【摘要】 在计算机自适应性测验 (CAT)中 ,传统的项目选题策略正面对越来越多的问题 ,比如 :测验的安全 ,项目的曝光率 ,项目的平衡应用等等。分层选题策略的新发展 -A -STR和BAS -选题策略部分地解决了传统的选题策略所面临的难题。能够有效地控制高区分度项目的曝光率 ,增加低区分度项目的曝光率 ,平衡项目的应用 ,提高测验效率 ,降低测验成本等等。为计算机自适应测验的选题策略提供了一种更加有效的方法 ,也为我国开展计算机自适应测验提供了一种思路更多还原

【Abstract】 The traditional item selection method in CAT are facing more and more problems just like the safety of testing, item exposure rate and the balance of item usage etc. The new improvement of a stratified selection method-A STR and BAS-can partly solve these difficult problems. A STR and BAS can effectively control the exposure rate of high discriminating items, increase the exposure rate of low discriminating items, balance the item usage, improve the testing efficiency and decrease the cost of testing management. BAS and a STR provide a more powerful method for CAT item selection and also strike out a new idea for developing CAT in China.更多还原