A conceptual framework for developing explorative e-learning strategy using ontology-based knowledge management

This paper presents a conceptual framework for developing explorative e-learning strategy using ontology-based knowledge management. It conducts a comprehensive analysis of the applicability of ontologies in management of knowledge, with a particular reference to the development of explorative e-learning environments for enhancing an efficient use and reuse of available information and knowledge in e-learning, leading to a better understanding of the main issues for developing effective explorative e-learning strategies in an e-learning environment

Evaluating Intertwined Critical Success Factors for Sustainable E-learning

Successfully leveraging knowledge transfer in distributed e-learning requires effective combination of pedagogies, technologies, and efficient management of learning resources. As a result, identifying and evaluating the critical success factors within each of these facets is vital for the success of e-learning. This paper explores the critical success factors intertwined within the learning ecosystem namely pedagogy, technology and management of learning resources in a higher education e-learning environment. Adopting a hybrid approach consisting of a systematic literature review and interviews with experts in e-learning, this paper shows that there is a discrepancy between theory and practice in e-learning in regard to the application of pedagogies, use of technology, and management of reusable learning objects. This implies that there is a need for tackling various issues regarding the adoption of appropriate e-learning strategies, knowledge sharing, quality, granularity and reusability of learning object for sustainable e-learning

Context-based multimedia semantics modelling and representation

The evolution of the World Wide Web, increase in processing power, and more network bandwidth have contributed to the proliferation of digital multimedia data. Since multimedia data has become a critical resource in many organisations, there is an increasing need to gain efficient access to data, in order to share, extract knowledge, and ultimately use the knowledge to inform business decisions. Existing methods for multimedia semantic understanding are limited to the computable low-level features; which raises the question of how to identify and represent the high-level semantic knowledge in multimedia resources.In order to bridge the semantic gap between multimedia low-level features and high-level human perception, this thesis seeks to identify the possible contextual dimensions in multimedia resources to help in semantic understanding and organisation. This thesis investigates the use of contextual knowledge to organise and represent the semantics of multimedia data aimed at efficient and effective multimedia content-based semantic retrieval.A mixed methods research approach incorporating both Design Science Research and Formal Methods for investigation and evaluation was adopted. A critical review of current approaches for multimedia semantic retrieval was undertaken and various shortcomings identified. The objectives for a solution were defined which led to the design, development, and formalisation of a context-based model for multimedia semantic understanding and organisation. The model relies on the identification of different contextual dimensions in multimedia resources to aggregate meaning and facilitate semantic representation, knowledge sharing and reuse. A prototype system for multimedia annotation, CONMAN was built to demonstrate aspects of the model and validate the research hypothesis, H₁.Towards providing richer and clearer semantic representation of multimedia content, the original contributions of this thesis to Information Science include: (a) a novel framework and formalised model for organising and representing the semantics of heterogeneous visual data; and (b) a novel S-Space model that is aimed at visual information semantic organisation and discovery, and forms the foundations for automatic video semantic understanding

The impact of knowledge governance mechanisms on supply chain performance: Empirical evidence from the agri-food industry

The agri-food supply chain (AFSC) is an extremely complex structure that comprises a series of events from farm-to-fork. Additionally, there is a wide range of information and material flows required to be managed, which are seen as the knowledge flow in the AFSCs. It is expected that the use of knowledge governance mechanisms (KGMs) will help in enhancing AFSC performance. To examine the impact of KGMs on AFSC performance, a mixed methods research design was applied. First, semi-structured interviews were conducted to collect data. Then, themes were generated through thematic analysis. Afterwards, relationships between KGMs and AFSC performance were built by using total interpretive structural modelling (TISM). Finally, questionnaire-based structured interviews were undertaken to evaluate the empirical and theoretical findings further. The research results indicate that trust-, reciprocity-, market-, and contract-based KGMs have positive effects on product quality, efficiency, flexibility, responsiveness, and process quality of AFSC. Furthermore, market-based KGM, located in the lowest level in the TISM hierarchy, should be given additional focus due to its role as a key force driving the higher level of AFSC performance and other KGMs. The findings provide AFSC practitioners with useful guidance on how the relationships between KGMs and AFSC performance should be managed to improve the performance of AFSC

Facilitate Knowledge Communications in Multimedia e-learning Environments

International audienceWith current multimedia information management techniques, the knowledge communications among users in multimedia e-Learning environments are still limited at a relative low single type media servicing level. New developments in multimedia knowledge discovery, representation and integration are needed to improve the intelligence of the knowledge management and communications at the semantic level. This paper proposes a novel contextual knowledge management framework to improve the current isolated learning information retrieval and communication status, by enabling flexible knowledge representation beyond heterogeneous multimedia learning resources and facilitating multilevel knowledge communications between instructors and learners. Based on knowledge communication model analysis in university e-Learning environments, a contextual knowledge representation model is presented. Corresponding knowledge retrieval techniques are discussed afterwards. To demonstrate the proposed concepts and techniques, a case study in a virtual scenario-based learning environment shows how the presented framework works with existing e-Learning content description standards and multimedia information retrieval techniques, and consequently enables a semantic-based interactive learning environment