An Ontology-Based Approach in Personalization of the e-Learning System

The emergence of the Semantic Web and its technologies have opened the way, over the last decade, for the development of ontologies and systems that use ontologies in various fields, including e-learning. This article presents elements that underpin the development of an e-learning system in the area of the Human Resource Management in the field of ontology health, respectively basic notions about the semantic Web, ontologies, personalization in e-learning. The article presents a personalized e-learning environment that uses new technologies, semantic Web and ontologies to improve the human resource management training process, being addressed to hospital managers. The necessity of this approach is given by the training requirements in the field of human resources management for the specialists from the medical system in Romania, as well as by the need to solve current limitations of the e-learning systems. The implementation of the concept of personalization of learning in the e-learning system is performed starting from the student model built to determine the level of knowledge and the objectives of training. Modeling the student profile using ontologies has demonstrated the possibility of re-using the models, the detailed and complete representation of the student’s knowledge as well as the reasoning process. This learning program aims to increase the performance, skills and competence of health managers, by deepening knowledge in the field of public health, healthcare management, and human resource management

A knowledge-based framework to facilitate E-training implementation

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de ComputadoresNowadays, there is an evident increase of the custom-made products or solutions demands with the objective to better fits to customer needs and profiles. Aligned with this, research in e-learning domain is focused in developing systems able to dynamically readjust their contents to respond to learners’ profiles demands. On the other hand, there is also an increase of e-learning developers which even not being from pedagogical curricula, as research engineers, needs to prepare e-learning programmes about their prototypes or products developed. This thesis presents a knowledge-based framework with the purpose to support the creation of e-learning materials, which would be easily adapted for an effective generation of custom-made e-learning courses or programmes. It embraces solutions for knowledge management, namely extraction from text & formalization and methodologies for collaborative e-learning courses development, where main objective is to enable multiple organizations to actively participate on its production. This also pursues the challenge of promoting the development of competencies, which would result from an efficient knowledge-transfer from research to industry

Knowledge management framework based on brain models and human physiology

The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications

Knowledge representation in support of adaptable elearning services for all

In general, formal knowledge representation enables computers characterize relevant information related to determined process elements and actors in a domain for specific advanced reasoning. In the eLearning domain, several mechanisms of knowledge representation have been proposed, such as standards, technological specifications and ontologies. Both ontologies and specifications play an important role in eLearning systems because they offer an explicit conceptualisation allowing key concepts and terms relevant to a given domain to be identified and defined in a structure able to facilitate reasoning, use and exchange knowledge between the components and users of its systems and by that, to contribute to the increase of its computational intelligence. In this paper we introduce the importance of the knowledge representation mechanisms to support the generation of adaptable eLearning services for allAuthors would like to thank to: European Commission for its support through the funding of the ALTERNATIVA Project (DCI-ALA/19.09.01/10/21526/245-575/ALFA III(2010)88); the Spanish Science and Education Ministry for the financial support of ARreLS project: Augmented Reality in Adaptive Learning Management Systems for All (TIN2011-23930) and to all involved in the activities supporting the development of the CoSpaces Training Syste

Semantic adaptability for the systems interoperability

In the current global and competitive business context, it is essential that enterprises adapt their knowledge resources in order to smoothly interact and collaborate with others. However, due to the existent multiculturalism of people and enterprises, there are different representation views of business processes or products, even inside a same domain. Consequently, one of the main problems found in the interoperability between enterprise systems and applications is related to semantics. The integration and sharing of enterprises knowledge to build a common lexicon, plays an important role to the semantic adaptability of the information systems. The author proposes a framework to support the development of systems to manage dynamic semantic adaptability resolution. It allows different organisations to participate in a common knowledge base building, letting at the same time maintain their own views of the domain, without compromising the integration between them. Thus, systems are able to be aware of new knowledge, and have the capacity to learn from it and to manage its semantic interoperability in a dynamic and adaptable way. The author endorses the vision that in the near future, the semantic adaptability skills of the enterprise systems will be the booster to enterprises collaboration and the appearance of new business opportunities

A quality assessment framework for knowledge management software

CONTEXT: Knowledge is a strategic asset to any organisation due to its usefulness in supportinginnovation, performance improvement and competitive advantage. In order to gain the maximum benefit from knowledge, the effective management of various forms of knowledge is increasingly viewed as vital. A Knowledge Management System (KMS) is a class of Information System (IS) that manages organisational knowledge, and KMS software (KMSS) is a KMS component that can be used as a platform for managing various forms of knowledge. The evaluation of the effectiveness or quality of KMS software is challenging, and no systematic evidence exists on the quality evaluation of knowledge management software which considers the various aspects of Knowledge Management (KM) to ensure the effectiveness of a KMS.AIM: The overall aim is to formalise a quality assessment framework for knowledge management software (KMSS).METHOD: In order to achieve the aim, the research was planned and carried out in the stages identified in the software engineering research methods literature. The need for this research was identified through a mapping study of prior KMS research. The data collected through a Systematic Literature Review (SLR) and the evaluation of a KMSS prototype using a sample of 58 regular usersof knowledge management software were used as the main sources of data for the formalisation of the quality assessment framework. A test bed for empirical data collection was designed and implemented based on key principles of learning. A formalised quality assessment framework was applied to select knowledge management software and was evaluated for effectiveness. RESULTS: The final outcome of this research is a quality assessment framework consisting of 41 quality attributes categorised under content quality, platform quality and user satisfaction. A Quality Index was formulated by integrating these three categories of quality attributes to evaluate the quality of knowledge management software.CONCLUSION: This research generates novel contributions by presenting a framework for the quality assessment of knowledge management software, never previously available in the research. This framework is a valuable resource for any organisation or individual in selecting the most suitable knowledge management software by considering the quality attributes of the software