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基于Web的计算机自适应测验的设计 总被引:2,自引:0,他引:2
扼要介绍了计算机化自适应测验的理论基础--项目反应理论(IRT),在此基础上着重阐述了基于网络的前台在线自适应测验的设计、施测系统主程序的结构流程及计算机化自适应测验优点和应用前景。 相似文献
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基于Web的化学计算机化自适应测验系统的实现 总被引:1,自引:0,他引:1
在IRT理论和双参数Logistic模型的基础上,规划了基于Web的化学计算机化自适应测验系统。在实现该系统过程中,建立起包括item表、user表和calculation表在内的后台测验试题库;用HTML语言完成了用户使用的前台界面;用Visual Basic语言写出了包含有多个模块的CGI应用程序,使网络得以与试题库进行动态连接,从而实现了使国内外用户能够通过网络进行化学在线自适应测验的既定研究目标。 相似文献
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考试是教学活动中最重要的环节之一,传统的考试方式在面对当前的社会发展形势时,无论从效率、成本、公平性等方面来看都存在许多问题。如何解决传统考试方式所固有的弊病,已经成为一个急需解决的问题。介绍了针对《C语言程序设计》课程而开发的基于项目反应理论的计算机自适应测验系统的设计和开发。 相似文献
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计算机化自适应测验CAT(Computerized Adaptive Testing)中的选题策略,一直是国内外相关学者关注的问题。选题策略是计算机自适应测验研究的一项重要内容,它的好坏直接关系到考试的信度、效度及考试的安全性。采用计算机模拟程序对影响a分层选题策略的各因素进行研究。得出了包括测试的终止条件应设为已测项目的信息总量或题目总数达到事先预定标准,层次划分数应为15层,各层信息量所占比例应逐渐上升,项目难度参数应服从均匀分布等各因素的最佳状态,实验证明,优化了a分层选题策略,能显著提高计算机自适应测验的准确性和稳定性。 相似文献
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计算机自适应考试的理论模型研究 总被引:6,自引:0,他引:6
阐述了教育测量的两种主要理论,即经典测试理论(Qassical Test Theory,CTT)和项目反应理论(Item Response Theory,IRT)。其中IRT是计算机自适应测试CAT的理论基础。介绍了IRT和CTT相比的优点和几种IRT模型,并以三参数Logistic模型为典型代表论述了Logistic模型的基本理论。 相似文献
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随着教育测试理论的不断发展,计算机自适应测试得到了广泛的研究与应用,本文在项目反应理论的基础上,采用三参数Logistic模型进行研究,提出了一种有效的计算机自适应测试算法,从而提高测试的效率和准确性,实现对应试者能力水平的估计。 相似文献
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吴志新 《计算机技术与发展》2005,15(2)
测试是远程教育系统的重要组成部分之一.计算机自适应测试具有测试精度高、速度快等优点,但目前在远程教育中应用的还较少.文中在对自适应测试理论的研究基础上,指出了自适应测试在应用中存在一些主要问题,提出了利用XML按照教育资源规范进行IRT试题描述的方法,解决了IRT题库的建设和共享问题.结合Java技术较好地解决了自适应测试中的计算量大的问题,最后简单地描述了系统的实现过程,并给出了系统的设计模式. 相似文献
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基于XML的计算机自适应测试技术的应用研究 总被引:3,自引:0,他引:3
测试是远程教育系统的重要组成部分之一。计算机自适应测试具有测试精度高、速度快等优点,但目前在远程教育中应用的还较少。文中在对自适应测试理论的研究基础上,指出了自适应测试在应用中存在一些主要问题,提出了利用XML按照教育资源规范进行IRT试题描述的方法,解决了IRT题库的建设和共享问题。结合Java技术较好地解决了自适应测试中的计算量大的问题,最后简单地描述了系统的实现过程,并给出了系统的设计模式。 相似文献
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With the rapid growth of computer and Internet technologies, e-learning has become a major trend in the computer assisted teaching and learning field. Previously, many researchers put effort into e-learning systems with personalized learning mechanism to aid on-line learning. However, most systems focus on using learner’s behaviors, interests, and habits to provide personalized e-learning services. These systems commonly neglect to consider if learner ability and the difficulty level of the recommended courseware are matched to each other. Frequently, unsuitable courseware causes learner’s cognitive overload or disorientation during learning. To promote learning effectiveness, our previous study proposed a personalized e-learning system based on Item response theory (PEL-IRT), which can consider both course material difficulty and learner ability evaluated by learner’s crisp feedback responses (i.e. completely understanding or not understanding answer) to provide personalized learning paths for individual learners. The PEL-IRT cannot estimate learner ability for personalized learning services according to learner’s non-crisp responses (i.e. uncertain/fuzzy responses). The main problem is that learner’s response is not usually belonging to completely understanding or not understanding case for the content of learned courseware. Therefore, this study developed a personalized intelligent tutoring system based on the proposed fuzzy item response theory (FIRT), which could be capable of recommending courseware with suitable difficulty levels for learners according to learner’s uncertain/fuzzy feedback responses. The proposed FIRT can correctly estimate learner ability via the fuzzy inference mechanism and revise estimating function of learner ability while the learner responds to the difficulty level and comprehension percentage for the learned courseware. Moreover, a courseware modeling process developed in this study is based on a statistical technique to establish the difficulty parameters of courseware for the proposed personalized intelligent tutoring system. Experiment results indicate that applying the proposed FIRT to web-based learning can provide better learning services for individual learners than our previous study, thus helping learners to learn more effectively. 相似文献
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Harutyun Terteryan 《计算机技术与应用:英文》2014,(1):21-24
This paper studies the technics of reducing item exposure by utilizing automatic item generation methods. Known test item calibration method uses item parameter estimation with the statistical data, collected during examinees prior testing. Disadvantage of the mentioned item calibration method is the item exposure; when test items become familiar to the examinees. To reduce the item exposure, automatic item generation method is used, where item models are being constructed based on already calibrated test items without losing already estimated item parameters. A technic of item model extraction method from the already calibrated and therefore exposed test items described, which can be used by the test item development specialists to integrate automatic item generation principles with the existing testing applications. 相似文献
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基于自适应遗传算法的智能组卷研究 总被引:20,自引:1,他引:20
计算机辅助教学CAI(Computer Assisted Instruction)的一个重要应用是计算机辅助测验CBT(Computer Based Testing).智能组卷是CBT的基础.组卷中关键是解决约束优化问题.在研究现代教育测试理论与计算机辅助测验CBT的基础上.提出一种解决计算机组卷中约束优化问题的方法,自适应遗传算法,该方法有效地解决了基于IRT的智能组卷问题,为解决约束优化问题提供一种新的有效途径.具有较好的性能和实用性. 相似文献