Knowledge-on-Demand in e-Learning and e-Working Settings
The emergence of the knowledge society and the knowledge-based economy signify a new era for education and training. In the traditional economy, the physical capital and material resources have been the driving force, whereas, the new economy is driven by human/intellectual capital and knowledge. As computer-based systems tend to take over the linear, repetitive functions that 20th century workers used to perform, the new economy workers are expected to focus on problem-solving and critical thinking tasks (Hartley, 2000). Furthermore, rigid organisational structures are gradually replaced by adaptive, semi-autonomous, virtual organisations that rely on decentralised responsibilities and expertise - “learning organisations” which aim to attain success through the ability to learn faster than their competitors (Senge, 1990).
Within this framework, knowledge and skills of citizens are becoming increasingly important both for the economical strength and social cohesion of the society, and the quality of citizens’ life. The structural and functional society transformations raise the demand for major reforms in education and training, aiming at reducing the risks for knowledge gaps and social exclusion.
An interesting political and scientific debate is continuing about the paradigm shifts in the way that education and training is planned, organised and delivered, as well as the definition of concrete future objectives of educational systems. Typical demands include (Sampson, 2001):
The above trends call for a new paradigm for education and training, which goes beyond traditional practice, encompassing creative and critical thinking, communication skills, the ability to find information, as well as the ability to interact with others and so on. In this context, the importance of flexible, personalised life-long learning is widely acknowledged. Personalised learning takes a learner-centred approach to education, advocating that it is the learning environment that should be adapted to the learner, rather than the opposite. The individual learner is responsible for his/her own self-directed, life-long education and training, and technology is used to effectively assist to this end. Under this perspective, a new paradigm of on-demand learning emerges, where the “anyone, anytime, anywhere” delivery of education and training is adapted to the specific requirements and preferences of each individual citizen within different e-learning and e-working settings.
This paper outlines some of the requirements for on-demand learning, in terms of the two broad user categories involved in this context: people interested in accessing learning material, applications and services within different e-learning and e-working settings, and people interested in authoring and publishing learning material, or providing e-learning applications and services. The paper also outlines a set of typical tasks that are necessary for supporting on-demand learning, as well as our work for developing the enabling technology to meet these requirements.
The objective of our work is to contribute in relation to the increasing requirements for on-demand learning. That is, the demand for easy access to high-quality learning material and e-learning applications and services within different e-learning and e-working settings, in a personalised way; as well as the supply of on-demand learning material and e-learning applications and services (European Commission, 2000).
In this context, our work addresses two main broad categories of users (see figure 1).
Citizens of the knowledge society, interested in accessing learning material and/or e-learning applications and services, from internal (to their organisation, community, etc) and external knowledge repositories, within different contexts of use. Front-end users include:
Front-end users require efficient, effective, just-in-time and context-sensitive access to learning material and/or e-learning applications and services, anytime and anywhere, in apersonalised way, according to their individual (and continuously changing) needs, requirements, preferences, skills, background, and so on.
Individuals or organisations interested in publishing learning material, or providing e-learning applications and services. Back-end users may have different roles, business interests, and so on:
Back-end users require tools that can enable them to meet the requirements of front-end users for on-demand, personalised learning within different e-learning and e-working settings. Moreover, they require tools which can enable them to author and publish learning material and provide e-learning applications and services in an interoperable and re-usable way.
Following the identification of the groups of users and the analysis of their needs, we have defined a set of high-level typical tasks that should be available for front- and back-end users for supporting on-demand learning. The scenarios for front-end users and back-end users are presented in Figure 2 and Figure 3, respectively, and are briefly described below.
Front-end users need to be able to authenticate themselves, as well as define, edit and save their personal user profile for receiving personalised services. Then, front-end users need to search into internal and external knowledge repositories, through local and remote search agents, and retrieve learning material according to their specific requirements and preferences. Based on the results of these (personalised) searches, front-end users need to be able to build, edit, update and save personal knowledge routes – collections of learning resources which are appropriate for their needs. Finally, front-end users need to “interact” with these knowledge routes for improving their knowledge, and have their profile updated accordingly. Front-end users require these actions to be contextualised, that is, based on their changing requirements within different e-learning and e-working settings.
Back-end users need to be able to publish their learning material in a commonly accessible format, so that it can be effectively and efficiently searched and retrieved in the different contexts of use described in section 0. This, in turn, requires that back-end users can describe the meta-data of each resource, as well as the competencies, questions & tests, etc, that are related to each resource. Moreover, this description should be according to a common ontology, to promote semantic interoperability of resources. Also, back-end users need to be able to describe collections of resources (as opposed to “atomic” resources), as well as how these collections are disaggregated, so that different knowledge routes (parts of the learning packages) are presented according to different user profiles, thus meeting the requirements for on-demand, personalised learning. This involves the definition and editing of the respective user profiles through a knowledge routes toolkit. Finally, back-end users need to be able to “configure” their applications and services, so that they can meet diverse requirements. This involves a set of “agents”, which can act as a communication, integration and customisation mechanism.
Towards a Technical Solution
It can be argued that the current state-of-the-art does not adequately support the requirements identified in the previous sections, and especially for:
In this context, we are currently working on a technical solution which can overcome some of the above limitations, and can meet the requirements for on-demand learning. We are working on the knowledge packaging format, an extension of the current version of the IMS Content Packaging specification, to enable the definition of adaptive educational content (see Figure 4).
The knowledge packaging format facilitates the description, in a common format, of the learning objects comprising each learning package, together with navigational rules which define which parts of the learning package should be selected for different learner profiles. As a result, an e-learning system can import knowledge packages (i.e. collections of learning objects described through the knowledge packaging format), interpret the rules included in them, and present different knowledge routes to each learner, according to his/her profile, thus facilitating personalised learning. Moreover, adaptive knowledge packages (i.e. adaptive learning material) can be easily interchanged and re-used across different e-learning applications and services, thus promoting on-demand, personalised learning (see Karagiannidis et al., 2001a, 2001b).
Based on the knowledge packaging format, we have developed an architecture which enables back-end users to produce adaptive learning material which can be easily exchanged and re-used. In particular, we are developing:
The above developments are planned to be demonstrated into two different scenarios, to assess the impact of our work into different learning and working settings. Both scenarios involve the development of adaptive learning material (in the tele-medicine and knowledge management domains, respectively) by back-end users through the above mentioned tools. In the first scenario, a group of life-long learners will have personalised access to tele-medicine adaptive learning material within an e-learning setting. While, in the second scenario, knowledge workers of a high-technology company will have personalised access to knowledge management adaptive learning material within an e-working setting, i.e. during their every day working activities, to improve their performance in their everyday tasks, and their competency in the knowledge-based economy.
Part of the work reported in this paper is carried our in the context of the KOD “Knowledge on Demand” Project (www.kodweb.org, kod.iti.gr), which is partially funded by the European Commission through the Information Society Technologies Programme, under Contract No IST-1999-12503.