Fuzzy logic approach for adaptive test sheet generation in e-learning

Good quality test refers to the ability of questions to test the student's cognitive abilities in the most efficient manner. The task of designing and developing a question paper for an adaptive e-learning system depends on organization of questions, concept, activity and learner level. In order to perform a better adaptation or Personalization we propose an e-test classify based on Bloom's classification, also known as taxonomy of learning objective for different type of learner model like rote learner, analytical learner, example base learner, analogy and deductive learner and commonsense based learner. In this paper we use fuzzy approach to evaluate student preferable test in e-learning environment.