智能化测量学教学辅助系统与组卷策略的设计及研究  

Design and research of intelligent surveying teaching assistant system and test paper generating scheme

作　　者：何琦敏 宋康明 李黎 连达军[2] 富尔江 张克非 HE Qimin;SONG Kangming;LI Li;LIAN Dajun;FU Erjiang;ZHANG Kefei(Research Center of Beidou Navigation and Environmental Remote Sensing,SUST,Suzhou 215009,China;School of Geography Science and Geomatics Engineering,SUST,Suzhou 215009,China;Guangzhou Urban Planning&Design Survey Research Institute,Guangzhou 510060,China;Bei-Stars Geospatial Information Innovation Institute,Nanjing 211800,China;School of Environment Science and Spatial Informatics,China University of Mining and Technology,Xuzhou 221116,China)

机构地区：[1]苏州科技大学北斗导航与环境感知研究中心,江苏苏州215009 [2]苏州科技大学地理科学与测绘工程学院,江苏苏州215009 [3]广州市城市规划勘测设计研究院,广东广州510060 [4]北星空间信息技术研究院(南京)有限公司,江苏南京211800 [5]中国矿业大学环境与测绘学院,江苏徐州221116

出　　处：《苏州科技大学学报（自然科学版）》2024年第1期61-68,共8页Journal of Suzhou University of Science and Technology（Natural Science Edition）

基　　金：国家自然科学基金项目(42274021,41730109,41874040);江苏省双创人才项目(JSSCRC2022281);苏州市产业前瞻与关键核心技术项目(SYC2022028);苏州科技大学自然科学青年基金项目(XKQ2021006)。

摘　　要：针对当前计算机教学辅助系统中存在的组卷难度和题型比例不合理等问题,以测量学课程为例,提出了多约束条件的组合优化模型,解决了自动化组卷的多指标参数问题,为实现科学的组卷策略提供参考依据。该模型综合考虑试卷的总分、难度、曝光率、题型比例、章节知识量、培养目标等多个方面的要求进行量化加权,建立了智能化组卷的总约束方程,构建了多参数约束的组合优化模型。采用计算机模拟仿真的方法建立了题库,分析了三种启发式搜索算法求解模型的解算精度和效率。结果表明,利用遗传算法实现的自动化组卷的整体精度和效率更高,在总分、难度、曝光率、题型比例、章节知识量和培养目标方面的平均偏差分别为0.2%.0.074、0.1%6.1%、8.2%和9.6%,迭代次数在230次以内基本能够达到最优解。In view of the difficulty and unreasonable proportion of test types in the current computer-assisted teaching system,a combined optimization model with multiple constraints is proposed to solve the problem of multiple index parameters in automatic test composition,which provides reference value for realizing scientific test composition strategy.The model comprehensively considers the total score,difficulty,exposure,proportion of question types,amount of chapter knowledge and training objectives of the test paper,and carries out quantitative weighting,establishes the total constraint equation of intelligent test paper composition,and constructs the combined optimization model with multi-parameter constraints.The question bank was established by computer simulation,and the accuracy and efficiency of three heuristic search algorithms were analyzed.The results show that the overall accuracy and efficiency of the automatic paper composition using genetic algorithm are higher,and the average deviations in total score,difficulty,exposure rate,proportion of question types,amount of chapter knowledge and training objectives are 0.2%,0.074,0.1%,6.1%,8.2%and 9.6%,respectively.The optimal solution can be basically achieved within 230 iterations.

关 键 词：教学辅助系统 启发式搜索算法 测量学 组合优化模型 遗传算法 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]