Analysis And Design Of Knowledge-processing-based Adaptive Tutoring Test System

Tests are important means of examining teaching effects and reinforce the learning contents. Computerized adaptive testing,a hot research topic of test theory, meets the personalized requirements of the testee that tailoring the difficulty of testing to testee's ability level, but less attention of knowledge structure are focused on testing process so as to weak parts of knowledge field weren't realized by testee. This defect is solved in the adaptive tutoring test system based on knowledge space theory discussed in this paper, which not only successively selects questions to maximize the precision of the test based on testee's knowledge, but also instructs the testee to learn the content close to acquired knowledge structure.After introduction and analysis of item response theory, the reason of choosing IRT-based adaptive test was presented. Knowledge space theory(KST) was introduced according to the characteristics and expression of knowledge, in which six questions as preconditions restricted, its Hasse map, knowledge spatial base and knowledge boundary were discussed.Combined database and teaching design, the system modules and their functions were analyzed and designed. Some parts were mainly emphasized, such as knowledge structure of University Physics, strategies of question presented, evaluation factors and rules as well as places maps for calculation. Moreover, a test example on Static Electric Field was demonstrated that how to integrate adaptive testing and KST in this system.