Abstract
This paper describes a definition of complexity of questions for a question and answer function in an intelligent support system for English learning, and its evaluation. To realize adaptive question and answer, the system should generates questions depending on both educational intentions and the learner's understanding state. For generating suitable questions for the learner automatically, we must investigate the factors which influence difficulty of questions, and prepare the mechanism to calculate the difficulty. The difficulty is composed of the learner dependent part and the independent part. The former is evaluated by referring to a student model. The latter is defined by enumerating factors which influence complexity of questions. We present a definition of the complexity along with learners' answering flow; understanding text sentences, understanding a question and composing an answer. Moreover, we describe experimentation comparing the complexity of questions calculated by computer according to the definition with the complexity evaluated by human.
