A knowledge-based consultancy system using ICT Newhouse indicators with reasoning techniques for consultants in e-learning

Abstract

In e-learning evaluation plays an important role in learning management systems. In this article we present a knowledge-based consultancy system designed to enable novel methods for web-based training with advanced features. This study aims to develop a new approach using ICT Newhouse indicators with reasoning techniques capable of handling both explicit and tacit knowledge using a fuzzy rule-based approach in which linguistic (semantic) terms are used to express rules and preferences. The fuzzy rules are implemented using forward and backward chaining techniques. Evaluation of our proposed approach has utilised testing using 12 courses at Hanoi University of Science and Technology with experts feedback using the three reasoning rule levels in the knowledge base to realise precise definition(s) of performance and quality of outcomes. Experimental results derived in the third layer demonstrate that the proposed approach achieved is the highest being in the range of 84% to 90% compared to expert's responses in respect of the correct answers, combined events, and results of other rules in the knowledge base. As compared to alternative conventional approaches which use forward and backward chaining, the performance of the proposed approach shows improvements measured by responses in real-time when applied to the web-based training with automated reasoning dialogue consultants.