40 research outputs found

    A Tool for Automatic Creation of Rule-Based Expert Systems with CFs

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    The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study

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    The use of e-learning in higher education has increased significantly in recent years, which has led to several studies being conducted to investigate the usability of the platforms that support it. A variety of different usability evaluation methods and attributes have been used, and it has therefore become important to start reviewing this work in a systematic way to determine how the field has developed in the last 15 years. This paper describes a systematic mapping study that performed searches on five electronic libraries to identify usability issues and methods that have been used to evaluate e-learning platforms. Sixty-one papers were selected and analysed, with the majority of studies using a simple research design reliant on questionnaires. The usability attributes measured were mostly related to effectiveness, satisfaction, efficiency, and perceived ease of use. Furthermore, several research gaps have been identified and recommendations have been made for further work in the area of the usability of online learning

    CONSTRUCTING MODULAR HYBRID RULE BASES FOR EXPERT SYSTEMS

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    Multi-inference with Multi-neurules

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    Neurules are a type of hybrid rules combining a symbolic and a connectionist representation. There are two disadvantages of neurules. The first is that the created neurule bases usually contain multiple representations of the same piece of knowledge. Also, the inference mechanism is rather connectionism oriented than symbolism oriented, thus reducing naturalness. To remedy these deficiencies, we introduce an extension to neurules, called multineurules, and an alternative inference process, which is rather symbolism oriented. Experimental results comparing the two inference processes are also presented
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