Comparative Study of Different Approaches for Measuring Difficulty Level of Question

Abstract

Semantics-based information representations such as ontologies are found to be very useful in repeatedly generating important factual questions. Formative the difficulty-level Of these system generated questions is helpful to successfully make use of them in various learning and specialized applications. The accessible approaches for result the difficulty-level of factual questions are very simple and are limited to a few basic principles. We suggest a new tactic for this problem by considering an edifying theory called Item Response Theory (IRT).In the IRT, facts skill of end users (learners) are considered for assigning difficulty levels, because of the assumptions that a given question is apparent differently by learners of various proficiencies. We have done a detailed study on the features/factors of a question statement which could perhaps determine its difficulty-level for three learner categories (experts, intermediates, and easy).