Fuzzy students� knowledge modelling system through revised bloom�s taxonomy

The conveniences of web-based educational systems have attracted a large heterogeneous group of learners with various knowledge levels,learning goals,and others learning characteristics,to study online. to enhance the effectiveness of the web-based educational system in delivery knowledge,a system should be capable to identify the learners� learning characteristics,and adapt the instructional process accordingly. hence,this paper presented a students� knowledge modelling system that is capable of infer and updating the students� knowledge level in accordance to the cognitive processes dimension in the revised bloom�s taxonomy. however,the students� knowledge modeling process consists of tasks and factors that are vague and unmeasured,thus fuzzy logic is integrated into the students� knowledge modeling system to deal with such uncertainties. the proposed fuzzy students� knowledge modeling system uses fuzzy sets to represent students� knowledge level and other influencing factors,and uses mamdani type inference technique to determine and update knowledge levels.