ELeGI: The European Learning GRID Infrastructure Pierluigi Ritrovato,Matteo Gaeta CRMPA, University of Salerno, Italy Alan Ruddle, Colin Allison School of Computer Science University of St Andrews, Scotland

Overview Motivation Project Aims Advanced Learning Environment Features Grid Service-based Learning Environments ELeGI Activities Summary Example Demonstrator: Finesse Learning environment Monitoring and Adaptation Conclusions

Motivation Lack of effective existing e-Learning practices and environments Based on the information transfer paradigm with focus on the content and the “teacher” Technology driven approach –e-Learning becomes an activity in which teachers produce, and students consume, multimedia books on the Web In the new approach, knowledge construction, rather than information transfer, is the key. The focus is on the learner and on the learning strategies that better satisfy the learner characteristics

Project Consortium 23 partners from 8 Countries –13 Universities (2 Open Universities) –4 Industrial partners –6 research Centres

characteristics of future learning scenarios Based on new learning approaches –Experiential –Contextualised –Collaborative –Personalised Extensive use of advanced technologies and software solutions virtualised as services –Virtual Reality –Virtual Laboratory –Video conferencing Service Orientation –not product oriented! Dynamicity Strong need for interoperability Open Architecture and standards Security and Trust Issues

Main Goals 1.To define new models of human learning enabling ubiquitous and collaborative learning, merging experiential, personalised and contextualised approaches 2.To define and implement an advanced service-oriented Grid based software architecture for accessing and integrating different technologies, resources and contents needed to realise the new paradigm 3.To validate and evaluate the software architecture and the didactical approaches through the use of SEES and demonstrators

Features of the new paradigm Collaboration: group working should be supported routinely; dynamically formed virtual communities Experiential: the learner is genuinely involved Realism: real-world input should be easy to incorporate, as should simulations, ranging from simple interactive animations to immersive VR Personalised: students should find themselves at the centre of their online environment, with their individual needs addressed Ubiquity and Accessibility: –wider, more flexible access to educational resources should be provided, often referred to as “anytime/anywhere” learning. –multiple different types of devices, interfaces, and network connection types should be supported where possible Contextualised: appropriate learning contexts may naturally be short-lived, as well as the more traditional static situations such as the classroom and the library – this calls for dynamicity in the creation of contexts

What does the Grid bring ? Common infrastructure –OGSA, WSDL, UDDI, etc Component sharing Dynamic Service Composition Combined resources for enhanced functionality and power Open architecture and open standards Registry Service Requester Service Provider

ELeGI Activities Design and Implementation of Service Oriented infrastructure Pedagogical and Usability Evaluation The Learning GRID Infrastructure GRID Technologies Dissemination Exploitation SEES & Demos Didactical Models Knowledge Repres. Enhanced Presence Convers. processes

Example Learning Environment: Finesse Finesse: finance education in a scaleable software environment Supports teaching of fund management Virtual portfolios at the core –Buy/sell shares –Try to make a profit relative to market Inspect historic data “Notebook” messaging tool for asynchronous collaboration

Finesse future Re-engineer to be GSDL based Synchronous communications –Video conferencing –Synchronous groupware Device independence

Enhanced Presence

FiGS – Finesse Grid Services Browser Video User Web Servlets GS:ManagerGS:Manager GS: Notebook GS: Conferencing GS: Portfolio GS: Stock Data Source 1 GS: Stock Data Source 2 Finesse Services Grid ServicesWeb Services

Technical implications Grid-service-based learning environments (LEs) -> Quality of Service (QoS)  Dangerous assumption – that there will be QoS “on demand” for the Grid Realistic assumption: Grid-based LEs must make use of available infrastructure e.g. the Internet

Internet QoS Approaches Ostrich algorithm –No requirements from infrastructure –No guarantees! Wide variance in quality Resource Reservation –Admission Control, schemes: RSVP, IntServ –Major requirements on infrastructure Aggregate Flows –Modest requirements on infrastructure, MPLS –Deployed at edge, no state at ‘core’ routers: DiffServ –Scales well within single administrative domains Adaptive QoS –End-to-end for users –No requirements on infrastructure –Deployable at the local network level

Adaptive QoS Provision Past network conditions -> statistics –TCP/ RTP/RTCP traffic monitoring Estimate likely network path conditions –Temporal & spatial patterns in traffic Inform learning resource at start Learning resource adapts to changes

Conceptual Framework: Location Information Server

Conference Controller Architecture for Video Conferencing

QoS Summary the assumption of QoS provision in Grid based applications, which use the Internet, is an unsafe one it is beneficial to use measures which predict the likely QoS provision and adapt to it how to provide a QoS aware service to a Grid conferencing service so that it can be adaptive, and to that extent, contextualized for each participant we have successfully integrated a prototype of this system into an existing learning environment (Finesse) the feasibility and potential of mechanisms for achieving adaptive, dynamically constituted conference sessions has been shown Future: QoS advisory service more automated and available for use in any Grid-based collaborative learning environment

ELeGI Expected results The service oriented GRID based Software Architecture; Formalisation of didactical models for the new learning approaches; Methodologies for evaluating the effectiveness of these new learning approaches from the pedagogical and usability points of view; Prototypes for demonstrating the potential offered by the ELeGI technologies and methodologies; Methodologies and techniques for making existing applications Grid-aware; Contribution to the technical standards in the Learning, semantic Web, and Grid domains; Workshops, Conferences, Publications, Information Web sites, and Demonstrator Web sites;