多媒体网络教学系统及评教算法研究

发布时间：2018-03-02 07:03

本文关键词： 网络平台课程 Moodle框架神经网络算法教学评价　出处：《华东理工大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着网络技术和计算机软硬件技术的飞速发展,很多国内外的大学和各种教育机构都陆续开设了远程教育,通过构建计算机网络教学平台实现异地教育和培训。利用多媒体网络平台,可以更加高效的分享信息与资源,真正实现教与学分离的远程教育和培训,对于教育信息化的发展具有重要的意义和深远的影响。多媒体网络教学系统是集网络课程发布、远程教学及评价系统为一体的教学辅助系统,是校园管理系统的重要组成部分,其功能主要是将远程教育与课堂教学进行有效结合,通过教师在网络上发布一些课程的信息,教学课件,课后习题,问题解答等,辅助传统的课堂教学,并且通过给学生提供阶段性的测试以检测学生的学习情况,以及实现学生在线的教学质量评估。通过该教学辅助系统,学生能更方便的预习及复习课堂内容,在线完成作业,在线学习情况评估,也便于与教师及其他同学进行交流,对所学知识进行测验,并且可以将自己的意见和建议反馈给教师,形成合理的教学质量评价。本文采用基于PHP及Moodle框架技术搭建了多媒体网络教学系统平台,实现了诸如在线课堂、在线考试、在线备课、习题发布及解答、教学评价等功能。为了将程序嵌入到HTML文档中去执行,并且得到很高的执行效率,因此选择PHP执行编译后的代码,实现编译加密和提升代码运行效率。同时利用PHP能实现CGI全部功能,并支持当今所有主流操作系统及数据库的特点,结合Moodle框架技术搭建系统平台。本文在多媒体网络教学平台的开发过程中,创新地将优化遗传算法引用到教学评估模块中,并对原来的基于神经网络的评估算法进行了改进,对非指定神经网络的权值进行优化,缩小搜索空间范围,达到从全局中寻找最优、最快的效果,用于对课堂及网络教学的教学情况进行有效评估。经过遗传算法优化的BP神经网络算法模型,在实验后发现其既具有神经网络的学习功能,又能增强遗传算法的全局随机查询能力。因此,数据的自动获取和空间知识的累积搜索以及搜索过程中自适应控制性也得到显著提升,分析得出的结论更为真实有效。
[Abstract]:With the rapid development of network technology and computer hardware and software technology, many universities and various educational institutions at home and abroad have set up distance education one after another. Through constructing the computer network teaching platform to realize the remote education and training, the multimedia network platform can be used to share information and resources more efficiently and realize the distance education and training which is separated from teaching and learning. The multimedia network teaching system is a teaching assistant system which integrates the network course issue, the distance teaching and the evaluation system, and is an important part of the campus management system. Its function is to effectively combine distance education with classroom teaching, and to assist traditional classroom teaching by publishing some information of courses, teaching courseware, after-class exercises, problem solving and so on. And by providing the students with periodic tests to test the students' learning situation and realize the students' online teaching quality evaluation, the students can more conveniently preview and review the classroom content and finish their homework online through the teaching aid system. Online learning assessment also facilitates communication with teachers and other students, tests what they have learned, and can feed back their opinions and suggestions to teachers. This paper uses PHP and Moodle framework technology to build a multimedia network teaching system platform, such as online classroom, online examination, online lesson preparation, exercise issue and solution. In order to embed the program into the HTML document to execute, and get very high execution efficiency, so choose PHP to execute the compiled code, At the same time, we can realize all the functions of CGI by using PHP, and support the characteristics of all the mainstream operating systems and databases. In the course of the development of multimedia network teaching platform, this paper innovatively applies the optimized genetic algorithm to the teaching evaluation module, and improves the original evaluation algorithm based on neural network. The weights of the non-specified neural networks are optimized to narrow the search space to find the best and fastest result from the overall situation. The BP neural network algorithm model, which is optimized by genetic algorithm, is found to have the learning function of neural network after experiment. Therefore, the automatic acquisition of data, the cumulative search of spatial knowledge and the adaptive control in the search process are also significantly improved, and the conclusion is more real and effective.
【学位授予单位】：华东理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP311.52;TP183

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