【作者】 张阳；

【导师】 王东； 张桂华；

【作者基本信息】 湖南大学 ， 计算机技术， 2006， 硕士

【摘要】 飞速发展的计算机网络技术使网络化教学日益成为一种重要的教学手段和教学平台。网络教学与传统教学的最大区别就是赋予了学生充分的学习自主性,使学生成为学习的真正主人。如何在网络教学系统中监督学习效果,使教学双方形成有效地交互与反馈,为教学过程的决策取向提供直接参考依据,网络学习评价系统承担着重要的任务。目前大多数的网络学习评价还是只注重在线测试,仅仅是课堂试卷考试的翻版,不能全面、客观地反映学生对知识的学习过程和掌握程度。我国素质教育强调:既要重视学习结果评价,更应重视学习过程评价,发挥评价对学生的教育、促进作用。评价不应只是学习结束后的总结性判断,而应贯穿整个学习过程。目前我国还没有网络化学习评价的基本标准,因此有必要针对网络学习评价方法进行研究,特别是围绕面向网络学习历程的形成性评价的实施进行研究。本论文针对目前网络学习评价系统中不注重学习者学习历程的评价,单纯用学期考试成绩不能全面、客观地对学生进行评价的问题,构建了一个新的网络学习评价系统。论文从分析网络学习评价的现状、要求和分析网络学习者的特征出发,创设了学习评价环境,改进了学习评价指标;制定一个适合网络教学的学习评价层次模型,特别是建立了非量化与量化相结合的评价体系;运用数据挖掘技术对网页日志中记录的学习活动信息的挖掘,提取影响学生学习成效的关键信息,作为学习历程评价的信息来源;将评价信息构建成三维数据立方体,使得教师可从各个方面来观察学生的学习历程;系统自动统计出学生参与学习活动的频率、时间,计算学生的整体学习活动能力指标值,并提出模糊理论与层次分析法相结合的评价方案,通过层次分析法来制定评价项目间的权重,减少人为因素;对收集起来的学习历程评价信息进行模糊评价,以分数法、模糊等级法作为评价输出,使教师能迅速地得到学生网络学习的全面、综合和客观的评价。实践证明,采用模糊理论与层次分析法相结合的方法来评定学生的综合成绩,既能使教师充分了解学生的在线学习参与情况,又能比较客观、全面地反映学生对所学课程的知识掌握程度。对于教师而言,虽然增加了考核项目,但只需评定模糊等级(优、良、…),操作容易,其余的统计和分析工作均由计算机完成,数据可靠性高,提高了网络学习评价的效率。采用该评价方案的网络学习评价系统的在实际应用中已取得了良好的效果。更多还原

【Abstract】 As the fast development of computer network technology, teaching on the platform of the network has become an important method for effective education. The biggest difference between network teaching and traditional teaching is that the network teaching tends to make students independent and initiative in the process of learning. How to examine the results of learning on the teaching network, and how to help teachers choose their online teaching contents by obtaining effective mutual feedbacks from students have become important tasks of network teaching evaluation system. However, presently, most network teaching evaluation systems are restricted on online tests. They are little different than paper tests, and thus can not be used to evaluate students’learning progress effectively and efficiently. The quality-oriented education in our country has emphasized that not only the evaluation for the learning results should be valued, but also the evaluation for the learning process. Their positive effects on teaching and learning should be valued. In addition, evaluations should run through the whole process of learning, rather than only being done at the end. Our country has not published a standard for the evaluation of network teaching. Therefore, it is necessary to study the methods for network learning evaluation, especially the formative evaluation, which features in the process of network learning.This thesis will construct an innovative network learning evaluation system, which tends to solve the problem that present ineffective network teaching evaluation systems only use test scores for the learning process but do not pay attention to the evaluation . The thesis will start from analyzing the current situation, requirements, and characteristics of students in network learning. Then, it will create an evaluation system and improve the indexes. After that, a learning level evaluation model, which is suitable for the network learning evaluation system, as well as an evaluation system, which consists of quantization and non-quantization, will be proposed. We will use data mining technology to extract useful information from daily studying activities recorded on the web log, especially the key information that will affect students’study results, and use it as the source for learning process evaluation. Then, we will use evaluation information to build up a three-dimensional data cube, which will enable teachers to observe students’learning from every aspect. The system will first automatically collect the frequencies and the time that the students spend on learning, calculate the students’learning ability index, propose an evaluation approach that iscombined with fuzzy theory and analytic hierarchy process, and reduce human factor by making evaluation weights through analytic hierarchy process. Finally, we will apply fuzzy evaluation to the accumulated learning process evaluation information, and export the results in scores or fuzzy grades, which would help teachers to get overall, comprehensive and objective students’network learning evaluation.Being proved in practice, the method, which uses fuzzy theory and analytic hierarchy process to evaluate students’overall achievement, will provide objective and comprehensive information to help teachers to completely know how students learn online. Although, to evaluate how well the students’master of knowledge objectively and completely will increase examinations, the evaluation only needs to be graded fuzzily, such as excellent, good, and etc. Teachers can leave the calculations and statistical work to the computer, which is very easy to handle. This method will enhance the reliability of the data and the efficiency of network learning evaluation. The evaluation system which adopts the method proposed in the paper has obtained a good result in practical applications.更多还原