Building students´ models based on an enhanced concept-effect relationship in intelligent tutoring systems

The algorithm of an enhanced concept effect relationship is applied into the assessment of chemistry learning (the topic is focus on Redox). The research results indicate that the cognitive level of students´ Redox learning can be analyzed effectively and the misconceptions and lacuna in the students´ cognitive structure can be measured accurately. Some suggestions of different learning paths are put forward to improve learning effect. Enhanced concept effect relationship is proved to be a good theory to construct students´ model in the chemistry intelligent tutor system.