Recently, there has been an increased interest in producing electronic courses. However, literature shows that adopting E-learning does not guarantee improved learning. This is because mixing technology and content does not necessarily yield effective learning. This paper presents a systematic design process for developing blended courses. The instructional design process is based on Bloom Taxonomy, Redeker Taxonomy and Guerra scale. A mapping model is proposed and embedded in the design process to develop a blended course from the objectives and content of a traditional course. This paper also presents an evaluation process that measures the effectiveness of the selected designed blended course. This effectiveness is evaluated in terms of course content formats, interaction and collaboration. A case study is presented to demonstrate the proposed design approach on a System Analysis and Design blended course under development.
This paper studies the role that ontologies can play in establishing conceptual data models during the process of information systems development. A mapping algorithm has been proposed and embedded in a special purpose Transformation-Engine to generate a conceptual data model from a given domain ontology. In addition, this paper focuses on applying the proposed approach to a bioinformatics context as the nature of biological data is considered a barrier in representing biological conceptual data models. Both quantitative and qualitative methods have been adopted to critically evaluate this new approach. The results of this evaluation indicate that the quality of the generated conceptual data models can reflect the problem domain entities and the associations between them. The results are encouraging and support the potential role that this approach can play in providing a suitable starting point for conceptual data model development.
This paper studies the differences and similarities between domain ontologies and conceptual data models and the role that ontologies can play in establishing conceptual data models during the process of information systems development. A mapping algorithm has been proposed and embedded in a special purpose Transformation Engine to generate a conceptual data model from a given domain ontology. Both quantitative and qualitative methods have been adopted to critically evaluate this new approach. In addition, this paper focuses on evaluating the quality of the generated conceptual data model elements using Bunge-Wand-Weber and OntoClean ontologies. The results of this evaluation indicate that the generated conceptual data model provides a high degree of accuracy in identifying the substantial domain entities along with their attributes and relationships being derived from the consensual semantics of domain knowledge. The results are encouraging and support the potential role that this approach can take part in process of information system development.
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