本文關(guān)鍵詞： 網(wǎng)絡(luò)平臺課程 Moodle框架 神經(jīng)網(wǎng)絡(luò)算法 教學(xué)評價　出處：《華東理工大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著網(wǎng)絡(luò)技術(shù)和計算機軟硬件技術(shù)的飛速發(fā)展,很多國內(nèi)外的大學(xué)和各種教育機構(gòu)都陸續(xù)開設(shè)了遠程教育,通過構(gòu)建計算機網(wǎng)絡(luò)教學(xué)平臺實現(xiàn)異地教育和培訓(xùn)。利用多媒體網(wǎng)絡(luò)平臺,可以更加高效的分享信息與資源,真正實現(xiàn)教與學(xué)分離的遠程教育和培訓(xùn),對于教育信息化的發(fā)展具有重要的意義和深遠的影響。多媒體網(wǎng)絡(luò)教學(xué)系統(tǒng)是集網(wǎng)絡(luò)課程發(fā)布、遠程教學(xué)及評價系統(tǒng)為一體的教學(xué)輔助系統(tǒng),是校園管理系統(tǒng)的重要組成部分,其功能主要是將遠程教育與課堂教學(xué)進行有效結(jié)合,通過教師在網(wǎng)絡(luò)上發(fā)布一些課程的信息,教學(xué)課件,課后習(xí)題,問題解答等,輔助傳統(tǒng)的課堂教學(xué),并且通過給學(xué)生提供階段性的測試以檢測學(xué)生的學(xué)習(xí)情況,以及實現(xiàn)學(xué)生在線的教學(xué)質(zhì)量評估。通過該教學(xué)輔助系統(tǒng),學(xué)生能更方便的預(yù)習(xí)及復(fù)習(xí)課堂內(nèi)容,在線完成作業(yè),在線學(xué)習(xí)情況評估,也便于與教師及其他同學(xué)進行交流,對所學(xué)知識進行測驗,并且可以將自己的意見和建議反饋給教師,形成合理的教學(xué)質(zhì)量評價。本文采用基于PHP及Moodle框架技術(shù)搭建了多媒體網(wǎng)絡(luò)教學(xué)系統(tǒng)平臺,實現(xiàn)了諸如在線課堂、在線考試、在線備課、習(xí)題發(fā)布及解答、教學(xué)評價等功能。為了將程序嵌入到HTML文檔中去執(zhí)行,并且得到很高的執(zhí)行效率,因此選擇PHP執(zhí)行編譯后的代碼,實現(xiàn)編譯加密和提升代碼運行效率。同時利用PHP能實現(xiàn)CGI全部功能,并支持當(dāng)今所有主流操作系統(tǒng)及數(shù)據(jù)庫的特點,結(jié)合Moodle框架技術(shù)搭建系統(tǒng)平臺。本文在多媒體網(wǎng)絡(luò)教學(xué)平臺的開發(fā)過程中,創(chuàng)新地將優(yōu)化遺傳算法引用到教學(xué)評估模塊中,并對原來的基于神經(jīng)網(wǎng)絡(luò)的評估算法進行了改進,對非指定神經(jīng)網(wǎng)絡(luò)的權(quán)值進行優(yōu)化,縮小搜索空間范圍,達到從全局中尋找最優(yōu)、最快的效果,用于對課堂及網(wǎng)絡(luò)教學(xué)的教學(xué)情況進行有效評估。經(jīng)過遺傳算法優(yōu)化的BP神經(jīng)網(wǎng)絡(luò)算法模型,在實驗后發(fā)現(xiàn)其既具有神經(jīng)網(wǎng)絡(luò)的學(xué)習(xí)功能,又能增強遺傳算法的全局隨機查詢能力。因此,數(shù)據(jù)的自動獲取和空間知識的累積搜索以及搜索過程中自適應(yīng)控制性也得到顯著提升,分析得出的結(jié)論更為真實有效。
[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.
【學(xué)位授予單位】：華東理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP311.52;TP183

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