Grid technologies are rising as the next generation of Internet by defining a powerful computing paradigm by analogy with the electric Power Grid. A Grid user is able to use his private workplace to invoke applications from a remote system, use the system best suited for executing that application, access data securely and consistently from remote sites, exploit multiple systems to complete economically complex tasks or to solve large problems that exceed the capacity of a single system.

Grid could be used as a technology “glue” providing users with a uniform way to access resources by means of several devices. These technologies can provide, in a natural way, a support for Technology Enhanced Learning (TEL) by enabling new learning environments based on collaboration, real direct experience, personalisation, ubiquity, accessibility and contextualisation.

Nevertheless, to be effectively used in TEL, Grid must be complemented with other elements like semantics and educational modelling leading to the concept of “Learning Grid” as defined in the homonymous Special Interest Group (SIG) of the European Network of Excellence “Kaleidoscope: Shaping the Scientific Evolution of Technology Enhanced Learning”.

The key challenge that Kaleidoscope is facing is the scientific and structural integration of the European TEL research. In this context, the Learning Grid SIG aims at contributing to the achievement of an improvement in TEL practices through the definition of open, distributed and pervasive environments for effective human learning, taking into account that effective learning requires an active attitude from learners and that learning is a social and collaborative activity requiring a technology that allows for active and realistic experiments, personalization, knowledge creation and evolution, as well as autonomous and dynamic creation of communities.

The research program of the Learning Grid SIG encompasses the definition of challenging scenarios for distributed service-oriented TEL, the analysis of technologies for creating distributed service-oriented TEL environments as well as the analysis of languages and frameworks for the dynamic composition of distributed TEL resources and services. Starting from that, the purpose of this book is to update, harmonize and consolidate obtained research results.

The first section of the book is about the concept of Learning Grid and related technologies. The first chapter gives a formal definition of the Learning Grid as an enabling architecture based on Grid, Semantics and Educational Modelling allowing the definition and the execution of TEL experiences obtained as cooperation and composition of distributed heterogeneous actors, resources and services. This chapter also presents an abstract architecture for the Learning Grid, a set of suitable learning approaches and some related research work.

The second chapter analyses and compares existing languages for the dynamic composition of distributed learning resources and services in a Learning Grid. It is worth noting that the application of such languages is important where heterogeneous services have to be dynamically composed according to learners' needs and preferences and to teacher defined learning methods and strategies. Based on that, the third chapter gives an overview of the main approaches to tackle the problems of semantic description and matchmaking of Learning Grid Services.

The fourth chapter concludes the first section with the definition of challenging application scenarios in the TEL domain that can be approached with a Learning Grid. The purpose is to understand and argue about the potential advantages of adopting a Learning Grid and to show why its features are paramount to improve personalisation and knowledge construction in the learning process as well as communication and collaboration inside learning groups.

The second section of the book is purposed to share research results obtained by European research groups connected with the Learning Grid SIG in their own projects on the field.

Chapter 5 is centred on some of the results of the ELeGI project: after having presented a theoretical learning model which allows to generate personalised learning experiences and to dynamically adapt them during the learning process, a Learning Grid software architecture created modifying the Intelligent Web Teacher (IWT) innovative learning platform and conceived for supporting the execution of the processes defined in the learning model, is described.

Chapter 6 presents an overview of Gridcole, a grid service-based tailorable collaborative TEL system enabling the integration of tools requiring supercomputing capabilities or specific hardware resources in order to support collaborative learning situations in which these types of tools are required and, at the same time, able to interpret collaboration scripts created by educators in order to guide participants during the realization of collaborative learning situations.

Chapter 7 presents a grid-based Virtual Observatory built in the AstroGrid project and explores how such a grid can be used as an e-learning platform for a wider audience. Moreover, in order to facilitate teacher interaction with remote students and to increase the interactivity level of the virtual classroom, the integration of Augmented Reality applications is also discussed.

Chapter 8, starting from the consideration that mobile and grid technologies provide complementary features that can address the requirements of next generation e-learning applications, presents some of the results of the Akogrimo project designed to build a platform based on both mobile and grid technologies and, in particular, discusses an m-learning scenario built on such platform.

Chapter 9 presents L4All: a system, coming from the homonymous project, able to record and share learning trails through educational offerings with the aim of facilitating progression of lifelong learners from Secondary Education, through to Further Education and on to Higher Education. The focus of the chapter is on the description of the service-oriented architecture of the system enabling a comprehensive set of educational activities.

Chapter 10 presents some results of the SeLeNe project which investigated the feasibility and designed tools to support learning communities (self e-learning networks) by matching learners' needs with educational resources potentially available on the Web. The focus is on the description of the personalisation services designed and developed using a combination of Web Service and Semantic Web technologies.

Chapter 11 presents a grid-based approach to capture and structure the information generated by collaborative learning activities in order to extract relevant knowledge and to provide learners and tutors with efficient awareness and feedback as regards group performance and collaboration. The authors demonstrate how a grid-based approach can considerably decrease the time of processing group activity log files and thus allow group learners to receive selected knowledge even in real time.

Chapter 12 presents a Virtual Scientific Experiment framework designed and developed on top of a grid infrastructure for running interactive virtual laboratory experiments for distributed student communities with visualization capabilities. The architecture is based on Web Services standard protocols such as WSDL and WS-Notification as implemented in the WSRF specification. The chapter also presents system evaluation results from a distributed pool of students showing the added value of the framework in enhancing distance-learning programs and Virtual Classes with extensible collaborative and interactive Virtual Laboratories sessions.

Chapter 13 presents ActiveMath, a Web-based TEL environment for mathematics, and discusses it from service and semantics perspectives. The service-oriented architecture of the system is described and how component services interplay with the domain and the pedagogical semantics used is shown. Details on the knowledge representation for mathematics are provided and how it is used to represent learning material and learning goals is explained as well as how a course generator assembles sequences of learning objects to fulfil these goals.

Saverio Salerno, Dept. of Information Engineering and Applied Mathematics, University of Salerno