A study of problem difficulty evaluation for semantic network ontology based intelligent courseware sharing

Testing and evaluation is an integral part of the learning process. Educators have often tried to device methods for design of test-ware. Intelligent design and compilation of test-ware is a very interesting problem with immense applications. This research aims at automating the process of intelligent design of test-ware by providing qualitative assessment of questions. In this attempt, we provide some synthetic parameters for the evaluation of question in its concept space. The parameters are tested in some real world scenarios and intuitive inferences are deduced predicting the performance of the parameters. It is observed that the difficulty of a question is often a function of the concepts it tests. Concept knowledge can be represented in the form of linked concepts in semantic nets, the links representing the relationships between the concepts. If this directed graph is known, complexity of a question can be computed by synthetic means.