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Case-based analysis in user requirements modelling for knowledge construction

By Lily Sun and Cleopa Mushi

Abstract

Context: Learning can be regarded as knowledge construction in which prior knowledge and experience\ud serve as basis for the learners to expand their knowledge base. Such a process of knowledge construction\ud has to take place continuously in order to enhance the learners’ competence in a competitive working\ud environment. As the information consumers, the individual users demand personalised information provision\ud which meets their own specific purposes, goals, and expectations.\ud Objectives: The current methods in requirements engineering are capable of modelling the common\ud user’s behaviour in the domain of knowledge construction. The users’ requirements can be represented\ud as a case in the defined structure which can be reasoned to enable the requirements analysis. Such analysis\ud needs to be enhanced so that personalised information provision can be tackled and modelled. However,\ud there is a lack of suitable modelling methods to achieve this end. This paper presents a new\ud ontological method for capturing individual user’s requirements and transforming the requirements onto\ud personalised information provision specifications. Hence the right information can be provided to the\ud right user for the right purpose.\ud Method: An experiment was conducted based on the qualitative method. A medium size of group of users\ud participated to validate the method and its techniques, i.e. articulates, maps, configures, and learning content.\ud The results were used as the feedback for the improvement.\ud Result: The research work has produced an ontology model with a set of techniques which support the\ud functions for profiling user’s requirements, reasoning requirements patterns, generating workflow from\ud norms, and formulating information provision specifications.\ud Conclusion: The current requirements engineering approaches provide the methodical capability for\ud developing solutions. Our research outcome, i.e. the ontology model with the techniques, can further\ud enhance the RE approaches for modelling the individual user’s needs and discovering the user’s\ud requirements

Publisher: Elsevier
Year: 2010
OAI identifier: oai:centaur.reading.ac.uk:5737

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