Structure of a knowledge object.

Contexts in source publication

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... conceptual strategy for the building of the UOL is depicted in Figure 1 by six Use Cases: Describe General Information for the UOL, ...

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... first step to get the learning scenario running is, then, the instantiation step. That is, one needs to map actual users to the roles of the scenario, thus creating one scenario instance. Users have to be manually added to the different learning scenario roles, which, again, can be quite a hassle, as this has to be done within a command line interface. Once all needed users have been added, the CopperCore engine allows users to run the learning scenario. Fig. 1 shows the various activities proposed at the same moment to two different actors having different roles within the learning ...

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... avoid this, we are proposing the introduction of a number of features to enhance current CDMS. Such features range from social network analysis and visualization tools that facilitate communication and exchange, to more innovative approaches such as a d v a n c e d s i m u l a t i o n s to scaffold networking and knowledge exchange behavior, and to the use of stimulus agents acting on user models to propose networking choices and to highlight cooperative opportunities. Additionally, policies of self- organization (terms of use, standards and quality, reward system, membership/ role) will be tested to guide how users learn, share and create knowledge and support each other. Figure 1 shows the connections between the proposed methods/tools and related design principles. ...

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... this stage, the most arduous task is that of the learning designer first having to write down the complete learning scenario, intertwined with all of the variables and effects of the various conditions (i.e. availability of the various activities). Writing the IMS Learning Design itself becomes possible only once this work has been accomplished. It is, thus, very difficult to make even small modifications afterwards, such as adding or removing an activity. Besides, one thing was found to be missing from the IMS-LD specification: the ability to form groups of learners. Grouping learners in order to facilitate active learning, (e.g. problem-based or project-based) is, indeed a common practice, and the impossibility to describe such interactions in an easy way with the specification is, in one sense, a shortcoming which should be tackled. Fig. 1. Different activities and environments are presented to actors of different roles. On the left side are shown the activities and corresponding environments which are presented, at some point of the scenario, to a tutor, allowing him or her to see, among other things, the vari- ous students' choices made so far. On the right side of the figure are shown the activities avail- able at the same time to a ...

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... "8 Learning events model" introduces standardization of basic teaching and learning activities. It is composed of 8 documented teaching/learning events, i.e. ways of learning. This high level tool-kit provides guiding principle for taking decisions about how to divide the continuum of pedagogic practice into pedagogically meaningful parts. The 8 events are basic activity types (see figure 1) which can be applied in any context wherein activity structures' analysis and building are at stake. The 8LEM is a learning/teaching model, thus tackling both the learner and the teacher at the same time. It connects in a systematic way both the student's demand and the teacher's supply, and their interrelations (see figure 2). Learner and teacher's actions are complementary and interdependent, just as the two faces of a bivalve shell (such as a mussel or an oyster): observation/modeling, reception/transmission, exploration/documentation, self-reflection/co- reflection, debate/animation, creation/, creation/confortation, experimentation/reactivity, exercising/guidance. Providing an operational entry to learning, the model focuses mainly on cognitive aspects when considering the learner. (As such, it, at first glance, reflects the "acquisition metaphor of learning". But, when considered as a teacher's professional development, the model, as a artifact/process of pedagogical inquiry for practitioners, seems to have some features common with the "knowledge creation metaphor" ...

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... direct consequence of such a definition is that in other to give support to specific searches some semantic has to be associated to each different kind of knowledge object: basic knowledge resources (KR), units of learning (UoL), learning activities (LA), learning paths (LP), etc. This can be achieved by allowing at each level users of the KRMS Component to provide proper metadata they consider as relevant (see Figure 1). Internally the KRMS Component will be based on a service- oriented architecture or framework, conceived and designed in order to efficiently support the requested features. Some basic services in this framework have been already identified and need further specification ...

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... the list of classification descriptors on figure 1, we see that the last entry shows metadata from another classification scheme on cognitive skills and strategies, also extracted from our work on MISA [7,10] and integrated in section 9 of the LOM. For the example, this metadata indicates that the learners will use and develop synthesis skills. We have discussed elsewhere why such generic skills and strategies are fundamental to structure learning design strategies. Other LOM entries are useful to provide some semantic structure to the set of LD products in a repository. We use the 1.8 section of the LOM to specify one of four aggregation ...

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... facilitate search in learning object repositories containing learning design products we needed to classify the LDs according to their main properties. Figure 1 shows such a classification embedded in the PALOMA learning object manager. The left part presents a list of available repositories, including the IDLD repository; the center part shows a list of designs grouped in one repository; the right part is the section to creating, modify and view a standard IEEE-LOM record for the selected object. Here, this object is a learning design for a collaborative LD pattern entitled "FORUM ...

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... service-oriented architecture of the CORE is illustrated in Figure 1. The user accesses the virtual collaborative environment through a portal framework. Portlets within this framework provide for authentication, authorization, management of the user profile data, and workflow management of the experimental or research protocols and processes. From the portal framework, the user's needs for collaborative discussion, paper editing, data management and analysis, and GRID applications are provided by appropriate generic Web services. provides the basis for integrated computer support across both the research and educational domains, because these activities are intrinsically coupled as a part of the requirements of the orthopaedic surgeon's Continuing Professional ...

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... «Interface» ICopperCoreAdapter The Dispatchers most important role is the propagation of events through all defined adapters. It is the responsibility of the adapters to listen for these events. Vice versa, it is the responsibility of each adapter to trigger the Dispatcher when an event occurs that has potential cross service repercussions. The Dispatcher is also responsible for returning an adapter of the requested type to the client, thereby acting as an adapter factory. This adapter factory is necessary because the types and implementation of the adapters are not known in advance, and may vary even during deployment by simply adding or replacing adapters. Adapters can come in two flavors depending on the way the client wishes to access the adapter. This can be done either via native Java calls or via SOAP web services. For a native Java call the dispatcher returns an instance of a Java class. For a web services it returns a URL to the WSDL of the requested adapter. All adapters are declared in the CCSI service definition file. This file contains information about the base service type, the implementing Java class and WSDL URL. Furthermore Fig. 1 depicts two adapter types; an adapter for the LD service and an adapter for the QTI service. Note that there could have been additional adapters for other services as well. The common interfaces for these service types are defined by the interfaces ILDAdapter and IQTIAdapter. Each adapter must implement the interface for its base type. The figure also shows two abstract classes LDAdapter and QTIAdapter that are abstract classes implementing the hooks for the Dispatcher. They are the extension points for any adapter acting as façade for either an LD or QTI service ...

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... address this problem we have extended PlanetDR with a federation mode, using the federation architecture shown in figure 1. This mode which supports plug & play decentralized management of PlanetDR compatible servers, thus guaranteeing worldwide scalability. New PlanetDR active instances in the network are automatically detected and inserted into each node's local list of available servers. Each PlanetDR node listens to the different events which occur (insert / remove), and this allows each instance to maintain an updated list of available servers. Each server can join or leave the P2P federation of educational servers, and get a listing of all of them available in the network. Thus the federated mode maintains "awareness" of both the identity of the nodes which make up the network, and also of the content which they hold, so that directed searches can be sent to any of these ...

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... Act 2, 4 and 6 sub-models, we have extracted two recurrent activity structures called "TEXT PRODUCTION pattern" and "SOFTWARE PRODUCTION pattern". Finally, act 7 yields the "FORUM-SYNTHESIS pattern" whose metadata have been described in figure 1. In MOT+LD, these sub-models are simply copied to a new LD structure and stored in the repository using PALOMA. Afterwards, we search and retrieve these "atomic patterns" to group them in different plays and ...

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... ontology is usually composed of: classes of objects, a vocabulary of terms (instances), and various relations between classes or terms and classes. A critical step in ontology development is the selection of the most appropriate language for ontology description, and tool for performing the basic ontology operations. Ontology languages can be divided in two major groups: traditional and web-based languages [1,3]. Some traditional languages are Flogic, OCML and Ontolingua [17]. Other ontology languages like XOL [7], OIL [6], SHOE [8] are defined as web-based languages. On the other hand, we have languages, used mainly to physically code some ontology formalism, which are named representation languages. The most widespread such languages are XML [4], UML, RDF. Other languages like PIF and KIF [5] are used mainly for conversion between different ontology languages, supporting the process of interchange between different ontology formalisms. We will extend this classification with new type of languages: rule-based, like RuleML [2] and WRL [13]. Of course, some languages can be included in more than one group. Some of the traditional languages have been extended with additional, flexible and interactively updated information, making them very close to Web-based languages, like OWL [15]. Some other languages combine characteristics of web-based and rule-based languages, as SWRL [14]. The extended classification of all types of ontology description languages, as explained above, is shown on Fig.1 ...