisations and obligations requirements are met. This constitutes a major shortcoming of the UCON model in pervasive computing systems which constantly strive to adapt to environmental changes so as to minimise disruptions to the user. We propose a Context-Aware and Adaptive Usage Control (CA-UCON) model which extends the traditional UCON model to enable adaptation to environmental changes in the aim of preserving continuity of access. Indeed, when the authorisation and obligations requirements are fulfilled by the subject and object, and the conditions requirements fail due to changes in the environmental or the system context, our proposed model CA-UCON triggers specific actions in order to adapt to the new situation, so as to ensure continuity of usage. We then propose an architecture of CA-UCON model, presenting its various components. In this model, we integrated the adaptation decision with usage decision architecture, the comprehensive definition of each components and reveals the functions performed by each components in the architecture are presented. We also propose a novel computational model of our CA-UCON architecture. This model is formally specified as a finite state machine. It demonstrates how the access request of the subject is handled in CA-UCON model, including detail with regards to revoking of access and actions undertaken due to context changes. The extension of the original UCON architecture can be understood from this model. The formal specification of the CA-UCON is presented utilising the Calculus of Context-aware Ambients (CCA). This mathematical notation is considered suitable for modelling mobile and context-aware systems and has been preferred over alternatives for the following reasons: (i) Mobility and Context awareness are primitive constructs in CCA; (ii) A system's properties can be formally analysed; (iii) Most importantly, CCA specifications are executable allowing early validation of system properties and accelerated development of prototypes. For evaluation of CA-UCON model, a real-world case study of a ubiquitous learning (u-learning) system is selected. We propose a CA-UCON model for the u-learning system. This model is then formalised in CCA and the resultant specification is executed and analysed using an execution environment of CCA. Finally, we investigate the enforcement approaches for CA-UCON model. We present the CA-UCON reference monitor architecture with its components. We then proceed to demonstrate three types of enforcement architectures of the CA-UCON model: centralised architecture, distributed architecture and hybrid architecture. These are discussed in detail, including the analysis of their merits and drawbacks

Modeling, Designing, and Implementing an Ad-hoc M-Learning Platform that Integrates Sensory Data to Support Ubiquitous Learning

Learning at any-time, at anywhere, using any mobile computing platform learning (which we refer to as “education in your palm”) empowers informal and formal education. It supports the continued creation of knowledge outside a classroom, after-school programs, community-based organizations, museums, libraries, and shopping malls with under-resourced settings. In doing so, it fosters the continued creation of a cumulative body of knowledge in informal and formal education. Anytime, anywhere, using any device computing platform learning means that students are not required to attend traditional classroom settings in order to learn. Instead, students will be able to access and share learning resources from any mobile computing platform, such as smart phones, tablets using highly dynamic mobile and wireless ad-hoc networks. There has been little research on how to facilitate the integrated use of the service description, discovery and integration resources available in mobile and wireless ad-hoc networks including description schemas and mobile learning objects, and in particular as it relates to the consistency, availability, security and privacy of spatio-temporal and trajectory information. Another challenge is finding, combining and creating suitable learning modules to handle the inherent constraints of mobile learning, resource-poor mobile devices and ad-hoc networks. The aim of this research is to design, develop and implement the cutting edge context-aware and ubiquitous self-directed learning methodologies using ad-hoc and sensor networks. The emphasis of our work is on defining an appropriate mobile learning object and the service adaptation descriptions as well as providing mechanisms for ad-hoc service discovery and developing concepts for the seamless integration of the learning objects and their contents with a particular focus on preserving data and privacy. The research involves a combination of modeling, designing, and developing a mobile learning system in the absence of a networking infrastructure that integrates sensory data to support ubiquitous learning. The system includes mechanisms to allow content exchange among the mobile ad-hoc nodes to ensure consistency and availability of information. It also provides an on-the-fly content service discovery, query request, and retrieving data from mobile nodes and sensors

Une Approche pour le M-Learning dans le Cloud

Le d´eveloppement rapide des r´eseaux sans fil et des technologies mobiles a jou´e un r^ole important dans l’´evolution de la vie quotidienne. La technologie mobile et ses services facilitent la communication et le contact entre les personnes, quel que soit le lieu o`u ils se trouvent. Les appareils portables d’aujourd’hui peuvent ^etre utilis´es pour acc´eder et g´erer de nombreux types de donn´ees, d’un simple texte `a des dossiers multim´edias plus complexes. On peut affirmer que les environnements ´educatifs ne se limitent pas aux ´ecoles ou aux universit´es. Avec l’utilisation de la technologie au sein des syst`emes ´educatifs, les moyens d’acc`es `a l’information ont chang´e et de nouveaux concepts tels que l’apprentissage mobile ont ´emerg´e. Ceci dit, ce nouveau paradigme d’apprentissage soul`eve de nombreux d´efis auxquels les chercheurs sont confront´es pour assurer l’accessibilit´e `a tous les ´etudiants, suivre le rythme inou¨ı de la technologie, des pr´ef´erences et du contexte d’apprentissage L’objectif de cette th`ese est de concevoir un syst`eme d’apprentissage plus adapt´e et de le mettre en œuvre en se basant sur des agents qui prennent en charge la sensibilisation au contexte et le contenu d’apprentissage personnalis´e `a l’aide du Cloud Computing. Le syst`eme fournit un contenu d’apprentissage dispens´e par le biais d’appareils mobiles et adapt´e aux pr´ef´erences et au style d’apprentissage de l’apprenant, et ceci dans le but d’augmenter la satisfaction de l’apprenant et faciliter la r´eussite de l’apprentissage. Le syst`eme comprend des avantages des applications mobiles, des syst`emes multi-agents, de la sensibilit´e au contexte, de la personnalisation p´edagogique et du Cloud Computing. La prise en charge de la sensibilisation au contexte et de la personnalisation est essentielle dans les syst`emes d’apprentissage mobiles, afin qu’ils puissent am´eliorer l’efficacit´e de l’apprentissage et rendre l’apprentissage pertinent d’un point de vue contextuel. Les agents sont habitu´es `a b´en´eficier de leurs avantages qu’ils soient autonomes, r´eactifs, proactifs et sociaux. Les ressources informatiques peuvent ^etre partag´ees entre plusieurs ordinateurs sur un r´eseau ; par cons´equent, seul l’agent de contexte de l’apprenant doit ^etre install´e sur les appareils mobiles de l’apprenant. Le Cloud Computing permet aux apprenants d’acc´eder au contenu d’apprentissage dans tous les lieux o`u la connexion Internet est disponible. Le syst`eme a ´et´e mis en œuvre et test´e avec des ´etudiants du d´epartement d’informatique de l’Universit´e de Middlesex, Londres, Royaume-Uni, ainsi qu’avec des ´etudiants du d´epartement des sciences et technologies de l’Universit´e de T´ebessa, Alg´erie. Les r´esultats exp´erimentaux d´emontrent l’utilit´e et l’efficacit´e de notre syst`eme dans la pratique. Les ´etudiants ont convenu que le mat´eriel de cours pr´esent sur leur ’smart phones’ est tr`es clair, le mat´eriel d’apprentissage recommand´e par le syst`eme est tr`es pertinent dans leur contexte, et le syst`eme d’apprentissage mobile sensible au contexte propos´e est tr`es pratique. Ce dernier repr´esente un outil d’apprentissage utile pour aider le processus d’apprentissage et cela peut promouvoir leurs int´er^ets d’apprentissage