Designing Fuzzy Expert System to Identify Child Intelligence

Every child is special and has her/his own unique potential. Identifying child’s potential in early age is important for teaching purpose since every child has difference intelligence and interest. Therefore children’s teaching and learning process should be delivered based on child’s interest and intelligence, instead of forcing children to excel in every subject. We propose our research to identify child’s intelligence by designing fuzzy expert system. The system works based on several input data of children’s multiple intelligences. The fuzzy expert system is developed using 25 input variables and resulted in 9 output variables. The system classifies the result based on 9 types of intelligence in human, where each exhibits different level. We produce 81 rules with fuzzy set of three different levels value (high, moderate, or low) for every kind of intelligence. The result of this research is very useful to help parents and teachers for determining their method of teaching based on children’s potential

Improving Computer Based Speech Therapy Using a Fuzzy Expert System

In this paper we present our work about Computer Based Speech Therapy systems optimization. We focus especially on using a fuzzy expert system in order to determine specific parameters of personalized therapy, i.e. the number, length and content of training sessions. The efficiency of this new approach was tested during an experiment performed with our CBST, named LOGOMON