Research Of Auto-Generating Test Paper Algorithm In Intelligent Tutoring System

Auto-generating test paper is a multi-target parameter optimization question with certain restraint conditions in Intelligent Tutoring System and is difficult to be solved with traditional mathematics methods.The efficiency and the quality of Auto-generating test paper is completely depended on the design of the question bank and the Auto-generating:test paper algorithm.The Intelligent Examination System based on Item Response Theory can be traced back to the middle of 1980's.It is an important part of the Intelligent Tutoring System and modern measurement research.Its main trait is to construct an optimal test for each examinee,and this is implement by estimating the examinee's ability.The final grade will be independent of examination items choosing. Intelligence Examination System can be used to measure the real capabilities of the examinees more exactly and more impersonality and quickly.But it brings about a problem in psychometrics that how to comine information quantity with content and other non-psychometrics characteristics.The main contents include:1.The present situation of Auto-generating test paper algorithm and several common methods of Auto-generating test paper are analysed.The mathematical model of Auto-generating test paper question based on IRT is constructed.2.With the research on simple genetic algorithm,the prematurely and the low convergence speed of simple genetic algorithm are discovered.So the paper improves some aspects of genetic algorithms used to deal with the premature and the low convergence speed of genetic algorithm,such as coding strategy, the definition of fitness function,the design of genetic operators and the combination of the Adaptive Technology and the Niching Technology etc.The improved Auto-generating test paper algorithm is tested with three different types of test functions.The test results show that the improved Auto-generating test paper algorithm can improve the convergence speed and the algorithm is quite robust. 3.The proper coding strategy and fitness function are designed according to the traits of automatic group volume question and applies the improved Auto-generating test paper algorithm to the Auto-generating test paper question with the simulation question bank example.The example indicates that the improved Auto-generating test paper algorithm can be successfully applied in the Auto-generating test paper and could solve constraint optimization problems with good performance and practicability.Furthermore,the success rate and efficiency is also high.