In Global Peace Through The Global University System

2003 Ed. by T. Varis, T. Utsumi, and W. R. Klemm

University of Tampere, Hameenlinna, Finland

HUMAN LEARNING AS A GLOBAL CHALLENGE:

EUROPEAN LEARNING GRID INFRASTRUCTURE

Colin Allison, Stefano A. Cerri, Matteo Gaeta, Pierluigi Ritrovato, and Saverio Salerno

University of St. Andrews, Universite Montpellier II, University of Salerno

Abstract

The purpose of this paper is to describe the E-LeGI (European Learning GRID Infrastructure) Project [1] . E-LeGI has the ambitious goal of developing software technologies for effective human learning and promoting and supporting a learning paradigm shift. A new paradigm focused on knowledge construction using experiential based and collaborative learning approaches in a contextualised, personalised and ubiquitous way will replace the current information transfer paradigm, which is based on content, and on the key authoritative figure of the teacher who provides information. We have chosen a synergistic approach, sometimes called "human-centred design", to replace the classical, applicative approach to learning. As humans are at its centre, learning is clearly a social, constructive phenomenon. It occurs as a side effect of interactions, conversations and enhanced presence in dynamic virtual communities. The new paradigm will be explored through the use of experimental research concepts integrating new powerful developments of services in the Semantic GRID, the leading edge of Information and Communication Technologies (ICTs), with highly innovative and powerfully significant scenarios of human learning.

The E-LeGI project has three main objectives:

1) To study and define new models of human centred learning enabling ubiquitous and collaborative learning, merging experiential, personalised, and contextualised approaches.

2) To study, design and implement an advanced service-oriented Grid-based software architecture for learning. This will allow us to access and integrate different technologies, resources and contents that are needed in order to realise the new paradigm outlined in Objective 1.

3) Within the context of a single Integrated Project, we will research, develop, deploy, validate, and evaluate the GRID-based software architecture for learning and the human-centred approaches, through the use of SEES (Service Elicitation and Exploitation Scenarios).

The Vision

E-LeGI is concerned with developing and demonstrating a technical infrastructure able to support future learning scenarios. Briefly, the infrastructure must support communities, realism, collaborative working, formal and informal learning, new effective pedagogies, and provide access modes that are adaptable to any users' personal needs, including their current location, their current interface device, their learning preferences and special physical needs.

This section attempts to convey a feel for what the range and depth of a future scenario may look like.

An Example Scenario - Learning About the Weather

Most of us have an interest in the weather. Given the opportunity (time and other resources) we would like to learn more. So consider a community of learners who are all interested in learning about the weather - they look to the learning Grid for resources and a route to personal achievement.

The community consists of a wide variety of members who have potentially very different personal circumstances. They are spread across different parts of Europe. They speak different languages. Some are from highly developed areas, some are from relatively deprived regions. Some have special learning and physical needs. All members have access to a flexible set of high-quality learning resources, provided as services.

As they are a community they all have access to collaboration tools, allowing for mediated group formation, group awareness, group selection and a choice of group communication facilities, which transparently deal with language and special needs barriers.

The community naturally devolves into groups. Some are long-lived, some are transient, some overlap, some are mutually exclusive, some are sponsored, some are essential, most are optional.

Some members have access to the resources from their own home or work place, others may need to attend a local facility, some use sophisticated interfaces capable of immersive Virtual Reality, some use simple multimedia computers, some use disposable handheld devices, some enjoy the facility of ambient intelligence in their immediate environment.

Some learners are fully committed to using a specific collection of the available resources that have been grouped into a learning environment by a collection of institutions that offer a prescribed set of learning goals with accreditation. Others are pursuing this area of study as part of their work skills improvement or simply out of interest (quality of life).

All learners potentially have a learning profile. This includes learning preferences, special needs, prior accreditation and details of personal circumstances that may be useful to the learning environment (if revealed). The learning profile and identity of each member is guaranteed privacy and integrity. It is dynamically maintained by the infrastructure with regard to group membership, resource allocation and other aspects. Trust contracts are of course necessary for accreditation and miscellaneous other interactions.

Realism is brought into the study environment by allowing learners to attempt their own weather forecasting. A service routinely provides remote sensing data for various regions across the world. The data provided by the "learning" services has actually been filtered and formatted by processes created by experts to make it suitable for learners. Another service allows access to banks of super computers and programs, which can analyse the data. Groups of learners within the community select specific regions (from a pool of geographic areas chosen by subject-specialists for their educational attributes) to focus on and make their own weather predictions. Groups can compare the success of their predictions with those of the established professional services behind public media forecasts. They can compare their success with other groups. They can compare their success against the region being analysed. They can also delve into data banks for historical patterns in order to test their understanding. The possibilities are large.

Realism is also brought into the study environment by types of sophisticated simulation that are predicated upon advanced technological infrastructure. Aspects of meteorology require the understanding of physical processes that are difficult (or impossible) to demonstrate by real experiment. In this case Virtual Scientific Experiments and Immersive Virtual Reality can be provided for the learners to help understand these processes, and digital library content showing the manifestation of these processes e.g., sun spots, cloud formation, can be selected. At the same time, areas of mathematics and computing are also necessary to understand the models used in meteorology. Accordingly, learning resources, which focus on the specific areas of math and computing needed for weather models, are provided.

Some members of the community are less pro-active with regard to forecasting but follow the predictions closely through low-bandwidth mobile devices. They make observations and inform other interested members.

Some members see this as a long term study commitment, while others are only planning on taking part for a few days, to get a feel for the business process of forecasting and the schedules and resources involved.

Group discussions are a routine feature. This allows for division of labour and peer-mediated learning. Minimal delay means that a distributed group can have an enhanced face-to-face meeting for discussion purposes. Simultaneous language translation, where required, is transparent.

Tutors can attend group discussions, offer advice, recommend assessment exercises and levels, and if necessary identify and move disruptive or inappropriate members to different learning situations. Tutors enjoy predicate based monitoring of student progress - only special cases are immediately brought to their attention. Some learners are not associated with any tutor.

Experts (real or virtual) may also be called in by a group when it wishes to understand some very specific feature of the subject of study, and when the group has demonstrated it is ready to benefit from expert intervention.

Advancing Technology Enhanced Learning in Europe

The overall aim of the project is to radically advance the effective use of technology-enhanced learning in Europe through the design, implementation and validation of a pedagogy-driven, service-oriented software architecture for supporting ubiquitous, collaborative, experiential-based and contextualised learning. Previous projects which have set out to improve learning through novel technology have often failed to leave any significant mark because they did not give priority to the social, economic and technical perspectives of the key human actors. So, while the development and use of appropriate technology must be pedagogically driven, at the same time those involved in the formulation and evaluation of pedagogy must be made aware of, and shown by demonstration, state-of-the-art technological possibilities. We address this pervasive learning issue by explicitly listing the roles that actors play in the learning process and illustrate with reference to future learning scenarios. This provides us with a focus for formulating requirements in terms of didactical models, learning resources, services, quality of service (QoS), and usability for end-users. It also provides a clear reference for the context of the project - open and flexible software architecture for creating learning environments that accommodate the roles implied by the new learning possibilities and that demonstrate state-of-the-art technology-enhanced learning.

Our approach to human learning considers it to be a side effect of interactions and conversations (dialogues) that are enabled, supported, or enhanced by technological services both when the human actor's intention is explicit and shared (as in the case of institutional teaching) and when it is implicit (as in the case in any other human collaborative activity). Similarly, we wish to address both measurable human learning - as when a certification of acquired knowledge and skills is expected to be issued on rational basis - as well as when it is not measurable - when motivation, enthusiasm and proactive initiative generates new, unforeseen learning events.

Pedagogical Goals and New Learning Modes

In order to support the implementation of new learning modes related to ubiquitous, collaborative, experiential and contextualised learning, it is necessary to promote a paradigm shift in the general approach to teaching and learning.

Currently, teaching and learning practices are based mainly on the information transfer paradigm. This focuses on content, and on the key authoritative figure of the teacher that provides information. Teachers' efforts are mainly devoted to find the best way for presenting content in order to transmit information to learners. This has been critically referred to as the "the hydraulic view of learning". It has its roots in behaviourism, and even though it