E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective

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Then, the principles, methods, and tools required to build knowledge networks are summarized, and the problems associated with retrieving resources and knowledge in networked environments are addressed. This movement has affected different elements and components: infrastructures, tools, content-oriented applications, human—computer interactions, pedagogical issues, methodologies and models, case studies, and projects. This phenomenal development is particularly inspired by the opportunities generated by the Internet, a sophisticated computer network.

As computer networks evolve, the variety and quantity of machines available and the quantity of links used is increasing. This explains, in part, the existence of heterogeneous environments for public and private networks of boundless dimensions giving rise to many problems of incompatibility [30]. E-learning environments must address such problems. Over the last few years, an increasing number of organizations have recognized the importance of learning technologies and knowledge management [31]. Hence, tremendous investments in e-learning and telecommunication infrastructures are being made all over the world, yielding a proliferation of knowledge elements and learning components.

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As a result, it became necessary to identify, formalize, organize, and sustain the use of knowledge and learning components [4]. Despite this enthusiasm and growing interest, many problems remain to be solved before e-learning is widely adopted and deployed by organizations. Initial training in the public education sector, professional training, and personal training at home are merging.

Currently, most e-learning material is focused on transmitting information. To unleash the power of new learning technologies, new research-based solutions are needed to ensure accessible, reusable, and high-quality Web-based learning materials and activities. Such services are now available only through a small number of communication link types, but they will generalize rapidly through cable modems, DSL telephone lines, satellites, or non-wired terrestrial communication, and their full potential for education has yet to be reached. One of the most critical issues related to e-learning technologies remains the knowledge management paradigm, which constitutes an important concern for many major organizations.

E-Learning Networked Environments and Architectures

Knowledge management incorporates and extends traditional document or data management in many ways. It embeds concepts such as intellectual capital, learning organization, business intelligence, process re-engineering, decision support, competency management, and so on. Knowledge management integrates the processing of higherlevel knowledge, beyond raw data or factual information. It underlines the importance of principles, models, theories, processes, and methods, and helps uncover 1.

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E-Learning Networked Environments: Concepts and Issues 3 the tacit knowledge of experts to make it available for learning, working, and decision-making processes. From a knowledge management standpoint, the main issues pertaining to e-learning networked environments include the design of knowledge scenarios that can be integrated into knowledge environments, the building of knowledge networks dedicated to supporting these environments, and the mechanisms enabling the retrieval of learning resources or useful knowledge. This introductory chapter characterizes the e-learning environments and analyzes these issues.

Section 1. From an object-oriented programming standpoint, learning resources can be understood as objects in an object-oriented model, having methods and properties. These properties are generally described using metadata, i. Due to various methods, the learning objects can become interactive or adaptive [26]. Even though the term knowledge object takes precedence as it refers to uses other than formal learning, the terms learning object and learning resource are used as synonyms in this chapter. Learning objects or resources can be distributed over different servers.

They can be of any size and type: text, audiovisual material, educational software, multimedia presentations, or simulations. They also carry information to be explicitly used by persons in order to acquire knowledge and competencies. They can be described and gathered in such a way that facilitates their storage, publication, and retrieval. Such an organization is called a learning object repository LOR. Such an environment can be used for education and training, engineering and design, and, commerce and entertainment.

When hardware, software, and communication tools, as well as the teaching, coaching, and assistance services offered to the users of the computer network are integrated together in a coherent way, they constitute an e-learning networked environment. Figure 1. In large networked environments, learning takes place under a variety of technical constraints. A typical e-learning networked environment. For this reason, among others, learner modeling remains active, considering only the information available and computing only as deeply as time and space constraints permit. Instructional planning must also be sensitive to these time and resource limitations.

One of the advantages of a LOR is that it allows any instructional designers or any person acting as an editor to track down interesting learning objects created in a learning context in order to reuse them or adapt them for use in another environment. For this purpose, interoperability and metadata protocols are needed. One of the main purposes of interoperable learning objects is that they can be aggregated and integrated into a knowledge management or learning environment.

Such an environment sometimes emerges from peer-to-peer interaction and can be designed by a team of instructional engineers by creating and implementing a delivery model that depicts interactions between users and the learning system components, activity descriptions, and learning objects [19,20]. The main challenge for the interoperability of learning objects consists of their 1.

E-Learning Networked Environments: Concepts and Issues 5 design rather than the platform interoperability issues that initially motivated their development. From a knowledge management standpoint, learning objects need to be encapsulated into abstract resources in order to provide designers with a scripting language to produce aggregations and launch resources in all different technical situations. Learning objects can embody both educational content and learning activities and the traditional approaches to labeling and transporting containers of digital content are being challenged by emerging abilities to express content, processes, and metadata as semantically rich ontologies [32].

This leads to the concept of semantic Web services. Learning objects can be active or adaptive. In fact, they generally consist of raw material that ideally can be used in different ways, for different purposes, and in different contexts. For these purposes, it is necessary for designers to be able to adapt original learning objects in order to reuse them properly in new contexts.

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This time-consuming task constitutes a serious bottleneck in the development of e-learning materials. In fact, making learning objects readily adaptable to various contexts, various learner capabilities, and various pedagogical needs would be a useful extension of their current capacities. For this reason, it would be impossible to ensure the consistency of any central registry.

Methods already developed in the areas of autonomous agents, multiagent systems, planning, 6 Samuel Pierre and Gilbert Paquette machine learning, and knowledge representation could be extended and adapted to solve these problems. Learning objects can also be of an advanced multimedia type including threedimensional 3D or virtual-reality components. One of the unique characteristics of a virtual-reality system is the head-mounted display worn by users.

These displays block out the entire external world and show the user a scene that is entirely under the control of the computer. Augmented reality AR is a growing area of virtual-reality research [27].

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An augmented-reality system generates a composite view for the user. It combines and projects an authentic scene to the user with a computer-generated virtual scene thereby enhancing the real scene with additional information. In all applications, the improved reality presented to users enhances their performance and perception of the world. The ultimate goal is to create a system so that the user cannot tell the difference between the real world and the virtually enhanced version. Advanced multimedia includes VR and AR simulations that are used to provide advanced computer-based instruction and training.

Another relevant concept pertains to a Virtualized RealityTM Environment VRE : a generalization of the essentially synthetic virtual environment concept. Simulations, such as virtual reality, undoubtedly create a very rich learning environment [8,9]. The creation of these objects requires advanced authoring tools, particularly when such objects must 1. Knowledge scenarios are basically networks of learning events curriculum, courses, units, activities with learning objects, material, and resources used or produced within the context of these events. All users have their own view of the learning scenario and the learning objects they need to use or produce according to their role.

Furthermore, each tool and document can accumulate data pertaining to its users. Process-based learning scenarios are the main focus of instructional engineering. A learning unit without an associated skill is analogous to a set of data without any process acting on it. Consider, for example, a training unit for electronic technicians. These learners must acquire knowledge pertaining to electronic devices. They must also be able to identify various kinds of electronic components and they need the competencies required to diagnose a defective electronic device.

The second goal corresponds to another generic skill, diagnosis, also applicable to any knowledge domain. Of course, a training unit in electronics will be very different if the course designer only wants learners to classify components, compared to a designer who wishes to train learners to diagnose malfunctions. A learning scenario for a unit should be based, whenever possible, on a generic process corresponding to a generic skill.

Then, the collaborative activities, as well as the information, production, and assistance resources, will be chosen accordingly. Building a learning scenario can be described as a three-step process. Building a knowledge scenario step 1. Typically, the learners search for information and consult writing methods and norms. Then, a plan of the document is sketched and a work plan to distribute tasks among learners is built. Finally, the sections are written.

The integration of these sections yields a preliminary text that will be revised and evaluated. In this example, these actors belong to a team of writers, composed of a leader and other learners. The tutor or trainer is also an actor and plays the role of an evaluation expert or a client who will validate the text at the end.

All of these actors are linked as ruling R agents to the activities in the scenario. In this example, a Web search engine and an annotation tool are used to search for input information and to consult writing methods and norms. Access to a human content expert can be provided to advise users about writing 1. Building a knowledge scenario step 2. Teleconferencing could be added to sketch the plan and distribute the writing assignments.

Finally, the tutor acting as the client annotates the text and sends an evaluation through Web email. Note also that this scenario is generic, based on a generic collaborative writing task and an information synthesis generic skill. From the scenario, the Web site can be designed and the resources selected and integrated into the interaction spaces that will constitute a knowledge environment for the learners or for other actors. Studying in a classroom for a certain period of time does not mean learners are isolated from the outside world.

Networked computers can provide access to Web sites and Internet multimedia presentations. Videoconferencing can also bring new expertise into the classroom. Distributed classrooms are quite similar to high-tech classrooms except for the fact that learners and trainers are physically located in two or more distant locations. Learning events use specialized and sometimes costly real-time videoconferencing systems.

Alternatively, desktop videoconferencing software can be used for realtime communication. Hypermedia self-training refers to the use of learning materials accessible through the Web or CD-ROMs to support an individualized learning approach to 1. It is organized and led by a trainer or a teacher, allowing for interaction with the trainer or among learners during teamwork and discussion groups [14,15]. Communities of practice put the main emphasis on professional tasks [28]. The learners are basically content experts who wish to extend their knowledge through asynchronous exchanges of information via forums, emails, or document transfers.

They progress through collaborative problem solving and shared project know-how. Contrary to the previous model, communities of practices are devoid of trainers acting as content experts or pedagogical coaches. Group leaders are provided; however, they possess less knowledge of the subject matter than the learners, although they are more knowledgeable when it comes to the methods used to support group interactions. Performance support systems integrate training even more closely with the actual work processes and tasks in an organization [11].

This model promotes just-in-time information to help users focus on real-life problems whether individually or in teams. Paquette [23,24] describes how an object-oriented model was designed to create a Virtual Learning Center built for such a purpose. This system integrates the best features of the four models presented above. The learner achieves knowledge acquisition and construction by managing a learning environment planned by another actor, the designer, in collaboration with other learner agents and with assistance from other actors.

Learners can also make information available to others as a result of their production activities, thus becoming an informer agent. At the time of delivery, all of these actors interact within their own computerbased environment. This environment gathers resources that enable the actors to play their roles within a course Web site. Table 1. The extended architecture designed to create knowledge environments is presented in Chapter 4.

Three-level architecture. Within the same program, course, or learning event, certain units could be based on autonomous training, others on a community of practice, and even others on some form of distributed or high-tech classroom. This conceptual architecture is based on three levels. At the bottom, learning material knowledge resources are selected, adapted, digitized, or constructed to support content delivery of a subject matter.

Then the material is integrated into a Web site that gives access to a network of activities, resources, and productions to be realized. It is at this second level that the pedagogical strategy embedded in a knowledge scenario will be implemented. For example, a business process simulation integrated into a management course could also be used to analyze learning material in a course offered to trainers. The learning scenarios implemented into the Web site determine how a learning tool such as this one will be used for learning in various situations or different application domains.

Finally, at the upper level, the designer adds one or more e-learning environments to the course Web site—one for each actor in the training delivery process. The system then displays a list of the VLC learning events they can access, along with the roles they are authorized to play. The resources are distributed over interaction spaces. As shown in Figure 1.

The previous 1. E-Learning Networked Environments: Concepts and Issues 15 example shows a hybrid delivery model that combines hypermedia self-training, on-line training, and community of practice activities. The resources were chosen for a typical learner from a description of the learning scenario, its activities and input resources, and the productions the learner must accomplish according to the assignments associated with the activities.

The designer would carry out similar analyses for the trainer and the other actors in order to plan out their environments. In this context, the same characteristics must be presented to all participants. A shared sense of presence refers to the fact that when they enter the shared place, each participant takes on a virtual persona, called an avatar, which includes a graphical representation, a body structure model like the presence of arms, legs, antennae, tentacles, joints, etc.

Communicating in a networked environment consists of using gestures, typed text, or voice in order to enable some interaction among the participants. According to a fundamental component of engineering or training systems, ideally all communication mechanisms must seem authentic within a virtual environment.

A networked environment essentially consists of four basic components that work together to provide the sense of immersion among users located at different sites: graphic engines and displays, communication and control devices, processing systems, and communication networks. Graphic engines and displays constitute a key component of the user interface in a networked environment. The display provides the user with a 3D window into the environment and the engine generates the images on display. For these purposes, a CAVE can be used as a more immersive graphical display.

This is a cube in which the participants stand in the middle in order to see images that are projected onto the walls in front, above, below, and on both sides of them. The control and communication devices are necessary to allow users to communicate with other participants in the networked or virtual environment. The communication network is needed to allow users to exchange information text, audio, and video communication among themselves.

Typically, knowledge networks are environments that can be used for learning and training purposes. Network capacity constitutes a limited resource in a networked environment. For this reason, the network designer must carefully determine how to assign this capacity in order to avoid congestion, which would result in a decrease of network quality of service. The designer must also take into account the network heterogeneity, which refers to the fact that different users may be connecting to the networked environment using different communication networks with different capacities.

This issue is particularly relevant in interactive learning or training applications where a lack of equality can lead to unrealistic training. Heterogeneity issues also arise with regard to the graphical display and computational and audio capabilities. To fully use the capacities of broadband networks in e-learning networked environments, content-based and context-based search and delivery methods for advanced multimedia learning objects are required [10].

MPEG-4 has been developed to provide solutions for the new multimedia applications through characteristics like composition of presentation of structured and related objects, streaming, error resilience, powerful compression, and synchronization. The MPEG-4 streams are decoded in a way that allows object separation and reconstitution, making it possible for users to interact with the objects in the scene. Another issue that must be taken into account by the network designer pertains to the distributed interactions.

To be effective, the networked environment must provide users with the impression that the entire environment is located on their local machine and that their actions have an immediate impact on the environment. Other design issues, like real-time system design and failure management, are related to the capability of the networked environment to perform many tasks concurrently, in a reasonable time frame, while ensuring that it remains operational 1.

Scalability is measured by the number of entities that may be processed simultaneously by the environment. It can also be a measure of the number of hosts that may be simultaneously connected to the environment. It depends on a variety of factors, including network capacity, processor capabilities, rendering speeds, the speed, and the throughput of shared servers.

As a result, there is an impact on the software design, the choice of implementation language, and the set of supported execution platforms. The complexity of deployment issues increases if the networked environment must be executed within Web browsers over the Internet. It is used by learners to carry out tasks, solve problems or manage projects, by trainers looking for resources to facilitate learning, and by designers seeking resources to build knowledge environments.

The increased need to reuse learning objects or knowledge resources and the increasing necessity to integrate e-learning systems have led to a vast movement toward international standards for learning objects LOs. Actors operate scenarios composed of operations or activities where knowledge resources LOs are used or produced. Knowledge referentials metadata or ontologies describe the information owned or processed by actors, processed through operations, or contained in LOs: the properties of the knowledge resource.

Four corresponding managers store and retrieve information in a database, construct information structures, and present information to users. High-level architecture for knowledge environments. The two upper components, the LO aggregator and the LO launcher, operate knowledge resources LOs that were previously retrieved from one or more learning object repositories located somewhere on the Web.

View E Learning Networked Environments And Architectures: A Knowledge Processing Perspective 2006

Main components of a knowledge resource manager. It can move a metadata record from one folder to another, copy an alias onto another folder, delete a record or a folder, and duplicate a record to speed up the meta-referencing of a similar LO. Rights include viewing, adding, modifying, deleting, and granting rights to other users. It is integrated into the LO repository. These messages can also be stored in the metadata repository database. Subclasses are based on whether the actor provides technological, informational, organizational, student support, public relations, or training location support in a classroom, a laboratory, a virtual library, or an external location.

A possible solution involves distinguishing metadata attributes by taking into account the LO granularity. Metadata records in LO repositories should make some semantic description available to computer search agents. Another important international problem, especially prominent in Canada and Europe, concerns bilingual and multilingual metadata editing. Due to the global 1. E-Learning Networked Environments: Concepts and Issues 21 distribution of LOs over the Internet, it is indispensable to provide translation possibilities by providing multilingual equivalents for all vocabulary-based metadata.

There should be an effective control of the indexing language, covering selected concepts and interlanguage equivalency among descriptors.

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However, standards have yet to be made readily available, and further collaboration is needed between groups and developers. The main challenge for LO interoperability lies more in the advances of instructional engineering [18] than in the metadata standardization initiatives that actually triggered their initial development.

It is believed that instructional engineering is the key to sound and practical solutions to LO aggregation and interoperability. After exposing the problematic of building knowledge scenarios and knowledge environments, the principles, methods, and issues related to the design of knowledge networks were summarized.

Finally, the problem pertaining to retrieving resources and knowledge in networked environments was addressed. Knowledge plays a central role in e-learning networked environments. It uses two important processes: knowledge extraction and knowledge assimilation. Knowledge assimilation by those who belong to the organization is the reverse process: transforming organizational information and knowledge into new competencies to be internalized by individual staff members through learning.

This is where knowledge engineering meets instructional engineering and learning object production and management. Knowledge models are produced through knowledge engineering and are used as inputs to knowledge and competency acquisition by persons involved in formal or informal training activities. Knowledge modeling also helps represent use cases of a computerized learning or knowledge management system by describing the actors, the operations they perform, and the resources or learning objects they use or produce while processing knowledge of a domain.

Conversely, actors involved in these use cases help test, validate, or identify improvements and extensions to the knowledge model or the ontology of a domain. In the process of designing knowledge networks, considerable effort is spent on critical tasks including the modeling, aggregation, and coordination of learning objects. The resources can be compounded and integrated into the repository of the application. Since current technologies do not support the automation of this task, the need for computer-based systems that support learning object adaptation and repurposing constitutes a real challenge [26].

To make learning objects active and adaptive, one approach consists of imbuing them with some degree of autonomy, i. To fully exploit the potential of images as a source of information, one would have to examine images based on their lower level features and look for hidden characteristics that would explain the behavior of domain level experts as they come into contact with these images. In this context, research on shape-based retrieval [6], image data mining and content based retrieval [7] must be conducted to adapt these technologies to learning object repositories.

References 1. Aukstakalnis, S. Berkeley, CA: Peachpit Press. Berners-Lee, T. Bimbo, A. San Francisco: Morgan Kaufmann. Davenport, T. Duval, E. Interactive learning environments. Special issue. Metadata 9 3 : — El Badawy, O. International Journal of Image and Graphics, 2 3 : — El Saddik, A.

Berlin: Springer-Verlag. Georganas, N. Gery G. Girard J. In: S. Lajoie and M. Vivet eds. IOS Press. Grass, J. New York: Macmillan. Wang, M. Individual Differences and School Learning Environments. Review of Research in Education, 11, — Glaser, R. Adaptive education: Individual, Diversity and Learning. New York: Holt. Carchiolo, V. Courses Personalization in an e- Learning Environment. July , Licchelli, O. LNAI Vol. Yoo, J. ACM Press. March , Houston, USA, pp.

Grieser, G. Consistency Queries in Information Extraction. Lecture Notes in Artificial Intelligence, Vol.

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Hwang, G. Mullier, D. In: Kommers, P. Tang, T. International Journal on e-Learning, 4 1 , Teng, C. Hammouda, K. Data Mining in e-Learning. In: Pierre, S.

E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective
E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective
E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective
E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective
E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective
E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective
E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective
E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective E-Learning Networked Environments and Architectures: A Knowledge Processing Perspective

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