e-Learning process management and the e-learning performance: Results of a European empirical study

The aim of this paper was to design and assess a comprehensive model for managing the e-learning process and to define the relationship between systematic implementation of the model, outcomes of certain e-learning aspects and subject of e-learning. The validation of the model was performed by using two questionnaires sent via e-mail to teachers and field experts from the chosen sample of 14 European schools participating in an EU-funded project. Research results imply the existence of a clear link between planning and controlling of the e-learning process and its learning outcomes. On the other hand, no empirical relationship between the e-learning outcomes and the subject of learning has been established. It is believed that the model and its practical implications can be used by institutions engaged in e-learning, or as a process model for introducing e-learning related activities.     

The design of instructional multimedia in e-Learning: A Media Richness Theory-based approach

The rapid development of computer and Internet technologies has made e-Learning become an important learning method. There has been a considerable increase in the needs for multimedia instructional material in e-Learning recently as such content has been shown to attract a learner’s attention and interests. The multimedia content alone, however, does not necessarily result in significant positive learning performance and satisfaction. Moreover, it is expensive to design and develop multimedia instructional material. There is a lack of extant research to address the critical issue of how to develop effective multimedia instructional content that leads to desirable learning performance and satisfaction. The objective of our paper is to propose and empirically test a model that examines the impact of the fitness of instructional content and media on a learner’s performance and satisfaction.     

Digital libraries in knowledge management: an e-learning case study

Knowledge and libraries – this conceptual symbiosis is as old as the idea of libraries itself: libraries collect artifacts of explicated knowledge and make them available for building up new knowledge in all areas of everyday life. Learning and qualification management support are further essential links in the knowledge supply chain, which starts at the expert knowledge of an author and ends at the targeted enhancement of another persons individual knowledge. Digital libraries and e-learning systems are thus important enabling technologies for the knowledge supply chain in the digital age.The e-Qualification project presented in this paper combines digital library, e-learning, and authoring support into an adaptable qualification management framework that provides integrated support and mediation for the various stakeholders involved in the qualification management process.     

Knowledge work support by semantic task management

This paper describes the particular requirements of knowledge work in an industrial setting and its support by semantic technologies. This setting is characterized by specific demands with respect to information handling, communication and work coordination. It is shown how semantic technologies can meet these demands. Specifically, the Social Semantic Desktop (SSD) is discussed that covers requirements for individual structuring and proceeding as well as organizational needs. It is discussed which aspects come to the fore in an industrial setting and require particular consideration. Here we find a focus on communication and on work coordination. The latter is addressed by semantic task management and allows for new approaches towards experience management in industry. In this respect the SSD opens up completely new opportunities. It is shown how such a framework has been realized in the European Integrated Project Nepomuk.     

Semantic annotation for knowledge management: Requirements and a survey of the state of the art

While much of a company's knowledge can be found in text repositories, current content management systems have limited capabilities for structuring and interpreting documents. In the emerging Semantic Web, search, interpretation and aggregation can be addressed by ontology-based semantic mark-up. In this paper, we examine semantic annotation, identify a number of requirements, and review the current generation of semantic annotation systems. This analysis shows that, while there is still some way to go before semantic annotation tools will be able to address fully all the knowledge management needs, research in the area is active and making good progress.     

Security as a contributor to knowledge management success

Security is an important topic, but is it important for Knowledge Management (KM)? To date, little mainstream KM research is coming through with a security focus. This paper asks why, and proposes that security be integrated into KM success models. The Jennex and Olfman (International Journal of Knowledge Management 2(3):51–68, 2006) KM success model is used to illustrate how security, specifically risk management, and the National Security Telecommunications and Information System Security Committee (NSTISSC) security model can be applied to KM management support and governance and KM Strategy. Finally, two case studies are provided that illustrate the application of risk management through governance to KM.     

Towards an evaluation framework for knowledge management systems

In this paper we develop an evaluation framework for Knowledge Management Systems (KMS). The framework builds on the theoretical foundations underlying organizational Knowledge Management (KM) to identify key KM activities and the KMS capabilities required to support each activity. These capabilities are then used to form a benchmark for evaluating KMS. Organizations selecting KMS can use the framework to identify gaps and overlaps in the extent to which the capabilities provided and utilized by their current KMS portfolio meet the KM needs of the organization. Other applications of the framework are also discussed.

A knowledge engineering approach to knowledge management

Knowledge management facilitates the capture, storage, and dissemination of knowledge using information technology. Methods for managing knowledge have become an important issue in the past few decades, and the KM community has developed a wide range of technologies and applications for both academic research and practical applications. In this paper, we propose a knowledge engineering approach (KMKE) to knowledge management. First, a knowledge modeling approach is used to organize and express various types of knowledge in a unified knowledge representation. Second, a verification mechanism is used to verify knowledge models based on the formal semantics of the knowledge representation. Third, knowledge models are classified and stored in a hierarchical ontology system. Fourth, a knowledge query language is designed to enhance the dissemination of knowledge. Finally, a knowledge update process is applied to modify the knowledge storage with respect to users’ needs. A knowledge management system for computer repair is used as an illustrative example.     

General framework for distributed knowledge management in mechatronic systems

This paper is concerned with the application of knowledge management on the mechatronic system. First, data, information and knowledge terms have been explained according to their disparities and similarities. Then, knowledge management has been described in general. The Internet—based CNC machining center has been considered and its knowledge management model has been prepared. The model prepared has been analyzed for machining performance of the manufacturing system.     

Semantic representation of multimedia content: Knowledge representation and semantic indexing

In this paper we present a framework for unified, personalized access to heterogeneous multimedia content in distributed repositories. Focusing on semantic analysis of multimedia documents, metadata, user queries and user profiles, it contributes to the bridging of the gap between the semantic nature of user queries and raw multimedia documents. The proposed approach utilizes as input visual content analysis results, as well as analyzes and exploits associated textual annotation, in order to extract the underlying semantics, construct a semantic index and classify documents to topics, based on a unified knowledge and semantics representation model. It may then accept user queries, and, carrying out semantic interpretation and expansion, retrieve documents from the index and rank them according to user preferences, similarly to text retrieval. All processes are based on a novel semantic processing methodology, employing fuzzy algebra and principles of taxonomic knowledge representation. The first part of this work presented in this paper deals with data and knowledge models, manipulation of multimedia content annotations and semantic indexing, while the second part will continue on the use of the extracted semantic information for personalized retrieval.

Capturing and reusing knowledge in engineering change management: A case of automobile development

The development of complex products, such as automobiles, involves engineering changes that frequently require redesigning or altering the products. Although it has been found that efficient management of knowledge and collaboration in engineering changes is crucial for the success of new product development, extant systems for engineering changes focus mainly on storing documents related to the engineering changes or simply automating the approval processes, while the knowledge that is generated from collaboration and decision-making processes may not be captured and managed easily. This consequently limits the use of the systems by the participants in engineering change processes. This paper describes a model for knowledge management and collaboration in engineering change processes, and based on the model, builds a prototype system that demonstrates the model’s strengths. We studied a major Korean automobile company to analyze the automobile industry’s unique requirements regarding engineering changes. We also developed domain ontologies from the case to facilitate knowledge sharing in the design process. For achieving efficient retrieval and reuse of past engineering changes, we used a case-based reasoning (CBR) with a concept-based similarity measure.

School knowledge management framework and strategies: The new perspective on teacher professional development

During the epoch of knowledge-based economy and knowledge management, teachers must learn in order to improve professional development. The paper discusses on the problems of teacher professional development in China, and analyze on the relationship among teacher learning, teacher professional development and school knowledge management. From the perspective of schools, this study develops school knowledge management framework to facilitate teacher learning and improve teacher professional development, in the basis of this framework, schools’ knowledge management strategies are presented, and provide references for administrators of schools. The result reveals the knowledge management strategies to improve teacher professional development, including school organizational reforger and knowledge leaders, constructing learning school and organization learning culture, establishing teacher knowledge management system of teacher professional development, encouraging team learning, teaching cooperation and knowledge sharing, establishing performance assessment mechanism of knowledge applications and development.     

Using a simulation model for knowledge elicitation and knowledge management

The work reported in this paper is part of a project simulating maintenance operations in an automotive engine production facility. The decisions made by the people in charge of these operations form a crucial element of this simulation. Eliciting this knowledge is problematic. One approach is to use the simulation model as part of the knowledge elicitation process.This paper reports on the experience so far with using a simulation model to support knowledge management in this way. Issues are discussed regarding the data available, the use of the model, and the elicitation process itself.     

Exploring barriers to knowledge flow at different knowledge management maturity stages

A significant amount of work has been done to better understand the barriers to knowledge flow and develop models of KM maturity; this was intended to help in assessing the progress of KM initiatives in the firm. However, to date there has been no comprehensive research that considers both these issues at the same time, and thus it is still necessary to explore the evolution of barriers to knowledge flow when the level of KM maturity is changing. We reviewed the progress of KM initiatives in recent years, categorized the barriers to knowledge flow according to the cultural historical activity theory (CHAT), and used one of the existing models of KM maturity (the Knowledge Navigator Model—KNM), to address gaps in the current literature. As part of our exploratory study, a longitudinal survey, involving constant observation, development and use of questionnaires and qualitative interviews with managers of seven firms were conducted. We selected the firms so they covered a wide range of KM maturity levels; triangulation was adopted to enhance the quality of the process. The major findings indicated that: (1) barriers to knowledge flow were inherently different at different KM maturity levels; and (2) various changes in the barriers to knowledge flow were associated with the maturity of the KM.     

Reflective knowledge models to support an advanced HCI for decision management

In the previous years, the evolution of the telematics technology has introduced a new scenario of human–computer operation where the achievement of an adequate level of user–system interaction has become a key aspect. This issue is specially relevant in real-time management scenarios where the system is intended to provide an intelligent support to human operators in the decision-making task. This paper proposes the use of advanced knowledge-based models to support human–computer interaction in the context of real-time decision for management problems. The approach is mainly based on endowing intelligent systems with an introspection capability that makes possible an adaptive performance to the characteristics of the interaction. This capability is supported by a reflective architecture where a metalevel layer dynamically configures reasoning strategies to generate the required answers by looking into a structured collection of problem-solving components. The approach was developed and applied within the FLUIDS project, an European Commission Telematics Applications research project. The proposal is illustrated with an example in the domain of real-time private traffic management in the city of Turin.     

A study on the critical success factors for corporations embarking on knowledge community-based e-learning

Corporations have felt the pressure for fast-paced innovations and knowledge transfer as major driving forces in raising their sustainable competitive advantage and organizational total productivity. Thus, the development of the knowledge community through e-learning is an important strategy in implementing knowledge management policy. This paper illustrates an empirical study with which to conduct qualitative research of learning organization. From the case company’s real progress and practical experience, some core principles were extracted from four managerial aspects, such as: strategy, technology, process, and personnel. These aspects were analyzed in order to understand the value chain framework and the major concerns of knowledge community development. Further, the main benefits are addressed and certain critical factors are proposed and shown in this paper to ensure the success of corporations embarking on knowledge community-based e-learning.     

Architecture for knowledge discovery and knowledge management

In this paper, we propose I-MIN model for knowledge discovery and knowledge management in evolving databases. The model splits the KDD process into three phases. The schema designed during the first phase, abstracts the generic mining requirements of the KDD process and provides a mapping between the generic KDD process and (user) specific KDD subprocesses. The generic process is executed periodically during the second phase and windows of condensed knowledge called knowledge concentrates are created. During the third phase, which corresponds to actual mining by the end users, specific KDD subprocesses are invoked to mine knowledge concentrates. The model provides a set of mining operators for the development of mining applications to discover and renew, preserve and reuse, and share knowledge for effective knowledge management. These operators can be invoked by either using a declarative query language or by writing applications.The architectural proposal emulates a DBMS like environment for the managers, administrators and end users in the organization. Knowledge management functions, like sharing and reuse of the discovered knowledge among the users and periodic updating of the discovered knowledge are supported. Complete documentation and control of all the KDD endeavors in an organization are facilitated by the I-MIN model. This helps in structuring and streamlining the KDD operations in an organization.     

Understanding the effect of knowledge management strategies on knowledge management performance: A contingency perspective

The universalistic perspective research on employing a unidimensional knowledge management (KM) strategy has yielded conflicting findings and recommendations in different contexts. This study proposes a contingency model for investigating the effects of KM strategies on KM performance to resolve these contradictions. Drawing on the knowledge-based view (KBV) of the firm, which identifies knowledge type and origin as two key KM dimensions, this study first defines four KM strategies: external codification, internal codification, external personalization, and internal personalization. A multiple contingency model of KM strategy is then developed based on a technology–organization–environment framework. This study proposes that the effectiveness of each KM strategy depends on both external and internal contextual conditions, namely, environmental knowledge intensity and organizational information systems (IS) maturity. To test and validate the contingency model, we analyze data from 141 firms to explain the effects of KM strategies on KM performance. Our results reveal three KM strategies, not including the internal personalization strategy, which have a significant association with KM performance in their hypothesized contexts. This study expands KM strategy research by theoretically developing an advanced contingency model aligned with external and internal contexts and by providing valuable practical suggestions to managers for selecting a KM strategy based on multiple contingencies related to the external and internal conditions of a firm.