ZhouYanfang and Tao Zhiqiong.  Management of Teaching Questions Database Based on Improved Random Extraction Algorithm.  Dynamic Systems and Applications 29 (2020) No. 3, 636-647

https://doi.org/10.46719/dsa202029318

ABSTRACT. The computer network platform is widely used in the examination process of China colleges and universities to realize the management of test paper formation. The overall efficiency of the examination operation has been greatly improved, but the existing algorithm of test paper formation is difficult to meet the requirements. Based on this, an improved random extraction algorithm is proposed to realize the management of the test question bank for teaching. The current research progress of teaching question bank in universities is briefly analyzed, and the application of the random extraction algorithm to the test question bank is analyzed. Describing the design of random extraction parameters of the test database, the random extraction algorithm is improved based on the shortcomings of existing algorithms. When the number of test questions is determined, it covers the widest range of knowledge points and has the lowest exposure rate. At the same time, it supports non test. Through the system test, the improved random extraction algorithm designed has higher application in the management of the test question bank for teaching, and it runs stably. The performance is good, which basically meets the needs of the management of the test database for teaching.

Keywords. Random extraction algorithm; test question bank; question score; test difficulty